Historical trends based on likes and comments.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this jupyter notebook, I will be briefly looking through some historical trends based on the number of numbers and the \n",
    "number of comments of posts from NUSWhispers's website (https://www.nuswhispers.com). If you are not interested in the code, this will be at most be a  **5 minute read**.\n",
    "\n",
    "The data was scraped using a Python command line application that I build, the Github repository of the code for the application can be found at https://github.com/yaofeng-wang/NUSWhispers_scraper. The data can be found at https://github.com/yaofeng-wang/NUSWhispers_scraper/tree/master/output. If you have any suggestion/criticism, please contact me at yaofeng96@gmail.com . \n",
    "\n",
    "In the following cells, I will refer to each post in NUSWhispers as a 'Whisper'. If you are not interested in the code,\n",
    "feel free to skip the 'Data pre-processing' section that will follow immediately and proceed to the 'Overview of data' \n",
    "section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import calendar\n",
    "from datetime import date, datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "\n",
    "# Label each bar plot with the value on top of each bar\n",
    "# https://matplotlib.org/3.1.1/gallery/lines_bars_and_markers/barchart.html#sphx-glr-gallery-lines-bars-and-markers-barchart-py\n",
    "def autolabel(rects, dtype):\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        if dtype == 'int':\n",
    "            ax.annotate(f'{height}', xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3), \n",
    "                        textcoords=\"offset points\",\n",
    "                        ha='center', va='bottom')\n",
    "        else:\n",
    "            ax.annotate(f'{height:.2f}', xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3), \n",
    "                        textcoords=\"offset points\",\n",
    "                        ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df53000to53999 = pd.read_excel(\"./posts53000to53999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df54000to54999 = pd.read_excel(\"./posts54000to54999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df55000to55999 = pd.read_excel(\"./posts55000to55999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df56000to56999 = pd.read_excel(\"./posts56000to56999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df57000to57999 = pd.read_excel(\"./posts57000to57999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df58000to58999 = pd.read_excel(\"./posts58000to58999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df59000to59999 = pd.read_excel(\"./posts59000to59999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df60000to60999 = pd.read_excel(\"./posts60000to60999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df61000to61999 = pd.read_excel(\"./posts61000to61999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df62000to62999 = pd.read_excel(\"./posts62000to62999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df63000to63999 = pd.read_excel(\"./posts63000to63999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df64000to64999 = pd.read_excel(\"./posts64000to64999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df65000to65999 = pd.read_excel(\"./posts65000to65999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df66000to66999 = pd.read_excel(\"./posts66000to66999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "df67000to67999 = pd.read_excel(\"./posts67000to67999.xlsx\",\n",
    "    names=['index','categories','text','num_likes','num_comments','post_age','num_favourites'])\n",
    "\n",
    "df = pd.concat([df53000to53999, df54000to54999, df55000to55999, df56000to56999, df57000to57999, df58000to58999, \n",
    "                df59000to59999, df60000to60999, df61000to61999, df62000to62999, df63000to63999, df64000to64999, \n",
    "                df65000to65999, df66000to66999, df67000to67999], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert post_age to month-year string\n",
    "# e.g. '2 months ago' becomes 'Jun-19'\n",
    "#      '9 months ago' becomes 'Nov-18'\n",
    "#      'a month ago' becomes  'Jul-19'\n",
    "#      '2 hours ago' becomes  'Aug-19'\n",
    "def get_post_age(x):\n",
    "    first_word, second_word = x.split(\" \")[0], x.split(\" \")[1]\n",
    "    current_date = date(year=2019,month=8,day=1)\n",
    "    post_posted_on = None\n",
    "    if second_word == 'months':\n",
    "        post_posted_on = current_date -  relativedelta(months=int(first_word))\n",
    "    elif second_word == 'month':\n",
    "        post_posted_on = current_date -  relativedelta(months=1)\n",
    "    else:\n",
    "        post_posted_on = current_date\n",
    "    return post_posted_on.strftime(\"%b-%y\")\n",
    "        \n",
    "# https://stackoverflow.com/questions/48042915/sort-a-pandass-dataframe-series-by-month-name/48043319\n",
    "months = [\"Oct-18\", \"Nov-18\", \"Dec-18\", \"Jan-19\", \"Feb-19\", \"Mar-19\", \"Apr-19\", \"May-19\", \"Jun-19\", \"Jul-19\", \"Aug-19\"]\n",
    "df['month'] = pd.Categorical(df['post_age'].apply(get_post_age), categories=months, ordered=True)\n",
    "\n",
    "# There were some Whispers without num_likes 57766, 57778, 57784, 57787, 57792, 57877, 57879\n",
    "# Unable to find posts on Facebook\n",
    "df['num_likes'] = df['num_likes'].apply(lambda x: 0 if x == 'None' else int(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overview of data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us first dip our feet into the pool by taking a look at the general overview of our data. We will start by plotting the \n",
