superstore_analysis.ipynb

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        "<a href=\"https://colab.research.google.com/github/minchillo4/sales_proj/blob/main/superstore_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "source": [
        "LOADING FILES\n"
      ],
      "metadata": {
        "id": "78lb6afJG47s"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "ECOltcpBeg_A"
      }
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        "colab": {
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        "outputId": "e365ffa9-47b1-46af-ff63-92014908be04"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import files\n",
        "import sqlite3\n",
        "import pandas as pd\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "uploaded = files.upload()"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "evdJjtTfKD49",
        "outputId": "26ab5a8d-9e48-41fe-fd9a-c43dc1097c52"
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      "outputs": [
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              "\n",
              "     <input type=\"file\" id=\"files-4c92cf15-ea30-4eca-86e8-a66f0f6b5894\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
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              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
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              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
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              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
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              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
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              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
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              "          file: file.name,\n",
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              "        },\n",
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              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
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              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving superstore_dataset.csv to superstore_dataset.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "conn = sqlite3.connect(':memory:')\n",
        "cursor = conn.cursor()"
      ],
      "metadata": {
        "id": "UsUjgqpiKGKG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"superstore_dataset.csv\", encoding=\"latin-1\") ## Criando o dataframe inicial\n",
        "df"
      ],
      "metadata": {
        "id": "irFPA81i6YXU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 926
        },
        "outputId": "e9afba23-675d-401b-d104-233ca06843a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Row ID        Order ID  Order Date   Ship Date       Ship Mode  \\\n",
              "0          1  CA-2016-152156   11/8/2016  11/11/2016    Second Class   \n",
              "1          2  CA-2016-152156   11/8/2016  11/11/2016    Second Class   \n",
              "2          3  CA-2016-138688   6/12/2016   6/16/2016    Second Class   \n",
              "3          4  US-2015-108966  10/11/2015  10/18/2015  Standard Class   \n",
              "4          5  US-2015-108966  10/11/2015  10/18/2015  Standard Class   \n",
              "...      ...             ...         ...         ...             ...   \n",
              "9989    9990  CA-2014-110422   1/21/2014   1/23/2014    Second Class   \n",
              "9990    9991  CA-2017-121258   2/26/2017    3/3/2017  Standard Class   \n",
              "9991    9992  CA-2017-121258   2/26/2017    3/3/2017  Standard Class   \n",
              "9992    9993  CA-2017-121258   2/26/2017    3/3/2017  Standard Class   \n",
              "9993    9994  CA-2017-119914    5/4/2017    5/9/2017    Second Class   \n",
              "\n",
              "     Customer ID     Customer Name    Segment        Country             City  \\\n",
              "0       CG-12520       Claire Gute   Consumer  United States        Henderson   \n",
              "1       CG-12520       Claire Gute   Consumer  United States        Henderson   \n",
              "2       DV-13045   Darrin Van Huff  Corporate  United States      Los Angeles   \n",
              "3       SO-20335    Sean O'Donnell   Consumer  United States  Fort Lauderdale   \n",
              "4       SO-20335    Sean O'Donnell   Consumer  United States  Fort Lauderdale   \n",
              "...          ...               ...        ...            ...              ...   \n",
              "9989    TB-21400  Tom Boeckenhauer   Consumer  United States            Miami   \n",
              "9990    DB-13060       Dave Brooks   Consumer  United States       Costa Mesa   \n",
              "9991    DB-13060       Dave Brooks   Consumer  United States       Costa Mesa   \n",
              "9992    DB-13060       Dave Brooks   Consumer  United States       Costa Mesa   \n",
              "9993    CC-12220      Chris Cortes   Consumer  United States      Westminster   \n",
              "\n",
              "      ... Postal Code  Region       Product ID         Category Sub-Category  \\\n",
              "0     ...       42420   South  FUR-BO-10001798        Furniture    Bookcases   \n",
              "1     ...       42420   South  FUR-CH-10000454        Furniture       Chairs   \n",
              "2     ...       90036    West  OFF-LA-10000240  Office Supplies       Labels   \n",
              "3     ...       33311   South  FUR-TA-10000577        Furniture       Tables   \n",
              "4     ...       33311   South  OFF-ST-10000760  Office Supplies      Storage   \n",
              "...   ...         ...     ...              ...              ...          ...   \n",
              "9989  ...       33180   South  FUR-FU-10001889        Furniture  Furnishings   \n",
              "9990  ...       92627    West  FUR-FU-10000747        Furniture  Furnishings   \n",
              "9991  ...       92627    West  TEC-PH-10003645       Technology       Phones   \n",
              "9992  ...       92627    West  OFF-PA-10004041  Office Supplies        Paper   \n",
              "9993  ...       92683    West  OFF-AP-10002684  Office Supplies   Appliances   \n",
              "\n",
              "                                           Product Name     Sales  Quantity  \\\n",
              "0                     Bush Somerset Collection Bookcase  261.9600         2   \n",
              "1     Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400         3   \n",
              "2     Self-Adhesive Address Labels for Typewriters b...   14.6200         2   \n",
              "3         Bretford CR4500 Series Slim Rectangular Table  957.5775         5   \n",
              "4                        Eldon Fold 'N Roll Cart System   22.3680         2   \n",
              "...                                                 ...       ...       ...   \n",
              "9989                             Ultra Door Pull Handle   25.2480         3   \n",
              "9990  Tenex B1-RE Series Chair Mats for Low Pile Car...   91.9600         2   \n",
              "9991                              Aastra 57i VoIP phone  258.5760         2   \n",
              "9992  It's Hot Message Books with Stickers, 2 3/4\" x 5\"   29.6000         4   \n",
              "9993  Acco 7-Outlet Masterpiece Power Center, Wihtou...  243.1600         2   \n",
              "\n",
              "      Discount    Profit  \n",
              "0         0.00   41.9136  \n",
              "1         0.00  219.5820  \n",
              "2         0.00    6.8714  \n",
              "3         0.45 -383.0310  \n",
              "4         0.20    2.5164  \n",
              "...        ...       ...  \n",
              "9989      0.20    4.1028  \n",
              "9990      0.00   15.6332  \n",
              "9991      0.20   19.3932  \n",
              "9992      0.00   13.3200  \n",
              "9993      0.00   72.9480  \n",
              "\n",
              "[9994 rows x 21 columns]"
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              "      <th>Row ID</th>\n",
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              "      <td>1</td>\n",
              "      <td>CA-2016-152156</td>\n",
              "      <td>11/8/2016</td>\n",
              "      <td>11/11/2016</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>CG-12520</td>\n",
              "      <td>Claire Gute</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Henderson</td>\n",
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              "      <td>42420</td>\n",
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              "      <td>FUR-BO-10001798</td>\n",
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              "      <td>Bush Somerset Collection Bookcase</td>\n",
              "      <td>261.9600</td>\n",
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              "      <td>CA-2016-152156</td>\n",
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              "      <td>11/11/2016</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>CG-12520</td>\n",
              "      <td>Claire Gute</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
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              "      <td>CA-2016-138688</td>\n",
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              "      <td>6/16/2016</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>DV-13045</td>\n",
              "      <td>Darrin Van Huff</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>United States</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>...</td>\n",
              "      <td>90036</td>\n",
              "      <td>West</td>\n",
              "      <td>OFF-LA-10000240</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Labels</td>\n",
              "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
              "      <td>14.6200</td>\n",
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              "      <td>6.8714</td>\n",
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              "      <td>US-2015-108966</td>\n",
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              "      <td>10/18/2015</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>SO-20335</td>\n",
              "      <td>Sean O'Donnell</td>\n",
              "      <td>Consumer</td>\n",
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              "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
              "      <td>957.5775</td>\n",
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              "      <td>US-2015-108966</td>\n",
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              "      <td>Standard Class</td>\n",
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              "      <td>Sean O'Donnell</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9989</th>\n",
              "      <td>9990</td>\n",
              "      <td>CA-2014-110422</td>\n",
              "      <td>1/21/2014</td>\n",
              "      <td>1/23/2014</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>TB-21400</td>\n",
              "      <td>Tom Boeckenhauer</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Miami</td>\n",
              "      <td>...</td>\n",
              "      <td>33180</td>\n",
              "      <td>South</td>\n",
              "      <td>FUR-FU-10001889</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Furnishings</td>\n",
              "      <td>Ultra Door Pull Handle</td>\n",
              "      <td>25.2480</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "      <td>4.1028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9990</th>\n",
              "      <td>9991</td>\n",
              "      <td>CA-2017-121258</td>\n",
              "      <td>2/26/2017</td>\n",
              "      <td>3/3/2017</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>DB-13060</td>\n",
              "      <td>Dave Brooks</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Costa Mesa</td>\n",
              "      <td>...</td>\n",
              "      <td>92627</td>\n",
              "      <td>West</td>\n",
              "      <td>FUR-FU-10000747</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Furnishings</td>\n",
              "      <td>Tenex B1-RE Series Chair Mats for Low Pile Car...</td>\n",
              "      <td>91.9600</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>15.6332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9991</th>\n",
              "      <td>9992</td>\n",
              "      <td>CA-2017-121258</td>\n",
              "      <td>2/26/2017</td>\n",
              "      <td>3/3/2017</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>DB-13060</td>\n",
              "      <td>Dave Brooks</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Costa Mesa</td>\n",
              "      <td>...</td>\n",
              "      <td>92627</td>\n",
              "      <td>West</td>\n",
              "      <td>TEC-PH-10003645</td>\n",
              "      <td>Technology</td>\n",
              "      <td>Phones</td>\n",
              "      <td>Aastra 57i VoIP phone</td>\n",
              "      <td>258.5760</td>\n",
              "      <td>2</td>\n",
              "      <td>0.20</td>\n",
              "      <td>19.3932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9992</th>\n",
              "      <td>9993</td>\n",
              "      <td>CA-2017-121258</td>\n",
              "      <td>2/26/2017</td>\n",
              "      <td>3/3/2017</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>DB-13060</td>\n",
              "      <td>Dave Brooks</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Costa Mesa</td>\n",
              "      <td>...</td>\n",
              "      <td>92627</td>\n",
              "      <td>West</td>\n",
              "      <td>OFF-PA-10004041</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Paper</td>\n",
              "      <td>It's Hot Message Books with Stickers, 2 3/4\" x 5\"</td>\n",
              "      <td>29.6000</td>\n",
              "      <td>4</td>\n",
              "      <td>0.00</td>\n",
              "      <td>13.3200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9993</th>\n",
              "      <td>9994</td>\n",
              "      <td>CA-2017-119914</td>\n",
              "      <td>5/4/2017</td>\n",
              "      <td>5/9/2017</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>CC-12220</td>\n",
              "      <td>Chris Cortes</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Westminster</td>\n",
              "      <td>...</td>\n",
              "      <td>92683</td>\n",
              "      <td>West</td>\n",
              "      <td>OFF-AP-10002684</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>Acco 7-Outlet Masterpiece Power Center, Wihtou...</td>\n",
              "      <td>243.1600</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>72.9480</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9994 rows × 21 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "\n",
              "  .colab-df-spinner {\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "</div>\n",
              "\n",
              "  <div id=\"id_c778f96b-4c6a-4b81-a7c9-46f1ae071628\">\n",
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              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Transformar nossas colunas Order Date e Ship Date em colunas de data."
      ],
      "metadata": {
        "id": "PTMJDpKQoLX8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Com o dataframe em mãos, podemos analisar a estrutura de seus dados."
      ],
      "metadata": {
        "id": "nY__dnJ0VsGg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.describe())"
      ],
      "metadata": {
        "id": "M-nqa9icPHok",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4c0b5e06-a1ed-4ccd-cb19-2f1e91b64cad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "            Row ID   Postal Code         Sales     Quantity     Discount  \\\n",
            "count  9994.000000   9994.000000   9994.000000  9994.000000  9994.000000   \n",
            "mean   4997.500000  55190.379428    229.858001     3.789574     0.156203   \n",
            "std    2885.163629  32063.693350    623.245101     2.225110     0.206452   \n",
            "min       1.000000   1040.000000      0.444000     1.000000     0.000000   \n",
            "25%    2499.250000  23223.000000     17.280000     2.000000     0.000000   \n",
            "50%    4997.500000  56430.500000     54.490000     3.000000     0.200000   \n",
            "75%    7495.750000  90008.000000    209.940000     5.000000     0.200000   \n",
            "max    9994.000000  99301.000000  22638.480000    14.000000     0.800000   \n",
            "\n",
            "            Profit  \n",
            "count  9994.000000  \n",
            "mean     28.656896  \n",
            "std     234.260108  \n",
            "min   -6599.978000  \n",
            "25%       1.728750  \n",
            "50%       8.666500  \n",
            "75%      29.364000  \n",
            "max    8399.976000  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.info())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5PLRJX-KG79D",
        "outputId": "1d6a7f67-fe1b-4589-b419-70ae19ad6768"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9994 entries, 0 to 9993\n",
            "Data columns (total 21 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   Row ID         9994 non-null   int64  \n",
            " 1   Order ID       9994 non-null   object \n",
            " 2   Order Date     9994 non-null   object \n",
            " 3   Ship Date      9994 non-null   object \n",
            " 4   Ship Mode      9994 non-null   object \n",
            " 5   Customer ID    9994 non-null   object \n",
            " 6   Customer Name  9994 non-null   object \n",
            " 7   Segment        9994 non-null   object \n",
            " 8   Country        9994 non-null   object \n",
            " 9   City           9994 non-null   object \n",
            " 10  State          9994 non-null   object \n",
            " 11  Postal Code    9994 non-null   int64  \n",
            " 12  Region         9994 non-null   object \n",
            " 13  Product ID     9994 non-null   object \n",
            " 14  Category       9994 non-null   object \n",
            " 15  Sub-Category   9994 non-null   object \n",
            " 16  Product Name   9994 non-null   object \n",
            " 17  Sales          9994 non-null   float64\n",
            " 18  Quantity       9994 non-null   int64  \n",
            " 19  Discount       9994 non-null   float64\n",
            " 20  Profit         9994 non-null   float64\n",
            "dtypes: float64(3), int64(3), object(15)\n",
            "memory usage: 1.6+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Order Date'] = pd.to_datetime(df['Order Date'])\n",
        "df['Ship Date'] = pd.to_datetime(df['Ship Date'])\n"
      ],
      "metadata": {
        "id": "U359vplZJ0SU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Checar por valores duplicados"
      ],
      "metadata": {
        "id": "1JEKxanFFJFG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "duplicate_rows = df.duplicated()\n",
        "print(\"Number of duplicate rows:\", duplicate_rows.sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jzW4uaQu7hQG",
        "outputId": "d8017fb0-b8e9-470e-d209-de00962e3463"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of duplicate rows: 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos selecionar a a coluna ROW ID como índice do dataframe, assim ela também terá essa função dentro do SQL."
      ],
      "metadata": {
        "id": "Ck0UVuuXWXjr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.set_index('Row ID', inplace=True)\n"
      ],
      "metadata": {
        "id": "JIsJOALVF9FA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().any()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "io5RuQeB66Bd",
        "outputId": "07600412-29de-4ba8-de9f-80c35e4b295a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Order ID         False\n",
              "Order Date       False\n",
              "Ship Date        False\n",
              "Ship Mode        False\n",
              "Customer ID      False\n",
              "Customer Name    False\n",
              "Segment          False\n",
              "Country          False\n",
              "City             False\n",
              "State            False\n",
              "Postal Code      False\n",
              "Region           False\n",
              "Product ID       False\n",
              "Category         False\n",
              "Sub-Category     False\n",
              "Product Name     False\n",
              "Sales            False\n",
              "Quantity         False\n",
              "Discount         False\n",
              "Profit           False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('/content/drive/My Drive/mydata.csv', index=False)"
      ],
      "metadata": {
        "id": "hjmWquurtm07"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para garantir uma correspondência precisa entre os tipos de dados em meu DataFrame e os tipos de dados em minha tabela SQLite, estou criando um dicionário que mapeia o nome de cada coluna aos seus respectivos tipos de dados. Isso garantirá consistência e precisão ao inserir os dados do DataFrame na tabela do banco de dados."
      ],
      "metadata": {
        "id": "-lftbPFMXebP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "column_types = {\n",
        "    'Order_ID': 'TEXT',\n",
        "    'Order_Date': 'DATE',   # Change to DATE type\n",
        "    'Ship_Date': 'DATE',    # Change to DATE type\n",
        "    'Ship_Mode': 'TEXT',\n",
        "    'Customer_ID': 'TEXT',\n",
        "    'Customer_Name': 'TEXT',\n",
        "    'Segment': 'TEXT',\n",
        "    'Country': 'TEXT',\n",
        "    'City': 'TEXT',\n",
        "    'State': 'TEXT',\n",
        "    'Postal_Code': 'INTEGER',\n",
        "    'Region': 'TEXT',\n",
        "    'Product_ID': 'TEXT',\n",
        "    'Category': 'TEXT',\n",
        "    'Sub_Category': 'TEXT',\n",
        "    'Product_Name': 'TEXT',\n",
        "    'Sales': 'REAL',\n",
        "    'Quantity': 'INTEGER',\n",
        "    'Discount': 'REAL',\n",
        "    'Profit': 'REAL'\n",
        "}"
      ],
      "metadata": {
        "id": "iYKjR6qYQf2J"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Podemeos adicionar os dados para o banco de dados SQLite, usando o dicionário column_types para especificar os tipos e selecionando a coluna Row_ID como índice."
      ],
      "metadata": {
        "id": "J-2Abk4aovPm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_sql('Superstore', conn, if_exists='replace', index=True, index_label='Row_ID',dtype=column_types)"
      ],
      "metadata": {
        "id": "iafiX-6-UuYW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a90bc1ba-02d5-4c94-f729-d211f2c72233"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9994"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "conn.commit() ## Commiting the current transaction."
      ],
      "metadata": {
        "id": "1dDRTD-4QsKo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Após inserirmos nossos dados no banco de dados, podemos agora analisar o esquema da tabela. O esquema nos fornece uma visão estruturada dos diferentes elementos que compõem a tabela, como os nomes das colunas, os tipos de dados que cada coluna pode armazenar e quaisquer restrições ou índices aplicados a essas colunas"
      ],
      "metadata": {
        "id": "BAXhORi7pP7X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "schema_query = \"PRAGMA table_info(Superstore)\"\n",
        "\n",
        "# Execute the query\n",
        "cursor.execute(schema_query)\n",
        "\n",
        "# Fetch all the results\n",
        "schema = cursor.fetchall()\n",
        "\n",
        "# Print the schema\n",
        "for column in schema:\n",
        "    print(column)\n"
      ],
      "metadata": {
        "id": "mpzBxQpLMLVE",
        "outputId": "6458d8f2-1c23-4ddb-97ce-7775b4ec98a2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(0, 'Row_ID', 'INTEGER', 0, None, 0)\n",
            "(1, 'Order ID', 'TEXT', 0, None, 0)\n",
            "(2, 'Order Date', 'TIMESTAMP', 0, None, 0)\n",
            "(3, 'Ship Date', 'TIMESTAMP', 0, None, 0)\n",
            "(4, 'Ship Mode', 'TEXT', 0, None, 0)\n",
            "(5, 'Customer ID', 'TEXT', 0, None, 0)\n",
            "(6, 'Customer Name', 'TEXT', 0, None, 0)\n",
            "(7, 'Segment', 'TEXT', 0, None, 0)\n",
            "(8, 'Country', 'TEXT', 0, None, 0)\n",
            "(9, 'City', 'TEXT', 0, None, 0)\n",
            "(10, 'State', 'TEXT', 0, None, 0)\n",
            "(11, 'Postal Code', 'INTEGER', 0, None, 0)\n",
            "(12, 'Region', 'TEXT', 0, None, 0)\n",
            "(13, 'Product ID', 'TEXT', 0, None, 0)\n",
            "(14, 'Category', 'TEXT', 0, None, 0)\n",
            "(15, 'Sub-Category', 'TEXT', 0, None, 0)\n",
            "(16, 'Product Name', 'TEXT', 0, None, 0)\n",
            "(17, 'Sales', 'REAL', 0, None, 0)\n",
            "(18, 'Quantity', 'INTEGER', 0, None, 0)\n",
            "(19, 'Discount', 'REAL', 0, None, 0)\n",
            "(20, 'Profit', 'REAL', 0, None, 0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para auxiliar com a execução das queries, vamos criar a função query_executer. Essa função tem a responsabilidade de executar uma consulta SQL no banco de dados e converter o resultado em um DataFrame do Pandas, facilitando a análise e manipulação dos dados."