    "number of Whispers posted in each month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plots = plt.bar(months, df['month'].value_counts().sort_index())\n",
    "plt.title('Number of Whispers posted in each month')\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel('Number of Whispers')\n",
    "plt.ylim(0, 1100)\n",
    "ax = plt.gca()\n",
    "autolabel(plots, 'int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this bar plot above, it seems that the number of  Whispers dipped significantly during June and July, which might be  due to the summer vacation. There also seems to be a spike during April."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us take a quick look at the number of likes, then the number of comments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5198.000000\n",
       "mean       12.121393\n",
       "std        46.291757\n",
       "min         0.000000\n",
       "25%         1.000000\n",
       "50%         3.000000\n",
       "75%         9.000000\n",
       "max      1159.000000\n",
       "Name: num_likes, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()['num_likes']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the summary above, we see that the distribution for the number of likes has a very large spread, with values from\n",
    "0(min) to 1159(max). Even though the max is 1159, the mean is only 12.6 and the mean is only 3. \n",
    "\n",
    "Since the bar plot for num_likes is not very pleasing to the eyes, I shall ommit it. For those who are curious, the code\n",
    "can be found in the cell below.\n",
    "\n",
    "For those interesting, the Whispers with the top 3 highest number of likes can be found here:\n",
    "\n",
    "1. 1159 likes: https://www.nuswhispers.com/tag/60498\n",
    "2. 1071 likes: https://www.nuswhispers.com/tag/63802\n",
    "3. 1013 likes: https://www.nuswhispers.com/tag/62143"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "df2 = df['num_likes'].value_counts().sort_index().reset_index()\n",
    "highest_num_likes = max(df['num_likes'])\n",
    "for i in range(highest_num_likes):\n",
    "    if i not in df2['index'].values:\n",
    "        df2.append(pd.DataFrame([[i, 0]]))\n",
    "        \n",
    "plt.figure(figsize=(8,5))\n",
    "plt.xlabel(\"Number of likes\")\n",
    "plt.ylabel('Number of posts with the corresponding number of likes')\n",
    "plt.bar(df2['index'], df2['num_likes'])\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's move on to the number of comments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5191.000000\n",
       "mean        7.001734\n",
       "std         7.565933\n",
       "min         0.000000\n",
       "25%         1.000000\n",
       "50%         4.000000\n",
       "75%        10.000000\n",
       "max        25.000000\n",
       "Name: num_comments, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()['num_comments']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As compared to the number of likes, the distribution for the number of comments is much more closely packed, \n",
    "with values from 0(min) to 25(max). \n",
    "\n",
    "Taking a closer look at the plot for num_comments shown below, we see that num_comments seems to have a upper limit of 25. \n",
    "However, it seems that I wasn't the only person to have noticed this issue (https://www.nuswhispers.com/tag/67447). Since this hard limit only occurs on the NUSWhispers website, if you were to visit their Facebook page, you would still be able \n",
    "to see the real number of comments. Therefore, We will have to take note that if the number of comments for a Whisper\n",
    "is 25, this number could actually be an underestimate for the real number of comments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.title(\"Distribution for the number of comments\")\n",
    "plt.xlabel(\"Number of comments\")\n",
    "plt.ylabel('Number of Whispers')\n",
    "plt.ylim(0, 800)\n",
    "plots = plt.bar(np.arange(26), df['num_comments'].value_counts().sort_index())\n",
    "ax = plt.gca()\n",
    "autolabel(plots, 'int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend 1: Increase in the proportion of Whispers with a high number of likes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first look at the total number of likes in each month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "width = 0.35\n",
    "plots = plt.bar(months, df.groupby(['month']).agg({'num_likes':'sum'}).sort_index()['num_likes'], width)\n",
    "plt.title(\"Total number of likes, separated by month\")\n",
    "plt.ylabel('Number of likes')\n",
    "plt.xlabel('Month')\n",
    "plt.ylim(0, 14000)\n",
    "ax = plt.gca()\n",
    "autolabel(plots, 'int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plot above seems to be hinting at a general increase in the number of likes over time. \n",
    "\n",
    "However, let's have a closer look. We can bucketize the number of likes into a few discrete buckets and look at the number of Whispers in each bucket, in each month as shown below. We see that the length of the red rectangle, which represents the number of Whispers with more than 20 likes has gradually increased. \n",
    "\n",
    "FYI, the three groups \"0 to 9\", \"10 to 20\", and \"more than 20 likes\" were chosen arbitrarily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1d872f05160>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Divide num_likes into a smaller number of categories\n",
    "def num_likes_bins(x):\n",
    "    if int(x) <= 9:\n",
    "        return 0\n",
    "    elif int(x) <= 20:\n",
    "        return 1\n",
    "    else:\n",
    "        return 2\n",