      ],
      "metadata": {
        "id": "SrH1IltYVQsv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def query_executer(query):\n",
        "  cursor.execute(query)\n",
        "  schema = cursor.fetchall()\n",
        "  columns = [col[0] for col in cursor.description]\n",
        "  df = pd.DataFrame(schema,columns=columns)\n",
        "  return df\n",
        "\n"
      ],
      "metadata": {
        "id": "XMI9VorYOixp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Após carregar nossos dados banco, podemos solicitar as primeiras cinco linhas da nossa tabela para verificar o sucesso da importação"
      ],
      "metadata": {
        "id": "JOYheI4vqD9a"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query = '''SELECT *\n",
        "FROM superstore\n",
        "LIMIT 5;'''\n",
        "\n",
        "# Execute the query\n",
        "result = query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "id": "krMv5hKnG3hc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "outputId": "3dd8e0ff-3146-4fed-cb52-47ab47ceb361"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Row_ID        Order ID           Order Date            Ship Date  \\\n",
              "0       1  CA-2016-152156  2016-11-08 00:00:00  2016-11-11 00:00:00   \n",
              "1       2  CA-2016-152156  2016-11-08 00:00:00  2016-11-11 00:00:00   \n",
              "2       3  CA-2016-138688  2016-06-12 00:00:00  2016-06-16 00:00:00   \n",
              "3       4  US-2015-108966  2015-10-11 00:00:00  2015-10-18 00:00:00   \n",
              "4       5  US-2015-108966  2015-10-11 00:00:00  2015-10-18 00:00:00   \n",
              "\n",
              "        Ship Mode Customer ID    Customer Name    Segment        Country  \\\n",
              "0    Second Class    CG-12520      Claire Gute   Consumer  United States   \n",
              "1    Second Class    CG-12520      Claire Gute   Consumer  United States   \n",
              "2    Second Class    DV-13045  Darrin Van Huff  Corporate  United States   \n",
              "3  Standard Class    SO-20335   Sean O'Donnell   Consumer  United States   \n",
              "4  Standard Class    SO-20335   Sean O'Donnell   Consumer  United States   \n",
              "\n",
              "              City  ... Postal Code  Region       Product ID         Category  \\\n",
              "0        Henderson  ...       42420   South  FUR-BO-10001798        Furniture   \n",
              "1        Henderson  ...       42420   South  FUR-CH-10000454        Furniture   \n",
              "2      Los Angeles  ...       90036    West  OFF-LA-10000240  Office Supplies   \n",
              "3  Fort Lauderdale  ...       33311   South  FUR-TA-10000577        Furniture   \n",
              "4  Fort Lauderdale  ...       33311   South  OFF-ST-10000760  Office Supplies   \n",
              "\n",
              "  Sub-Category                                       Product Name     Sales  \\\n",
              "0    Bookcases                  Bush Somerset Collection Bookcase  261.9600   \n",
              "1       Chairs  Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400   \n",
              "2       Labels  Self-Adhesive Address Labels for Typewriters b...   14.6200   \n",
              "3       Tables      Bretford CR4500 Series Slim Rectangular Table  957.5775   \n",
              "4      Storage                     Eldon Fold 'N Roll Cart System   22.3680   \n",
              "\n",
              "   Quantity  Discount    Profit  \n",
              "0         2      0.00   41.9136  \n",
              "1         3      0.00  219.5820  \n",
              "2         2      0.00    6.8714  \n",
              "3         5      0.45 -383.0310  \n",
              "4         2      0.20    2.5164  \n",
              "\n",
              "[5 rows x 21 columns]"
            ],
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              "\n",
              "  <div id=\"df-893ceebb-d0f3-4629-bd90-b5655180cd8a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Row_ID</th>\n",
              "      <th>Order ID</th>\n",
              "      <th>Order Date</th>\n",
              "      <th>Ship Date</th>\n",
              "      <th>Ship Mode</th>\n",
              "      <th>Customer ID</th>\n",
              "      <th>Customer Name</th>\n",
              "      <th>Segment</th>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th>...</th>\n",
              "      <th>Postal Code</th>\n",
              "      <th>Region</th>\n",
              "      <th>Product ID</th>\n",
              "      <th>Category</th>\n",
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              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>CA-2016-152156</td>\n",
              "      <td>2016-11-08 00:00:00</td>\n",
              "      <td>2016-11-11 00:00:00</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>CG-12520</td>\n",
              "      <td>Claire Gute</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Henderson</td>\n",
              "      <td>...</td>\n",
              "      <td>42420</td>\n",
              "      <td>South</td>\n",
              "      <td>FUR-BO-10001798</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>Bush Somerset Collection Bookcase</td>\n",
              "      <td>261.9600</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>41.9136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>CA-2016-152156</td>\n",
              "      <td>2016-11-08 00:00:00</td>\n",
              "      <td>2016-11-11 00:00:00</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>CG-12520</td>\n",
              "      <td>Claire Gute</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Henderson</td>\n",
              "      <td>...</td>\n",
              "      <td>42420</td>\n",
              "      <td>South</td>\n",
              "      <td>FUR-CH-10000454</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>Hon Deluxe Fabric Upholstered Stacking Chairs,...</td>\n",
              "      <td>731.9400</td>\n",
              "      <td>3</td>\n",
              "      <td>0.00</td>\n",
              "      <td>219.5820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>CA-2016-138688</td>\n",
              "      <td>2016-06-12 00:00:00</td>\n",
              "      <td>2016-06-16 00:00:00</td>\n",
              "      <td>Second Class</td>\n",
              "      <td>DV-13045</td>\n",
              "      <td>Darrin Van Huff</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>United States</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>...</td>\n",
              "      <td>90036</td>\n",
              "      <td>West</td>\n",
              "      <td>OFF-LA-10000240</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Labels</td>\n",
              "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
              "      <td>14.6200</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.8714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>US-2015-108966</td>\n",
              "      <td>2015-10-11 00:00:00</td>\n",
              "      <td>2015-10-18 00:00:00</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>SO-20335</td>\n",
              "      <td>Sean O'Donnell</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Fort Lauderdale</td>\n",
              "      <td>...</td>\n",
              "      <td>33311</td>\n",
              "      <td>South</td>\n",
              "      <td>FUR-TA-10000577</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Tables</td>\n",
              "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
              "      <td>957.5775</td>\n",
              "      <td>5</td>\n",
              "      <td>0.45</td>\n",
              "      <td>-383.0310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>US-2015-108966</td>\n",
              "      <td>2015-10-11 00:00:00</td>\n",
              "      <td>2015-10-18 00:00:00</td>\n",
              "      <td>Standard Class</td>\n",
              "      <td>SO-20335</td>\n",
              "      <td>Sean O'Donnell</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Fort Lauderdale</td>\n",
              "      <td>...</td>\n",
              "      <td>33311</td>\n",
              "      <td>South</td>\n",
              "      <td>OFF-ST-10000760</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Storage</td>\n",
              "      <td>Eldon Fold 'N Roll Cart System</td>\n",
              "      <td>22.3680</td>\n",
              "      <td>2</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.5164</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 21 columns</p>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-893ceebb-d0f3-4629-bd90-b5655180cd8a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-893ceebb-d0f3-4629-bd90-b5655180cd8a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-850818f1-ba52-4b1f-8088-ae13d7797b78\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-850818f1-ba52-4b1f-8088-ae13d7797b78')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-850818f1-ba52-4b1f-8088-ae13d7797b78 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_884d21b5-29e9-47ab-b8b5-45d446bd8e95\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_884d21b5-29e9-47ab-b8b5-45d446bd8e95 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Queries\n",
        "### Podemos começar a fazer queries para estudar nossos dados e fornecer insights para a área de negócios."
      ],
      "metadata": {
        "id": "WEGOzrhlIw8J"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quanto foi o total de vendas e lucro por ano?\n",
        "\n"
      ],
      "metadata": {
        "id": "6bn62NSCN7AX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query = '''SELECT STRFTIME('%Y', \"Order Date\") AS year,\n",
        "SUM(Sales) AS total_sales,\n",
        "SUM(Profit) AS total_profit\n",
        "FROM Superstore\n",
        "GROUP BY year\n",
        "ORDER BY year ASC;'''m\n",
        "\n",
        "result = query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "vv66ahEcTEFZ",
        "outputId": "9d766356-7205-47a0-aadb-0900e230dbc7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   year  total_sales  total_profit\n",
              "0  2014  484247.4981    49543.9741\n",
              "1  2015  470532.5090    61618.6037\n",
              "2  2016  609205.5980    81795.1743\n",
              "3  2017  733215.2552    93439.2696"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6941467c-31fe-4079-b67c-4ae1d2e66f99\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>year</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2014</td>\n",
              "      <td>484247.4981</td>\n",
              "      <td>49543.9741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2015</td>\n",
              "      <td>470532.5090</td>\n",
              "      <td>61618.6037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016</td>\n",
              "      <td>609205.5980</td>\n",
              "      <td>81795.1743</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2017</td>\n",
              "      <td>733215.2552</td>\n",
              "      <td>93439.2696</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6941467c-31fe-4079-b67c-4ae1d2e66f99')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-6941467c-31fe-4079-b67c-4ae1d2e66f99 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-6941467c-31fe-4079-b67c-4ae1d2e66f99');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-14a6b491-e83a-437e-a3e8-4cc7edba4ed4\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-14a6b491-e83a-437e-a3e8-4cc7edba4ed4')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-14a6b491-e83a-437e-a3e8-4cc7edba4ed4 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_52922b1f-3e31-4d7e-bb64-39e63d873f64\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_52922b1f-3e31-4d7e-bb64-39e63d873f64 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "szI-UjXRyoXS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quanto foi o total de vendas e lucro por trimestre"
      ],
      "metadata": {
        "id": "63JlxUABr9zS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query = '''SELECT\n",
        "  STRFTIME('%Y', \"Order Date\") AS year,\n",
        "  CASE\n",
        "    WHEN STRFTIME('%m', \"Order Date\") IN ('01','02','03') THEN 'Q1'\n",
        "    WHEN STRFTIME('%m', \"Order Date\") IN ('04','05','06') THEN 'Q2'\n",
        "    WHEN STRFTIME('%m', \"Order Date\") IN ('07','08','09') THEN 'Q3'\n",
        "    ELSE 'Q4'\n",
        "  END AS quarter,\n",
        "  SUM(Sales) AS total_sales,\n",
        "  SUM(Profit) AS total_profit\n",
        "FROM Superstore\n",
        "GROUP BY year, quarter\n",
        "ORDER BY year, quarter;\n",
        "'''\n",
        "\n",
        "result = query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "MlUcQG336Bky",
        "outputId": "f4472f77-5ed2-4a6c-8f15-4273c5cc558a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    year quarter  total_sales  total_profit\n",
              "0   2014      Q1   74447.7960     3811.2290\n",
              "1   2014      Q2   86538.7596    11204.0692\n",
              "2   2014      Q3  143633.2123    12804.7218\n",
              "3   2014      Q4  179627.7302    21723.9541\n",
              "4   2015      Q1   68851.7386     9264.9416\n",
              "5   2015      Q2   89124.1870    12190.9224\n",
              "6   2015      Q3  130259.5752    16853.6194\n",
              "7   2015      Q4  182297.0082    23309.1203\n",
              "8   2016      Q1   93237.1810    11441.3708\n",
              "9   2016      Q2  136082.3010    16390.3394\n",
              "10  2016      Q3  143787.3622    15823.6048\n",
              "11  2016      Q4  236098.7538    38139.8593\n",
              "12  2017      Q1  123144.8602    23506.2026\n",
              "13  2017      Q2  133764.3720    15499.2085\n",
              "14  2017      Q3  196251.9560    26985.1325\n",
              "15  2017      Q4  280054.0670    27448.7260"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-303bdb25-5abb-49ed-b4ad-92c30b664684\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>year</th>\n",
              "      <th>quarter</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2014</td>\n",
              "      <td>Q1</td>\n",
              "      <td>74447.7960</td>\n",
              "      <td>3811.2290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2014</td>\n",
              "      <td>Q2</td>\n",
              "      <td>86538.7596</td>\n",
              "      <td>11204.0692</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2014</td>\n",
              "      <td>Q3</td>\n",
              "      <td>143633.2123</td>\n",
              "      <td>12804.7218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2014</td>\n",
              "      <td>Q4</td>\n",
              "      <td>179627.7302</td>\n",
              "      <td>21723.9541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>Q1</td>\n",
              "      <td>68851.7386</td>\n",
              "      <td>9264.9416</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2015</td>\n",
              "      <td>Q2</td>\n",
              "      <td>89124.1870</td>\n",
              "      <td>12190.9224</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2015</td>\n",
              "      <td>Q3</td>\n",
              "      <td>130259.5752</td>\n",
              "      <td>16853.6194</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2015</td>\n",
              "      <td>Q4</td>\n",
              "      <td>182297.0082</td>\n",
              "      <td>23309.1203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2016</td>\n",
              "      <td>Q1</td>\n",
              "      <td>93237.1810</td>\n",
              "      <td>11441.3708</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2016</td>\n",
              "      <td>Q2</td>\n",
              "      <td>136082.3010</td>\n",
              "      <td>16390.3394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2016</td>\n",
              "      <td>Q3</td>\n",
              "      <td>143787.3622</td>\n",
              "      <td>15823.6048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2016</td>\n",
              "      <td>Q4</td>\n",
              "      <td>236098.7538</td>\n",
              "      <td>38139.8593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2017</td>\n",
              "      <td>Q1</td>\n",
              "      <td>123144.8602</td>\n",
              "      <td>23506.2026</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2017</td>\n",
              "      <td>Q2</td>\n",
              "      <td>133764.3720</td>\n",
              "      <td>15499.2085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2017</td>\n",
              "      <td>Q3</td>\n",
              "      <td>196251.9560</td>\n",
              "      <td>26985.1325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2017</td>\n",
              "      <td>Q4</td>\n",
              "      <td>280054.0670</td>\n",
              "      <td>27448.7260</td>\n",
              "    </tr>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "720eRpITsf76"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query = '''SELECT\n",
        "  quarter,\n",
        "  SUM(total_sales) AS total_sales,\n",
        "  SUM(total_profit) AS total_profit\n",
        "FROM (\n",
        "    SELECT\n",
        "      CASE\n",
        "        WHEN STRFTIME('%m', \"Order Date\") IN ('01','02','03') THEN 'Q1'\n",
        "        WHEN STRFTIME('%m', \"Order Date\") IN ('04','05','06') THEN 'Q2'\n",
        "        WHEN STRFTIME('%m', \"Order Date\") IN ('07','08','09') THEN 'Q3'\n",
        "        ELSE 'Q4'\n",
        "      END AS quarter,\n",
        "      SUM(Sales) AS total_sales,\n",
        "      SUM(Profit) AS total_profit\n",
        "    FROM Superstore\n",
        "    GROUP BY quarter\n",
        ") AS quarters\n",
        "GROUP BY quarter\n",
        "ORDER BY quarter;\n",
        "'''\n",
        "result = query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "ycNXFp7AVkzX",
        "outputId": "fed477eb-fccd-43ac-8680-b8d60c506a99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  quarter  total_sales  total_profit\n",
              "0      Q1  359681.5758    48023.7440\n",
              "1      Q2  445509.6196    55284.5395\n",
              "2      Q3  613932.1057    72467.0785\n",
              "3      Q4  878077.5592   110621.6597"
            ],
            "text/html": [
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              "      <th>quarter</th>\n",
              "      <th>total_sales</th>\n",
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              "      <th>0</th>\n",
              "      <td>Q1</td>\n",
              "      <td>359681.5758</td>\n",
              "      <td>48023.7440</td>\n",
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              "      <th>1</th>\n",
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              "      <td>55284.5395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Q3</td>\n",
              "      <td>613932.1057</td>\n",
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              "      <th>3</th>\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-100b67b1-e3c9-4076-87cf-a0f9bf0cc718');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-4828091f-0598-48cc-96c6-c593ab255cbe\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4828091f-0598-48cc-96c6-c593ab255cbe')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4828091f-0598-48cc-96c6-c593ab255cbe button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_7e4873a8-1945-448c-bfc0-e5ce0b31b7fd\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_7e4873a8-1945-448c-bfc0-e5ce0b31b7fd button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais regiões que mais vendem e lucram?"
      ],
      "metadata": {
        "id": "qqCe1jSpsQfm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        " What region generates the highest sales and profits ?"
      ],
      "metadata": {
        "id": "Ywk98pEAeL5y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, SUM(sales) AS total_sales, SUM(profit) AS total_profits\n",
        "FROM superstore\n",
        "GROUP BY region\n",
        "ORDER BY total_profits DESC;'''\n",
        "\n",
        "result = query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "BYiydNFBW2ju",
        "outputId": "ea6259a0-07b3-43a0-ff3d-3f1e6605ee85"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Region  total_sales  total_profits\n",
              "0     West  725457.8245    108418.4489\n",
              "1     East  678781.2400     91522.7800\n",
              "2    South  391721.9050     46749.4303\n",
              "3  Central  501239.8908     39706.3625"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f390a340-05c3-4ca0-ac1c-3dfd29fcad2f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Region</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profits</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>West</td>\n",
              "      <td>725457.8245</td>\n",
              "      <td>108418.4489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>East</td>\n",
              "      <td>678781.2400</td>\n",
              "      <td>91522.7800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>South</td>\n",
              "      <td>391721.9050</td>\n",
              "      <td>46749.4303</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Central</td>\n",
              "      <td>501239.8908</td>\n",
              "      <td>39706.3625</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f390a340-05c3-4ca0-ac1c-3dfd29fcad2f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f390a340-05c3-4ca0-ac1c-3dfd29fcad2f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f390a340-05c3-4ca0-ac1c-3dfd29fcad2f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-21fa3cac-885c-46db-8fe8-fa89d1ec36cf\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-21fa3cac-885c-46db-8fe8-fa89d1ec36cf')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-21fa3cac-885c-46db-8fe8-fa89d1ec36cf button');\n",
              "      quickchartButtonEl.style.display =\n",
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          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, ROUND((SUM(profit) / SUM(sales)) * 100, 2) as profit_margin\n",
        "FROM superstore\n",
        "GROUP BY region\n",
        "ORDER BY profit_margin DESC'''\n",
        "\n",
        "\n",
        "result = query_executer(query)\n",
        "\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
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        "id": "gMxVU90teMey",
        "outputId": "fe19fcc5-caf4-4951-8d9e-3bae468961a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Region  profit_margin\n",
              "0     West          14.94\n",
              "1     East          13.48\n",
              "2    South          11.93\n",
              "3  Central           7.92"
            ],
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              "      <td>11.93</td>\n",
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              "      <td>7.92</td>\n",
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              "\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais cidades e estados que trazem as maiores vendas e lucros?"
      ],
      "metadata": {
        "id": "a4XMfnNatkEu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT State, SUM(Sales) as Total_Sales, SUM(Profit) as Total_Profits, ROUND((SUM(profit) / SUM(sales)) * 100, 2) as profit_margin\n",
        "FROM superstore\n",
        "GROUP BY State\n",
        "ORDER BY Total_Profits DESC\n",
        "LIMIT 10;'''\n",
        "\n",
        "\n",
        "result = query_executer(query)\n",
        "\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "TBdeH1djfZUb",
        "outputId": "1ea9635c-7179-43d8-e175-ff4587e78911"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        State  Total_Sales  Total_Profits  profit_margin\n",
              "0  California  457687.6315     76381.3871          16.69\n",
              "1    New York  310876.2710     74038.5486          23.82\n",
              "2  Washington  138641.2700     33402.6517          24.09\n",
              "3    Michigan   76269.6140     24463.1876          32.07\n",
              "4    Virginia   70636.7200     18597.9504          26.33\n",
              "5     Indiana   53555.3600     18382.9363          34.33\n",
              "6     Georgia   49095.8400     16250.0433          33.10\n",
              "7    Kentucky   36591.7500     11199.6966          30.61\n",
              "8   Minnesota   29863.1500     10823.1874          36.24\n",
              "9    Delaware   27451.0690      9977.3748          36.35"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Total_Sales</th>\n",
              "      <th>Total_Profits</th>\n",
              "      <th>profit_margin</th>\n",
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              "      <th>0</th>\n",
              "      <td>California</td>\n",
              "      <td>457687.6315</td>\n",
              "      <td>76381.3871</td>\n",
              "      <td>16.69</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>New York</td>\n",
              "      <td>310876.2710</td>\n",
              "      <td>74038.5486</td>\n",
              "      <td>23.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Washington</td>\n",
              "      <td>138641.2700</td>\n",
              "      <td>33402.6517</td>\n",
              "      <td>24.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Michigan</td>\n",
              "      <td>76269.6140</td>\n",
              "      <td>24463.1876</td>\n",
              "      <td>32.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Virginia</td>\n",
              "      <td>70636.7200</td>\n",
              "      <td>18597.9504</td>\n",
              "      <td>26.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Indiana</td>\n",
              "      <td>53555.3600</td>\n",
              "      <td>18382.9363</td>\n",
              "      <td>34.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Georgia</td>\n",
              "      <td>49095.8400</td>\n",
              "      <td>16250.0433</td>\n",
              "      <td>33.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Kentucky</td>\n",
              "      <td>36591.7500</td>\n",
              "      <td>11199.6966</td>\n",
              "      <td>30.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Minnesota</td>\n",
              "      <td>29863.1500</td>\n",
              "      <td>10823.1874</td>\n",
              "      <td>36.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Delaware</td>\n",
              "      <td>27451.0690</td>\n",
              "      <td>9977.3748</td>\n",
              "      <td>36.35</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram os estados com as piores margens de lucro?"
      ],
      "metadata": {
        "id": "-F6VUWmjuv3K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT State, SUM(Sales) as Total_Sales, SUM(Profit) as Total_Profits\n",
        "FROM superstore\n",
        "GROUP BY State\n",
        "ORDER BY Total_Profits ASC\n",
        "LIMIT 10;'''\n",
        "\n",
        "result = query_executer(query)\n",
        "\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "hhDyLgf0gNRG",
        "outputId": "0ae296d3-6fa1-40a9-c7e6-7df1f198fda1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            State  Total_Sales  Total_Profits\n",
              "0           Texas  170188.0458    -25729.3563\n",
              "1            Ohio   78258.1360    -16971.3766\n",
              "2    Pennsylvania  116511.9140    -15559.9603\n",
              "3        Illinois   80166.1010    -12607.8870\n",
              "4  North Carolina   55603.1640     -7490.9122\n",
              "5        Colorado   32108.1180     -6527.8579\n",
              "6       Tennessee   30661.8730     -5341.6936\n",
              "7         Arizona   35282.0010     -3427.9246\n",
              "8         Florida   89473.7080     -3399.3017\n",
              "9          Oregon   17431.1500     -1190.4705"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Total_Sales</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Texas</td>\n",
              "      <td>170188.0458</td>\n",
              "      <td>-25729.3563</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Ohio</td>\n",
              "      <td>78258.1360</td>\n",
              "      <td>-16971.3766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Pennsylvania</td>\n",
              "      <td>116511.9140</td>\n",
              "      <td>-15559.9603</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Illinois</td>\n",
              "      <td>80166.1010</td>\n",
              "      <td>-12607.8870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>North Carolina</td>\n",
              "      <td>55603.1640</td>\n",
              "      <td>-7490.9122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Colorado</td>\n",
              "      <td>32108.1180</td>\n",
              "      <td>-6527.8579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Tennessee</td>\n",
              "      <td>30661.8730</td>\n",
              "      <td>-5341.6936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Arizona</td>\n",
              "      <td>35282.0010</td>\n",
              "      <td>-3427.9246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Florida</td>\n",
              "      <td>89473.7080</td>\n",
              "      <td>-3399.3017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Oregon</td>\n",
              "      <td>17431.1500</td>\n",
              "      <td>-1190.4705</td>\n",
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              "        document.querySelector('#df-df9cd26a-19bc-464c-85ad-568eed6c9f9d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-df9cd26a-19bc-464c-85ad-568eed6c9f9d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-59bbfdf1-9eb1-4cdd-9af9-3d3d6a974bd2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-59bbfdf1-9eb1-4cdd-9af9-3d3d6a974bd2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-59bbfdf1-9eb1-4cdd-9af9-3d3d6a974bd2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_65fa5207-9345-43f6-ae6a-ee8c92d7e85c\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_65fa5207-9345-43f6-ae6a-ee8c92d7e85c button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais categorias de produto foram mais impactadas por descontos?"
      ],
      "metadata": {
        "id": "daPoILDlvNvT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT category, SUM(sales) AS total_sales, SUM(profit) AS total_profit, ROUND(SUM(profit)/SUM(sales)*100, 2) AS profit_margin\n",
        "FROM superstore\n",
        "GROUP BY category\n",
        "ORDER BY total_profit DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "cI57CcxIhqRf",
        "outputId": "3bdd010b-356c-4490-f736-b3accffaa6ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          Category  total_sales  total_profit  profit_margin\n",
              "0       Technology  836154.0330   145454.9481          17.40\n",
              "1  Office Supplies  719047.0320   122490.8008          17.04\n",
              "2        Furniture  741999.7953    18451.2728           2.49"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Category</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "      <th>profit_margin</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Technology</td>\n",
              "      <td>836154.0330</td>\n",
              "      <td>145454.9481</td>\n",
              "      <td>17.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>719047.0320</td>\n",
              "      <td>122490.8008</td>\n",
              "      <td>17.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Furniture</td>\n",
              "      <td>741999.7953</td>\n",
              "      <td>18451.2728</td>\n",
              "      <td>2.49</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a0b06d64-0454-4a61-b2ab-a1dd18a9dbcb')\"\n",
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              "    .colab-df-container {\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a0b06d64-0454-4a61-b2ab-a1dd18a9dbcb button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a0b06d64-0454-4a61-b2ab-a1dd18a9dbcb');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  </div>\n",
              "\n",
              "\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    display: none;\n",
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              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
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            ]
          },
          "metadata": {},
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as subcategorias de produtos que mais impactadas por descontos?"