    "df['num_likes_group'] = df['num_likes'].apply(num_likes_bins)\n",
    "\n",
    "df2 = df.groupby(['month', 'num_likes_group'], as_index=False).size().reset_index()\n",
    "width = 0.35\n",
    "\n",
    "num_likes_group_0 = df2.loc[df2['num_likes_group'] == 0, 0].values\n",
    "num_likes_group_1 = df2.loc[df2['num_likes_group'] == 1, 0].values\n",
    "num_likes_group_2 = df2.loc[df2['num_likes_group'] == 2, 0].values\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "p1 = plt.bar(months, num_likes_group_0, width, color='green')\n",
    "p2 = plt.bar(months, num_likes_group_1, width, bottom = num_likes_group_0, color='orange')\n",
    "p3 = plt.bar(months, num_likes_group_2, width, bottom = num_likes_group_0 + num_likes_group_1, color='red')\n",
    "\n",
    "\n",
    "plt.title(\"Number of Whispers, separated by likes categories and month\")\n",
    "plt.ylabel('Number of Whispers')\n",
    "plt.xlabel('Month')\n",
    "plt.legend((p1[0], p2[0], p3[0]), ('0 to 9 (inclusive) likes', '10 to 20 (inclusive) likes', 'more than 20 likes'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just to drive the point home, we can look at the mean number of likes, in each month, as shown below. We see that the\n",
    "later months do seem to have a higher mean number of likes than the earlier months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = df.groupby(['month']).agg({'num_likes':'sum'})\n",
    "df2 = df['month'].value_counts()\n",
    "df3 = pd.concat([df1, df2], axis=1)\n",
    "df3['num_likes_per_post'] = df3['num_likes'] / df3['month']\n",
    "plt.figure(figsize=(10, 5))\n",
    "p1 = plt.bar(months, df3['num_likes_per_post'].sort_index())\n",
    "plt.title('Mean number of likes vs. Month')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Mean number of likes')\n",
    "plt.ylim(0, 23)\n",
    "ax = plt.gca()\n",
    "autolabel(p1, 'float')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend 2: Increase in the proportion of Whispers with a high number of comments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we have done previously, we can first take a look at the number of comments separated by month. \n",
    "\n",
    "Note that since there is a hard upper limit of 25 comments for each Whisper on the NUSWhispers's website, the values below are underestimates of \n",
    "the real number of comments posted in each month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "width = 0.35\n",
    "plots = plt.bar(months, df.groupby(['month']).agg({'num_comments':'sum'}).sort_index()['num_comments'], width)\n",
    "plt.title(\"Number of comments, separated by month\")\n",
    "plt.ylabel('Number of comments')\n",
    "plt.xlabel('Month')\n",
    "plt.ylim(0, 8000)\n",
    "ax = plt.gca()\n",
    "autolabel(plots, 'int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we can also bucketise the number of comments into a fewer number of discrete bins (3 in this case) and \n",
    "look at the number of comments in each bin, in each month, as shown below. Similary to the situation in the number of likes, the length of the red bar show below seems to be increasing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1d87193ad30>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Divide num_likes into a smaller number of categories\n",
    "def num_comments_bins(x):\n",
    "    if x <= 12:\n",
    "        return 0\n",
    "    elif x <= 24:\n",
    "        return 1\n",
    "    else: # 25 or more\n",
    "        return 2\n",
    "df['num_comments_group'] = df['num_comments'].apply(num_comments_bins)\n",
    "\n",
    "df2 = df.groupby(['month', 'num_comments_group'], as_index=False).size().reset_index()\n",
    "\n",
    "width = 0.35\n",
    "\n",
    "num_comments_group_0 = df2.loc[df2['num_comments_group'] == 0, 0].values\n",
    "num_comments_group_1 = df2.loc[df2['num_comments_group'] == 1, 0].values\n",
    "num_comments_group_2 = df2.loc[df2['num_comments_group'] == 2, 0].values\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "p1 = plt.bar(months, num_comments_group_0, width, color='green')\n",
    "p2 = plt.bar(months, num_comments_group_1, width, bottom = num_comments_group_0, color='orange')\n",
    "p3 = plt.bar(months, num_comments_group_2, width, bottom = num_comments_group_0 + num_comments_group_1, color='red')\n",
    "\n",
    "plt.title(\"Number of Whispers, separated by comments categories and month\")\n",
    "plt.ylabel('Number of Whispers')\n",
    "plt.xlabel('Month')\n",
    "plt.legend((p1[0], p2[0], p3[0]), ('0 to 12 (inclusive) comments', '13 to 24 (inclusive) comments', '25 comments or more'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lastly, we can look at the mean number of comments, in each month, as shown below. We see that the\n",
    "later months do seem to have a higher mean number of likes than the earlier months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = df.groupby(['month']).agg({'num_comments':'sum'})\n",
    "df2 = df['month'].value_counts()\n",
    "df3 = pd.concat([df1, df2], axis=1)\n",
    "df3['num_comments_per_post'] = df3['num_comments'] / df3['month']\n",
    "plt.figure(figsize=(10, 5))\n",
    "p1 = plt.bar(months, df3['num_comments_per_post'].sort_index())\n",
    "plt.title('Mean number of comments vs. Month')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Mean number of comments')\n",
    "plt.ylim(0, 14)\n",
    "ax = plt.gca()\n",
    "autolabel(p1, 'float')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thank you for looking through this jupyter notebook! Once again If you have any suggestion/criticism, please contact me at yaofeng96@gmail.com. Have a good day :) (Last update: 12-Aug-2019)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}