      ],
      "metadata": {
        "id": "WUnyDtRv8uwx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT category, \"Sub-Category\", SUM(discount) AS total_discount\n",
        "FROM superstore\n",
        "GROUP BY category, \"Sub-Category\"\n",
        "ORDER BY total_discount DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "id": "SMWud68SqPTC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "outputId": "db007102-93c0-41ef-d0cb-cbf768a5d506"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Category Sub-Category  total_discount\n",
              "0   Office Supplies      Binders          567.00\n",
              "1        Technology       Phones          137.40\n",
              "2         Furniture  Furnishings          132.40\n",
              "3         Furniture       Chairs          105.00\n",
              "4   Office Supplies        Paper          102.60\n",
              "5         Furniture       Tables           83.35\n",
              "6   Office Supplies   Appliances           77.60\n",
              "7   Office Supplies      Storage           63.20\n",
              "8        Technology  Accessories           60.80\n",
              "9   Office Supplies          Art           59.60\n",
              "10        Furniture    Bookcases           48.14\n",
              "11       Technology     Machines           35.20\n",
              "12  Office Supplies       Labels           25.00\n",
              "13  Office Supplies    Envelopes           20.40\n",
              "14  Office Supplies    Fasteners           17.80\n",
              "15  Office Supplies     Supplies           14.60\n",
              "16       Technology      Copiers           11.00"
            ],
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              "    <tr>\n",
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              "      <td>60.80</td>\n",
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              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Office Supplies</td>\n",
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              "      <td>59.60</td>\n",
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              "    <tr>\n",
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              "      <td>48.14</td>\n",
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              "      <th>11</th>\n",
              "      <td>Technology</td>\n",
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              "      <td>35.20</td>\n",
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              "    <tr>\n",
              "      <th>12</th>\n",
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              "      <td>25.00</td>\n",
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              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Envelopes</td>\n",
              "      <td>20.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>17.80</td>\n",
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              "    <tr>\n",
              "      <th>15</th>\n",
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              "      <td>14.60</td>\n",
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              "    <tr>\n",
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              "\n",
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              "        google.colab.notebook.generateWithVariable('result');\n",
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              "    </script>\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "5D1GXqKQyHVV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais categorias de produto trouxeram as maiores vendas, lucro e margem de lucro?"
      ],
      "metadata": {
        "id": "8rER3MfwzdMt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT category, SUM(sales) AS total_sales, SUM(profit) AS total_profit, ROUND(SUM(profit)/SUM(sales)*100, 2) AS profit_margin\n",
        "FROM superstore\n",
        "GROUP BY category\n",
        "ORDER BY total_profit DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "4bq63eph09Tn",
        "outputId": "794d2313-b014-494b-c425-e7ffd937910d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          Category  total_sales  total_profit  profit_margin\n",
              "0       Technology  836154.0330   145454.9481          17.40\n",
              "1  Office Supplies  719047.0320   122490.8008          17.04\n",
              "2        Furniture  741999.7953    18451.2728           2.49"
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              "      <td>17.04</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as categorias que trouxeram mais lucro em cada estado?"
      ],
      "metadata": {
        "id": "EWlJYkly4OTR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT state, category, SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY state, category\n",
        "ORDER BY total_profit DESC\n",
        "LIMIT 20;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "gTq1iSakzUu-",
        "outputId": "15ebfb79-e018-47b6-f232-aa9d1508ffea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         State         Category  total_sales  total_profit\n",
              "0     New York       Technology  127483.5000    42186.7856\n",
              "1   California  Office Supplies  142351.9480    37748.3847\n",
              "2   California       Technology  159271.0820    29470.0368\n",
              "3     New York  Office Supplies   90020.0420    25994.0829\n",
              "4   Washington       Technology   50536.7100    15019.3435\n",
              "5     Michigan  Office Supplies   37723.7590    15005.3335\n",
              "6   Washington  Office Supplies   40084.4080    11189.5232\n",
              "7      Indiana       Technology   26323.2500    11000.8773\n",
              "8      Georgia  Office Supplies   26715.8100     9800.9256\n",
              "9   California        Furniture  156064.6015     9162.9656\n",
              "10   Minnesota  Office Supplies   19406.5400     7780.4995\n",
              "11    Virginia       Technology   24145.1600     7407.7544\n",
              "12  Washington        Furniture   48020.1520     7193.7850\n",
              "13    Delaware       Technology   14562.2200     6239.0508\n",
              "14    Virginia  Office Supplies   21169.6100     5985.8695\n",
              "15    New York        Furniture   93372.7290     5857.6801\n",
              "16    Virginia        Furniture   25321.9500     5204.3265\n",
              "17     Indiana  Office Supplies   15735.4000     5200.7837\n",
              "18    Illinois       Technology   31983.6730     4822.5592\n",
              "19    Michigan       Technology   16224.7550     4782.3025"
            ],
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              "      <th>1</th>\n",
              "      <td>California</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>142351.9480</td>\n",
              "      <td>37748.3847</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>California</td>\n",
              "      <td>Technology</td>\n",
              "      <td>159271.0820</td>\n",
              "      <td>29470.0368</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>New York</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>90020.0420</td>\n",
              "      <td>25994.0829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Washington</td>\n",
              "      <td>Technology</td>\n",
              "      <td>50536.7100</td>\n",
              "      <td>15019.3435</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Michigan</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>37723.7590</td>\n",
              "      <td>15005.3335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Washington</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>40084.4080</td>\n",
              "      <td>11189.5232</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Indiana</td>\n",
              "      <td>Technology</td>\n",
              "      <td>26323.2500</td>\n",
              "      <td>11000.8773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Georgia</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>26715.8100</td>\n",
              "      <td>9800.9256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>California</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>156064.6015</td>\n",
              "      <td>9162.9656</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Minnesota</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>19406.5400</td>\n",
              "      <td>7780.4995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Virginia</td>\n",
              "      <td>Technology</td>\n",
              "      <td>24145.1600</td>\n",
              "      <td>7407.7544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Washington</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>48020.1520</td>\n",
              "      <td>7193.7850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Delaware</td>\n",
              "      <td>Technology</td>\n",
              "      <td>14562.2200</td>\n",
              "      <td>6239.0508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Virginia</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>21169.6100</td>\n",
              "      <td>5985.8695</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>New York</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>93372.7290</td>\n",
              "      <td>5857.6801</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Virginia</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>25321.9500</td>\n",
              "      <td>5204.3265</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Indiana</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>15735.4000</td>\n",
              "      <td>5200.7837</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Illinois</td>\n",
              "      <td>Technology</td>\n",
              "      <td>31983.6730</td>\n",
              "      <td>4822.5592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Michigan</td>\n",
              "      <td>Technology</td>\n",
              "      <td>16224.7550</td>\n",
              "      <td>4782.3025</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as categorias que menos lucraram em cada estado?"
      ],
      "metadata": {
        "id": "fR4kzueJ5GbF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT state, category, SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY state, category\n",
        "ORDER BY total_profit ASC\n",
        "LIMIT 20;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "dNrXeIIr4cDJ",
        "outputId": "7abdcb75-0cb4-491b-f365-87a400cd03df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             State         Category  total_sales  total_profit\n",
              "0            Texas  Office Supplies   44490.5300   -18584.6434\n",
              "1             Ohio       Technology   35675.9920   -12649.9401\n",
              "2            Texas        Furniture   60593.2918   -10436.1419\n",
              "3         Illinois        Furniture   28274.5220    -9076.2894\n",
              "4         Illinois  Office Supplies   19907.9060    -8354.1568\n",
              "5     Pennsylvania        Furniture   39354.9310    -7196.7199\n",
              "6     Pennsylvania  Office Supplies   34941.7140    -5172.0188\n",
              "7             Ohio        Furniture   24199.1450    -4206.3212\n",
              "8   North Carolina       Technology   26083.1190    -3583.3040\n",
              "9   North Carolina        Furniture   15155.4840    -3486.4633\n",
              "10        Colorado       Technology   10966.3290    -3471.5845\n",
              "11       Tennessee  Office Supplies   12347.8580    -3199.0982\n",
              "12    Pennsylvania       Technology   42215.2690    -3191.2216\n",
              "13         Arizona        Furniture   13525.2910    -2744.9228\n",
              "14        Colorado        Furniture   13243.0370    -2683.1342\n",
              "15         Florida        Furniture   22987.0380    -2254.9807\n",
              "16       Tennessee        Furniture   13506.7320    -2208.6291\n",
              "17         Florida  Office Supplies   19518.6340    -1675.1258\n",
              "18          Oregon        Furniture    6338.1300    -1487.5769\n",
              "19         Arizona  Office Supplies   10005.8250     -795.5030"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>State</th>\n",
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              "      <th>0</th>\n",
              "      <td>Texas</td>\n",
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              "      <td>44490.5300</td>\n",
              "      <td>-18584.6434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Ohio</td>\n",
              "      <td>Technology</td>\n",
              "      <td>35675.9920</td>\n",
              "      <td>-12649.9401</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Texas</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>60593.2918</td>\n",
              "      <td>-10436.1419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Illinois</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>28274.5220</td>\n",
              "      <td>-9076.2894</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Illinois</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>19907.9060</td>\n",
              "      <td>-8354.1568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Pennsylvania</td>\n",
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              "      <td>39354.9310</td>\n",
              "      <td>-7196.7199</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Pennsylvania</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>34941.7140</td>\n",
              "      <td>-5172.0188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Ohio</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>24199.1450</td>\n",
              "      <td>-4206.3212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>North Carolina</td>\n",
              "      <td>Technology</td>\n",
              "      <td>26083.1190</td>\n",
              "      <td>-3583.3040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>North Carolina</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>15155.4840</td>\n",
              "      <td>-3486.4633</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Colorado</td>\n",
              "      <td>Technology</td>\n",
              "      <td>10966.3290</td>\n",
              "      <td>-3471.5845</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Tennessee</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>12347.8580</td>\n",
              "      <td>-3199.0982</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Pennsylvania</td>\n",
              "      <td>Technology</td>\n",
              "      <td>42215.2690</td>\n",
              "      <td>-3191.2216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Arizona</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>13525.2910</td>\n",
              "      <td>-2744.9228</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Colorado</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>13243.0370</td>\n",
              "      <td>-2683.1342</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Florida</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>22987.0380</td>\n",
              "      <td>-2254.9807</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Tennessee</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>13506.7320</td>\n",
              "      <td>-2208.6291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Florida</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>19518.6340</td>\n",
              "      <td>-1675.1258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Oregon</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>6338.1300</td>\n",
              "      <td>-1487.5769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Arizona</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>10005.8250</td>\n",
              "      <td>-795.5030</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as subcategorias de produtos que mais vendaram e lucraram em cada região e estado?"
      ],
      "metadata": {
        "id": "Rlzx32ci9efb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT \"Sub-Category\", SUM(sales) AS total_sales, SUM(profit) AS total_profit, ROUND(SUM(profit)/SUM(sales)*100, 2) AS profit_margin\n",
        "FROM superstore\n",
        "GROUP BY \"Sub-Category\"\n",
        "ORDER BY total_profit DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "id": "rnGX591A5OxT",
        "outputId": "6e1d1f40-8979-40a1-83c8-c938c64bc17b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Sub-Category  total_sales  total_profit  profit_margin\n",
              "0       Copiers  149528.0300    55617.8249          37.20\n",
              "1        Phones  330007.0540    44515.7306          13.49\n",
              "2   Accessories  167380.3180    41936.6357          25.05\n",
              "3         Paper   78479.2060    34053.5693          43.39\n",
              "4       Binders  203412.7330    30221.7633          14.86\n",
              "5        Chairs  328449.1030    26590.1663           8.10\n",
              "6       Storage  223843.6080    21278.8264           9.51\n",
              "7    Appliances  107532.1610    18138.0054          16.87\n",
              "8   Furnishings   91705.1640    13059.1436          14.24\n",
              "9     Envelopes   16476.4020     6964.1767          42.27\n",
              "10          Art   27118.7920     6527.7870          24.07\n",
              "11       Labels   12486.3120     5546.2540          44.42\n",
              "12     Machines  189238.6310     3384.7569           1.79\n",
              "13    Fasteners    3024.2800      949.5182          31.40\n",
              "14     Supplies   46673.5380    -1189.0995          -2.55\n",
              "15    Bookcases  114879.9963    -3472.5560          -3.02\n",
              "16       Tables  206965.5320   -17725.4811          -8.56"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-83bad6ec-3132-4a12-905b-1d6263506811\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sub-Category</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "      <th>profit_margin</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Copiers</td>\n",
              "      <td>149528.0300</td>\n",
              "      <td>55617.8249</td>\n",
              "      <td>37.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Phones</td>\n",
              "      <td>330007.0540</td>\n",
              "      <td>44515.7306</td>\n",
              "      <td>13.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Accessories</td>\n",
              "      <td>167380.3180</td>\n",
              "      <td>41936.6357</td>\n",
              "      <td>25.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Paper</td>\n",
              "      <td>78479.2060</td>\n",
              "      <td>34053.5693</td>\n",
              "      <td>43.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Binders</td>\n",
              "      <td>203412.7330</td>\n",
              "      <td>30221.7633</td>\n",
              "      <td>14.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Chairs</td>\n",
              "      <td>328449.1030</td>\n",
              "      <td>26590.1663</td>\n",
              "      <td>8.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Storage</td>\n",
              "      <td>223843.6080</td>\n",
              "      <td>21278.8264</td>\n",
              "      <td>9.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Appliances</td>\n",
              "      <td>107532.1610</td>\n",
              "      <td>18138.0054</td>\n",
              "      <td>16.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Furnishings</td>\n",
              "      <td>91705.1640</td>\n",
              "      <td>13059.1436</td>\n",
              "      <td>14.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Envelopes</td>\n",
              "      <td>16476.4020</td>\n",
              "      <td>6964.1767</td>\n",
              "      <td>42.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Art</td>\n",
              "      <td>27118.7920</td>\n",
              "      <td>6527.7870</td>\n",
              "      <td>24.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Labels</td>\n",
              "      <td>12486.3120</td>\n",
              "      <td>5546.2540</td>\n",
              "      <td>44.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Machines</td>\n",
              "      <td>189238.6310</td>\n",
              "      <td>3384.7569</td>\n",
              "      <td>1.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Fasteners</td>\n",
              "      <td>3024.2800</td>\n",
              "      <td>949.5182</td>\n",
              "      <td>31.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Supplies</td>\n",
              "      <td>46673.5380</td>\n",
              "      <td>-1189.0995</td>\n",
              "      <td>-2.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Bookcases</td>\n",
              "      <td>114879.9963</td>\n",
              "      <td>-3472.5560</td>\n",
              "      <td>-3.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Tables</td>\n",
              "      <td>206965.5320</td>\n",
              "      <td>-17725.4811</td>\n",
              "      <td>-8.56</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, \"Sub-Category\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY region, \"Sub-Category\"\n",
        "ORDER BY total_profit DESC\n",
        "LIMIT 30;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "id": "gMtCTrGu9vN8",
        "outputId": "c68cb975-acc8-4b13-fdf2-6d50e728c543"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Region Sub-Category  total_sales  total_profit\n",
              "0      West      Copiers    49749.242    19327.2351\n",
              "1      East      Copiers    53219.462    17022.8418\n",
              "2      West  Accessories    61114.116    16484.5983\n",
              "3      West      Binders    55961.113    16096.8016\n",
              "4   Central      Copiers    37259.570    15608.8413\n",
              "5   Central       Phones    72403.282    12323.0267\n",
              "6      East       Phones   100614.982    12314.6860\n",
              "7      West        Paper    26663.718    12119.2364\n",
              "8      East      Binders    53497.997    11267.9346\n",
              "9      East  Accessories    45033.372    11195.8644\n",
              "10    South       Phones    58304.438    10767.2753\n",
              "11     East       Chairs    96260.683     9357.7706\n",
              "12     West       Phones    98684.352     9110.7426\n",
              "13     East        Paper    20172.602     9015.3710\n",
              "14     West      Storage    70532.852     8645.3222\n",
              "15     East   Appliances    34188.466     8391.4134\n",
              "16     East      Storage    71612.584     8389.3712\n",
              "17     West   Appliances    30236.336     8261.2699\n",
              "18     West  Furnishings    30072.730     7641.2704\n",
              "19  Central  Accessories    33956.076     7251.6306\n",
              "20    South  Accessories    27276.754     7004.5424\n",
              "21  Central        Paper    17491.902     6971.9005\n",
              "22     East     Machines    66106.165     6928.6429\n",
              "23    South       Chairs    45176.446     6612.0893\n",
              "24  Central       Chairs    85230.646     6592.7221\n",
              "25    South        Paper    14150.984     5947.0614\n",
              "26     East  Furnishings    29071.380     5881.4071\n",
              "27    South   Appliances    19525.326     4123.9396\n",
              "28     West       Chairs   101781.328     4027.5843\n",
              "29    South      Binders    37030.341     3900.6640"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8ad68343-b927-401f-b99c-3bbcac823167\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Region</th>\n",
              "      <th>Sub-Category</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>West</td>\n",
              "      <td>Copiers</td>\n",
              "      <td>49749.242</td>\n",
              "      <td>19327.2351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>East</td>\n",
              "      <td>Copiers</td>\n",
              "      <td>53219.462</td>\n",
              "      <td>17022.8418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>West</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>61114.116</td>\n",
              "      <td>16484.5983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>West</td>\n",
              "      <td>Binders</td>\n",
              "      <td>55961.113</td>\n",
              "      <td>16096.8016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Central</td>\n",
              "      <td>Copiers</td>\n",
              "      <td>37259.570</td>\n",
              "      <td>15608.8413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Central</td>\n",
              "      <td>Phones</td>\n",
              "      <td>72403.282</td>\n",
              "      <td>12323.0267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>East</td>\n",
              "      <td>Phones</td>\n",
              "      <td>100614.982</td>\n",
              "      <td>12314.6860</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>West</td>\n",
              "      <td>Paper</td>\n",
              "      <td>26663.718</td>\n",
              "      <td>12119.2364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>East</td>\n",
              "      <td>Binders</td>\n",
              "      <td>53497.997</td>\n",
              "      <td>11267.9346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>East</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>45033.372</td>\n",
              "      <td>11195.8644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>South</td>\n",
              "      <td>Phones</td>\n",
              "      <td>58304.438</td>\n",
              "      <td>10767.2753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>East</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>96260.683</td>\n",
              "      <td>9357.7706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>West</td>\n",
              "      <td>Phones</td>\n",
              "      <td>98684.352</td>\n",
              "      <td>9110.7426</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>East</td>\n",
              "      <td>Paper</td>\n",
              "      <td>20172.602</td>\n",
              "      <td>9015.3710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>West</td>\n",
              "      <td>Storage</td>\n",
              "      <td>70532.852</td>\n",
              "      <td>8645.3222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>East</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>34188.466</td>\n",
              "      <td>8391.4134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>East</td>\n",
              "      <td>Storage</td>\n",
              "      <td>71612.584</td>\n",
              "      <td>8389.3712</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>West</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>30236.336</td>\n",
              "      <td>8261.2699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>West</td>\n",
              "      <td>Furnishings</td>\n",
              "      <td>30072.730</td>\n",
              "      <td>7641.2704</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Central</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>33956.076</td>\n",
              "      <td>7251.6306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>South</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>27276.754</td>\n",
              "      <td>7004.5424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Central</td>\n",
              "      <td>Paper</td>\n",
              "      <td>17491.902</td>\n",
              "      <td>6971.9005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>East</td>\n",
              "      <td>Machines</td>\n",
              "      <td>66106.165</td>\n",
              "      <td>6928.6429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>South</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>45176.446</td>\n",
              "      <td>6612.0893</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Central</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>85230.646</td>\n",
              "      <td>6592.7221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>South</td>\n",
              "      <td>Paper</td>\n",
              "      <td>14150.984</td>\n",
              "      <td>5947.0614</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>East</td>\n",
              "      <td>Furnishings</td>\n",
              "      <td>29071.380</td>\n",
              "      <td>5881.4071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>South</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>19525.326</td>\n",
              "      <td>4123.9396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>West</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>101781.328</td>\n",
              "      <td>4027.5843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>South</td>\n",
              "      <td>Binders</td>\n",
              "      <td>37030.341</td>\n",
              "      <td>3900.6640</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as subcategorias de produtos que menos lucraram em cada região e estado?"
      ],
      "metadata": {
        "id": "cW4WNDZT-GNv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, \"Sub-Category\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY region, \"Sub-Category\"\n",
        "ORDER BY total_profit ASC\n",
        "LIMIT 30;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "id": "pnx9Esan92qo",
        "outputId": "a0c49931-61f2-4289-bb28-7d2d25727ba8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Region Sub-Category  total_sales  total_profit\n",
              "0      East       Tables   39139.8070   -11025.3801\n",
              "1     South       Tables   43916.1920    -4623.0579\n",
              "2   Central  Furnishings   15254.3700    -3906.2168\n",
              "3   Central       Tables   39154.9710    -3559.6504\n",
              "4   Central   Appliances   23582.0330    -2638.6175\n",
              "5   Central    Bookcases   24157.1768    -1997.9043\n",
              "6      West    Bookcases   36004.1235    -1646.5117\n",
              "7   Central     Machines   26797.3840    -1486.0666\n",
              "8     South     Machines   53890.9600    -1438.8930\n",
              "9      East    Bookcases   43819.3340    -1167.6318\n",
              "10     East     Supplies   10760.1160    -1155.1352\n",
              "11  Central      Binders   56923.2820    -1043.6369\n",
              "12  Central     Supplies    9467.3720     -661.8881\n",
              "13     West     Machines   42444.1220     -618.9264\n",
              "14    South     Supplies    8318.9280        1.8773\n",
              "15    South    Fasteners     503.3160      173.7181\n",
              "16  Central    Fasteners     778.0300      236.6186\n",
              "17     East    Fasteners     819.7180      263.9908\n",
              "18     West    Fasteners     923.2160      275.1907\n",
              "19     West     Supplies   18127.1220      626.0465\n",
              "20    South       Labels    2353.1800     1040.7723\n",
              "21    South          Art    4655.6220     1058.5866\n",
              "22  Central       Labels    2451.4720     1073.0794\n",
              "23     East       Labels    2602.9340     1129.2800\n",
              "24  Central          Art    5765.3400     1195.1591\n",
              "25    South    Bookcases   10899.3620     1339.4918\n",
              "26    South    Envelopes    3345.5560     1465.4770\n",
              "27     West       Tables   84754.5620     1482.6073\n",
              "28  Central    Envelopes    4636.8720     1777.5283\n",
              "29     East    Envelopes    4375.8740     1812.4090"
            ],
            "text/html": [
              "\n",
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              "      <th>1</th>\n",
              "      <td>South</td>\n",
              "      <td>Tables</td>\n",
              "      <td>43916.1920</td>\n",
              "      <td>-4623.0579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Central</td>\n",
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              "      <td>15254.3700</td>\n",
              "      <td>-3906.2168</td>\n",
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              "      <th>3</th>\n",
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              "      <td>-3559.6504</td>\n",
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              "      <th>4</th>\n",
              "      <td>Central</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>23582.0330</td>\n",
              "      <td>-2638.6175</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Central</td>\n",
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              "      <td>-1997.9043</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
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              "      <td>Bookcases</td>\n",
              "      <td>36004.1235</td>\n",
              "      <td>-1646.5117</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Central</td>\n",
              "      <td>Machines</td>\n",
              "      <td>26797.3840</td>\n",
              "      <td>-1486.0666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>South</td>\n",
              "      <td>Machines</td>\n",
              "      <td>53890.9600</td>\n",
              "      <td>-1438.8930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>East</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>43819.3340</td>\n",
              "      <td>-1167.6318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>East</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>10760.1160</td>\n",
              "      <td>-1155.1352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Central</td>\n",
              "      <td>Binders</td>\n",
              "      <td>56923.2820</td>\n",
              "      <td>-1043.6369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Central</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>9467.3720</td>\n",
              "      <td>-661.8881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>West</td>\n",
              "      <td>Machines</td>\n",
              "      <td>42444.1220</td>\n",
              "      <td>-618.9264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>South</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>8318.9280</td>\n",
              "      <td>1.8773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>South</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>503.3160</td>\n",
              "      <td>173.7181</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Central</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>778.0300</td>\n",
              "      <td>236.6186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>East</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>819.7180</td>\n",
              "      <td>263.9908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>West</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>923.2160</td>\n",
              "      <td>275.1907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>West</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>18127.1220</td>\n",
              "      <td>626.0465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>South</td>\n",
              "      <td>Labels</td>\n",
              "      <td>2353.1800</td>\n",
              "      <td>1040.7723</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>South</td>\n",
              "      <td>Art</td>\n",
              "      <td>4655.6220</td>\n",
              "      <td>1058.5866</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Central</td>\n",
              "      <td>Labels</td>\n",
              "      <td>2451.4720</td>\n",
              "      <td>1073.0794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>East</td>\n",
              "      <td>Labels</td>\n",
              "      <td>2602.9340</td>\n",
              "      <td>1129.2800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Central</td>\n",
              "      <td>Art</td>\n",
              "      <td>5765.3400</td>\n",
              "      <td>1195.1591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>South</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>10899.3620</td>\n",
              "      <td>1339.4918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>South</td>\n",
              "      <td>Envelopes</td>\n",
              "      <td>3345.5560</td>\n",
              "      <td>1465.4770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>West</td>\n",
              "      <td>Tables</td>\n",
              "      <td>84754.5620</td>\n",
              "      <td>1482.6073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Central</td>\n",
              "      <td>Envelopes</td>\n",
              "      <td>4636.8720</td>\n",
              "      <td>1777.5283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>East</td>\n",
              "      <td>Envelopes</td>\n",
              "      <td>4375.8740</td>\n",
              "      <td>1812.4090</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as subcategorias com as maiores vendas/lucros em cada região e estado?"
      ],
      "metadata": {
        "id": "QKE0-5Hv_n9C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, \"Sub-Category\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY region, \"Sub-Category\"\n",
        "ORDER BY total_profit DESC\n",
        "LIMIT 20;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "Ul8lmty1_fBk",
        "outputId": "0140145f-c218-4e47-c74b-88e2b5fcb6af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Region Sub-Category  total_sales  total_profit\n",
              "0      West      Copiers    49749.242    19327.2351\n",
              "1      East      Copiers    53219.462    17022.8418\n",
              "2      West  Accessories    61114.116    16484.5983\n",
              "3      West      Binders    55961.113    16096.8016\n",
              "4   Central      Copiers    37259.570    15608.8413\n",
              "5   Central       Phones    72403.282    12323.0267\n",
              "6      East       Phones   100614.982    12314.6860\n",
              "7      West        Paper    26663.718    12119.2364\n",
              "8      East      Binders    53497.997    11267.9346\n",
              "9      East  Accessories    45033.372    11195.8644\n",
              "10    South       Phones    58304.438    10767.2753\n",
              "11     East       Chairs    96260.683     9357.7706\n",
              "12     West       Phones    98684.352     9110.7426\n",
              "13     East        Paper    20172.602     9015.3710\n",
              "14     West      Storage    70532.852     8645.3222\n",
              "15     East   Appliances    34188.466     8391.4134\n",
              "16     East      Storage    71612.584     8389.3712\n",
              "17     West   Appliances    30236.336     8261.2699\n",
              "18     West  Furnishings    30072.730     7641.2704\n",
              "19  Central  Accessories    33956.076     7251.6306"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>Region</th>\n",
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              "      <th>0</th>\n",
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              "      <td>19327.2351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>East</td>\n",
              "      <td>Copiers</td>\n",
              "      <td>53219.462</td>\n",
              "      <td>17022.8418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>West</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>61114.116</td>\n",
              "      <td>16484.5983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>West</td>\n",
              "      <td>Binders</td>\n",
              "      <td>55961.113</td>\n",
              "      <td>16096.8016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Central</td>\n",
              "      <td>Copiers</td>\n",
              "      <td>37259.570</td>\n",
              "      <td>15608.8413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Central</td>\n",
              "      <td>Phones</td>\n",
              "      <td>72403.282</td>\n",
              "      <td>12323.0267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>East</td>\n",
              "      <td>Phones</td>\n",
              "      <td>100614.982</td>\n",
              "      <td>12314.6860</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>West</td>\n",
              "      <td>Paper</td>\n",
              "      <td>26663.718</td>\n",
              "      <td>12119.2364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>East</td>\n",
              "      <td>Binders</td>\n",
              "      <td>53497.997</td>\n",
              "      <td>11267.9346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>East</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>45033.372</td>\n",
              "      <td>11195.8644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>South</td>\n",
              "      <td>Phones</td>\n",
              "      <td>58304.438</td>\n",
              "      <td>10767.2753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>East</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>96260.683</td>\n",
              "      <td>9357.7706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>West</td>\n",
              "      <td>Phones</td>\n",
              "      <td>98684.352</td>\n",
              "      <td>9110.7426</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>East</td>\n",
              "      <td>Paper</td>\n",
              "      <td>20172.602</td>\n",
              "      <td>9015.3710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>West</td>\n",
              "      <td>Storage</td>\n",
              "      <td>70532.852</td>\n",
              "      <td>8645.3222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>East</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>34188.466</td>\n",
              "      <td>8391.4134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>East</td>\n",
              "      <td>Storage</td>\n",
              "      <td>71612.584</td>\n",
              "      <td>8389.3712</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>West</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>30236.336</td>\n",
              "      <td>8261.2699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>West</td>\n",
              "      <td>Furnishings</td>\n",
              "      <td>30072.730</td>\n",
              "      <td>7641.2704</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Central</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>33956.076</td>\n",
              "      <td>7251.6306</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais foram as subcategorias com os menores vendas/lucros em cada região e estado?"
      ],
      "metadata": {
        "id": "LuRoer68AcXF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT region, \"Sub-Category\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY region, \"Sub-Category\"\n",
        "ORDER BY total_profit ASC\n",
        "LIMIT 20;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "B3y21M_fAdfl",
        "outputId": "6ee451fb-e442-4ea6-9916-dca36661cf52"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Region Sub-Category  total_sales  total_profit\n",
              "0      East       Tables   39139.8070   -11025.3801\n",
              "1     South       Tables   43916.1920    -4623.0579\n",
              "2   Central  Furnishings   15254.3700    -3906.2168\n",
              "3   Central       Tables   39154.9710    -3559.6504\n",
              "4   Central   Appliances   23582.0330    -2638.6175\n",
              "5   Central    Bookcases   24157.1768    -1997.9043\n",
              "6      West    Bookcases   36004.1235    -1646.5117\n",
              "7   Central     Machines   26797.3840    -1486.0666\n",
              "8     South     Machines   53890.9600    -1438.8930\n",
              "9      East    Bookcases   43819.3340    -1167.6318\n",
              "10     East     Supplies   10760.1160    -1155.1352\n",
              "11  Central      Binders   56923.2820    -1043.6369\n",
              "12  Central     Supplies    9467.3720     -661.8881\n",
              "13     West     Machines   42444.1220     -618.9264\n",
              "14    South     Supplies    8318.9280        1.8773\n",
              "15    South    Fasteners     503.3160      173.7181\n",
              "16  Central    Fasteners     778.0300      236.6186\n",
              "17     East    Fasteners     819.7180      263.9908\n",
              "18     West    Fasteners     923.2160      275.1907\n",
              "19     West     Supplies   18127.1220      626.0465"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>Region</th>\n",
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              "      <th>0</th>\n",
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              "      <th>1</th>\n",
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              "      <td>43916.1920</td>\n",
              "      <td>-4623.0579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Central</td>\n",
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              "      <td>-3906.2168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Central</td>\n",
              "      <td>Tables</td>\n",
              "      <td>39154.9710</td>\n",
              "      <td>-3559.6504</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Central</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>23582.0330</td>\n",
              "      <td>-2638.6175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Central</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>24157.1768</td>\n",
              "      <td>-1997.9043</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>West</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>36004.1235</td>\n",
              "      <td>-1646.5117</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Central</td>\n",
              "      <td>Machines</td>\n",
              "      <td>26797.3840</td>\n",
              "      <td>-1486.0666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>South</td>\n",
              "      <td>Machines</td>\n",
              "      <td>53890.9600</td>\n",
              "      <td>-1438.8930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>East</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>43819.3340</td>\n",
              "      <td>-1167.6318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>East</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>10760.1160</td>\n",
              "      <td>-1155.1352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Central</td>\n",
              "      <td>Binders</td>\n",
              "      <td>56923.2820</td>\n",
              "      <td>-1043.6369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Central</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>9467.3720</td>\n",
              "      <td>-661.8881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>West</td>\n",
              "      <td>Machines</td>\n",
              "      <td>42444.1220</td>\n",
              "      <td>-618.9264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>South</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>8318.9280</td>\n",
              "      <td>1.8773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>South</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>503.3160</td>\n",
              "      <td>173.7181</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Central</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>778.0300</td>\n",
              "      <td>236.6186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>East</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>819.7180</td>\n",
              "      <td>263.9908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>West</td>\n",
              "      <td>Fasteners</td>\n",
              "      <td>923.2160</td>\n",
              "      <td>275.1907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>West</td>\n",
              "      <td>Supplies</td>\n",
              "      <td>18127.1220</td>\n",
              "      <td>626.0465</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "\n",
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              "    </button>\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
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              "\n",
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              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais são os produtos mais lucrativos?"
      ],
      "metadata": {
        "id": "q50lNkCwBmxB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT \"Product Name\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY \"Product Name\"\n",
        "ORDER BY total_profit DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "QhKAmfyHBDfa",
        "outputId": "277c4553-7399-47c9-f188-bc68ef92528e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                           Product Name  total_sales  \\\n",
              "0                 Canon imageCLASS 2200 Advanced Copier    61599.824   \n",
              "1     Fellowes PB500 Electric Punch Plastic Comb Bin...    27453.384   \n",
              "2                  Hewlett Packard LaserJet 3310 Copier    18839.686   \n",
              "3                    Canon PC1060 Personal Laser Copier    11619.834   \n",
              "4     HP Designjet T520 Inkjet Large Format Printer ...    18374.895   \n",
              "...                                                 ...          ...   \n",
              "1845  Bush Advantage Collection Racetrack Conference...     9544.725   \n",
              "1846  Chromcraft Bull-Nose Wood Oval Conference Tabl...     9917.640   \n",
              "1847          Cubify CubeX 3D Printer Triple Head Print     7999.980   \n",
              "1848          Lexmark MX611dhe Monochrome Laser Printer    16829.901   \n",
              "1849          Cubify CubeX 3D Printer Double Head Print    11099.963   \n",
              "\n",
              "      total_profit  \n",
              "0       25199.9280  \n",
              "1        7753.0390  \n",
              "2        6983.8836  \n",
              "3        4570.9347  \n",
              "4        4094.9766  \n",
              "...            ...  \n",
              "1845    -1934.3976  \n",
              "1846    -2876.1156  \n",
              "1847    -3839.9904  \n",
              "1848    -4589.9730  \n",
              "1849    -8879.9704  \n",
              "\n",
              "[1850 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
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              "      <th></th>\n",
              "      <th>Product Name</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
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              "      <th>0</th>\n",
              "      <td>Canon imageCLASS 2200 Advanced Copier</td>\n",
              "      <td>61599.824</td>\n",
              "      <td>25199.9280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Fellowes PB500 Electric Punch Plastic Comb Bin...</td>\n",
              "      <td>27453.384</td>\n",
              "      <td>7753.0390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Hewlett Packard LaserJet 3310 Copier</td>\n",
              "      <td>18839.686</td>\n",
              "      <td>6983.8836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Canon PC1060 Personal Laser Copier</td>\n",
              "      <td>11619.834</td>\n",
              "      <td>4570.9347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>HP Designjet T520 Inkjet Large Format Printer ...</td>\n",
              "      <td>18374.895</td>\n",
              "      <td>4094.9766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <th>1845</th>\n",
              "      <td>Bush Advantage Collection Racetrack Conference...</td>\n",
              "      <td>9544.725</td>\n",
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              "    <tr>\n",
              "      <th>1846</th>\n",
              "      <td>Chromcraft Bull-Nose Wood Oval Conference Tabl...</td>\n",
              "      <td>9917.640</td>\n",
              "      <td>-2876.1156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1847</th>\n",
              "      <td>Cubify CubeX 3D Printer Triple Head Print</td>\n",
              "      <td>7999.980</td>\n",
              "      <td>-3839.9904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1848</th>\n",
              "      <td>Lexmark MX611dhe Monochrome Laser Printer</td>\n",
              "      <td>16829.901</td>\n",
              "      <td>-4589.9730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1849</th>\n",
              "      <td>Cubify CubeX 3D Printer Double Head Print</td>\n",
              "      <td>11099.963</td>\n",
              "      <td>-8879.9704</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1850 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2c51ee02-fa10-4835-91f8-c844cac18d8f')\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
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              "        document.querySelector('#df-2c51ee02-fa10-4835-91f8-c844cac18d8f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-2c51ee02-fa10-4835-91f8-c844cac18d8f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a12eb948-4fdf-4522-8858-512f2c36d4c4 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_e291c4b7-3443-4043-9cee-3a4804d7b7e3\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
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              "        border: none;\n",
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              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_e291c4b7-3443-4043-9cee-3a4804d7b7e3 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais são os produtos menos lucrativos?"
      ],
      "metadata": {
        "id": "iO9_yPYxB314"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT \"Product Name\", SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY \"Product Name\"\n",
        "ORDER BY total_profit ASC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "Xq1zWVENBc2s",
        "outputId": "980f0bfe-5dbf-4c67-9cf5-48233e58d274"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                           Product Name  total_sales  \\\n",
              "0             Cubify CubeX 3D Printer Double Head Print    11099.963   \n",
              "1             Lexmark MX611dhe Monochrome Laser Printer    16829.901   \n",
              "2             Cubify CubeX 3D Printer Triple Head Print     7999.980   \n",
              "3     Chromcraft Bull-Nose Wood Oval Conference Tabl...     9917.640   \n",
              "4     Bush Advantage Collection Racetrack Conference...     9544.725   \n",
              "...                                                 ...          ...   \n",
              "1845  HP Designjet T520 Inkjet Large Format Printer ...    18374.895   \n",
              "1846                 Canon PC1060 Personal Laser Copier    11619.834   \n",
              "1847               Hewlett Packard LaserJet 3310 Copier    18839.686   \n",
              "1848  Fellowes PB500 Electric Punch Plastic Comb Bin...    27453.384   \n",
              "1849              Canon imageCLASS 2200 Advanced Copier    61599.824   \n",
              "\n",
              "      total_profit  \n",
              "0       -8879.9704  \n",
              "1       -4589.9730  \n",
              "2       -3839.9904  \n",
              "3       -2876.1156  \n",
              "4       -1934.3976  \n",
              "...            ...  \n",
              "1845     4094.9766  \n",
              "1846     4570.9347  \n",
              "1847     6983.8836  \n",
              "1848     7753.0390  \n",
              "1849    25199.9280  \n",
              "\n",
              "[1850 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-966362bf-8a7b-401f-bb69-71f290c0a600\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Product Name</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Cubify CubeX 3D Printer Double Head Print</td>\n",
              "      <td>11099.963</td>\n",
              "      <td>-8879.9704</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Lexmark MX611dhe Monochrome Laser Printer</td>\n",
              "      <td>16829.901</td>\n",
              "      <td>-4589.9730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Cubify CubeX 3D Printer Triple Head Print</td>\n",
              "      <td>7999.980</td>\n",
              "      <td>-3839.9904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Chromcraft Bull-Nose Wood Oval Conference Tabl...</td>\n",
              "      <td>9917.640</td>\n",
              "      <td>-2876.1156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Bush Advantage Collection Racetrack Conference...</td>\n",
              "      <td>9544.725</td>\n",
              "      <td>-1934.3976</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>1845</th>\n",
              "      <td>HP Designjet T520 Inkjet Large Format Printer ...</td>\n",
              "      <td>18374.895</td>\n",
              "      <td>4094.9766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1846</th>\n",
              "      <td>Canon PC1060 Personal Laser Copier</td>\n",
              "      <td>11619.834</td>\n",
              "      <td>4570.9347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1847</th>\n",
              "      <td>Hewlett Packard LaserJet 3310 Copier</td>\n",
              "      <td>18839.686</td>\n",
              "      <td>6983.8836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1848</th>\n",
              "      <td>Fellowes PB500 Electric Punch Plastic Comb Bin...</td>\n",
              "      <td>27453.384</td>\n",
              "      <td>7753.0390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1849</th>\n",
              "      <td>Canon imageCLASS 2200 Advanced Copier</td>\n",
              "      <td>61599.824</td>\n",
              "      <td>25199.9280</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1850 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "\n",
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              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-966362bf-8a7b-401f-bb69-71f290c0a600 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-966362bf-8a7b-401f-bb69-71f290c0a600');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-3e04ff4c-1fc3-47ad-b12c-03441e69e641\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3e04ff4c-1fc3-47ad-b12c-03441e69e641')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-3e04ff4c-1fc3-47ad-b12c-03441e69e641 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_4b09a62c-568a-48f6-a6cb-c17a531da42d\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_4b09a62c-568a-48f6-a6cb-c17a531da42d button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais segmentos de produtos com maior lucro e vendas?"
      ],
      "metadata": {
        "id": "yoQZevxRCH9f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT segment, SUM(sales) AS total_sales, SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY segment\n",
        "ORDER BY total_profit DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "t3gAmUP7CAAL",
        "outputId": "28beea12-f0a9-473b-ac16-89e5dcf9fa53"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Segment   total_sales  total_profit\n",
              "0     Consumer  1.161401e+06   134119.2092\n",
              "1    Corporate  7.061464e+05    91979.1340\n",
              "2  Home Office  4.296531e+05    60298.6785"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b86cae6b-0fb5-4fdd-84c5-f19cb43ad8d6\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Segment</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Consumer</td>\n",
              "      <td>1.161401e+06</td>\n",
              "      <td>134119.2092</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Corporate</td>\n",
              "      <td>7.061464e+05</td>\n",
              "      <td>91979.1340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Home Office</td>\n",
              "      <td>4.296531e+05</td>\n",
              "      <td>60298.6785</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b86cae6b-0fb5-4fdd-84c5-f19cb43ad8d6')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b86cae6b-0fb5-4fdd-84c5-f19cb43ad8d6 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b86cae6b-0fb5-4fdd-84c5-f19cb43ad8d6');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-c61a3822-117e-4947-9253-684379c940f2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c61a3822-117e-4947-9253-684379c940f2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
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              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c61a3822-117e-4947-9253-684379c940f2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Qual é o número total de clientes?"
      ],
      "metadata": {
        "id": "y3dAKdsnDbP6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query='''SELECT COUNT(DISTINCT \"Customer ID\") AS total_customers\n",
        "FROM superstore;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "id": "6szFbDQuCSDN",
        "outputId": "1cdfd620-a91c-4611-b7e8-c03ee592dd67"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   total_customers\n",
              "0              793"
            ],
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            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quantos clientes existem por região?"
      ],
      "metadata": {
        "id": "sa_31l8eD7yR"
      }
    },
    {
      "cell_type": "code",
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        "query='''SELECT region, COUNT(DISTINCT \"Customer ID\") AS total_customers\n",
        "FROM superstore\n",
        "GROUP BY region\n",
        "ORDER BY total_customers DESC;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "6EWSX7y1DfVK",
        "outputId": "7ae374fa-e3a7-4617-cd53-82ea711b2745"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Region  total_customers\n",
              "0     West              686\n",
              "1     East              674\n",
              "2  Central              629\n",
              "3    South              512"
            ],
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              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-86e29e77-44d0-4c80-a225-c21ee7ba939e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_2ae6d23d-4d2a-496d-b7e6-67abb16d2dc0\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('result')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_2ae6d23d-4d2a-496d-b7e6-67abb16d2dc0 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('result');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Quais são os clientes mais leais?"
      ],
      "metadata": {
        "id": "nOPvZ3ZDEWxS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "query='''SELECT \"Customer ID\",\n",
        "SUM(sales) AS total_sales,\n",
        "SUM(profit) AS total_profit\n",
        "FROM superstore\n",
        "GROUP BY \"Customer ID\"\n",
        "ORDER BY total_sales DESC\n",
        "LIMIT 15;'''\n",
        "\n",
        "result =query_executer(query)\n",
        "result\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "kBRHbqxlEZLC",
        "outputId": "33cfa8dc-a9d6-429e-8064-6a02d6d12744"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Customer ID  total_sales  total_profit\n",
              "0     SM-20320    25043.050    -1980.7393\n",
              "1     TC-20980    19052.218     8981.3239\n",
              "2     RB-19360    15117.339     6976.0959\n",
              "3     TA-21385    14595.620     4703.7883\n",
              "4     AB-10105    14473.571     5444.8055\n",
              "5     KL-16645    14175.229      806.8550\n",
              "6     SC-20095    14142.334     5757.4119\n",
              "7     HL-15040    12873.298     5622.4292\n",
              "8     SE-20110    12209.438     2650.6769\n",
              "9     CC-12370    12129.072     2177.0493\n",
              "10    TS-21370    11891.751     2371.7144\n",
              "11    GT-14710    11820.120     2163.4269\n",
              "12    BM-11140    11789.630    -1659.9581\n",
              "13    SV-20365    11470.950     1199.4242\n",
              "14    CJ-12010    11164.974      858.7414"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a0242052-8f79-4682-88b3-72d00447fe54\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Customer ID</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>total_profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SM-20320</td>\n",
              "      <td>25043.050</td>\n",
              "      <td>-1980.7393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TC-20980</td>\n",
              "      <td>19052.218</td>\n",
              "      <td>8981.3239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>RB-19360</td>\n",
              "      <td>15117.339</td>\n",
              "      <td>6976.0959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TA-21385</td>\n",
              "      <td>14595.620</td>\n",
              "      <td>4703.7883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AB-10105</td>\n",
              "      <td>14473.571</td>\n",
              "      <td>5444.8055</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>KL-16645</td>\n",
              "      <td>14175.229</td>\n",
              "      <td>806.8550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>SC-20095</td>\n",
              "      <td>14142.334</td>\n",
              "      <td>5757.4119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>HL-15040</td>\n",
              "      <td>12873.298</td>\n",
              "      <td>5622.4292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>SE-20110</td>\n",
              "      <td>12209.438</td>\n",
              "      <td>2650.6769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>CC-12370</td>\n",
              "      <td>12129.072</td>\n",
              "      <td>2177.0493</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>TS-21370</td>\n",
              "      <td>11891.751</td>\n",
              "      <td>2371.7144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>GT-14710</td>\n",
              "      <td>11820.120</td>\n",
              "      <td>2163.4269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>BM-11140</td>\n",
              "      <td>11789.630</td>\n",
              "      <td>-1659.9581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>SV-20365</td>\n",
              "      <td>11470.950</td>\n",
              "      <td>1199.4242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>CJ-12010</td>\n",
              "      <td>11164.974</td>\n",
              "      <td>858.7414</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a0242052-8f79-4682-88b3-72d00447fe54')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a0242052-8f79-4682-88b3-72d00447fe54 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a0242052-8f79-4682-88b3-72d00447fe54');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
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              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
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              "    display: none;\n",
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              "    height: 32px;\n",
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              "  }\n",
              "\n",
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              "\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-top-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8c3b48db-a969-4877-a46b-38692d5d7c2a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
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              "        display: none;\n",
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              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "      buttonEl.style.display =\n",
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              "\n",
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              "        google.colab.notebook.generateWithVariable('result');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Qual o tempo de entrega  médio (em horas) de cada compra?"
      ],
      "metadata": {
        "id": "J0M0nwlrFGoQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "query = '''\n",
        "SELECT AVG((\"Ship Date\" - \"Order Date\") * 24) AS avg_shipping_time_hours\n",
        "FROM superstore;\n",
        "'''\n",
        "result =query_executer(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "id": "edVSjlvLEc6T",
        "outputId": "acea9b9e-e13a-4558-b8a3-224dce1420c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   avg_shipping_time_hours\n",
              "0                 0.365019"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>avg_shipping_time_hours</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
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              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "K-Nearest Neighbors is a supervised learning algorithm. Where the data is 'trained' with data points corresponding to their classification. To predict the class of a given data point, it takes into account the classes of the 'K' nearest data points and chooses the class in which the majority of the 'K' nearest data points belong to as the predicted class."
      ],
      "metadata": {
        "id": "1m1T_vAfeiLn"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "cCUNPgLr9WJs"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}