Projectile function.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def projectile(u,theta):\n",
    "    g=9.8\n",
    "    R=u**2*np.sin(2*(np.pi*theta/180))/(2*g)\n",
    "    T=2*u*np.sin(np.pi*theta/180)/g\n",
    "    H=2*u*np.sin(np.pi*theta/180)/g\n",
    "    return [R,H,T]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "A=[]\n",
    "R=[]\n",
    "H=[]\n",
    "T=[]\n",
    "for i in range (1,91):\n",
    "    a=projectile(100,i)\n",
    "    A.append(i)\n",
    "    R.append(a[0])\n",
    "    H.append(a[1])\n",
    "    T.append(a[2])\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data={}\n",
    "data.update({'Angle':A, 'Range':R, 'Time of Flight':T, 'Maximum Height': H})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Angle</th>\n",
       "      <th>Range</th>\n",
       "      <th>Time of Flight</th>\n",
       "      <th>Maximum Height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.780587e+01</td>\n",
       "      <td>0.356172</td>\n",
       "      <td>0.356172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3.559004e+01</td>\n",
       "      <td>0.712235</td>\n",
       "      <td>0.712235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>5.333085e+01</td>\n",
       "      <td>1.068081</td>\n",
       "      <td>1.068081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7.100668e+01</td>\n",
       "      <td>1.423602</td>\n",
       "      <td>1.423602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>8.859601e+01</td>\n",
       "      <td>1.778689</td>\n",
       "      <td>1.778689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>86</td>\n",
       "      <td>7.100668e+01</td>\n",
       "      <td>20.358450</td>\n",
       "      <td>20.358450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>87</td>\n",
       "      <td>5.333085e+01</td>\n",
       "      <td>20.380195</td>\n",
       "      <td>20.380195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>88</td>\n",
       "      <td>3.559004e+01</td>\n",
       "      <td>20.395731</td>\n",
       "      <td>20.395731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>89</td>\n",
       "      <td>1.780587e+01</td>\n",
       "      <td>20.405055</td>\n",
       "      <td>20.405055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>90</td>\n",
       "      <td>6.248198e-14</td>\n",
       "      <td>20.408163</td>\n",
       "      <td>20.408163</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Angle         Range  Time of Flight  Maximum Height\n",
       "0       1  1.780587e+01        0.356172        0.356172\n",
       "1       2  3.559004e+01        0.712235        0.712235\n",
       "2       3  5.333085e+01        1.068081        1.068081\n",
       "3       4  7.100668e+01        1.423602        1.423602\n",
       "4       5  8.859601e+01        1.778689        1.778689\n",
       "..    ...           ...             ...             ...\n",
       "85     86  7.100668e+01       20.358450       20.358450\n",
       "86     87  5.333085e+01       20.380195       20.380195\n",
       "87     88  3.559004e+01       20.395731       20.395731\n",
       "88     89  1.780587e+01       20.405055       20.405055\n",
       "89     90  6.248198e-14       20.408163       20.408163\n",
       "\n",
       "[90 rows x 4 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Project=pd.DataFrame(data)\n",
    "Project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "Project.to_csv('projectile.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Angle</th>\n",
       "      <th>Range</th>\n",
       "      <th>Time of Flight</th>\n",
       "      <th>Maximum Height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>17.805866</td>\n",
       "      <td>0.356172</td>\n",
       "      <td>0.356172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>35.590038</td>\n",
       "      <td>0.712235</td>\n",
       "      <td>0.712235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>53.330849</td>\n",
       "      <td>1.068081</td>\n",
       "      <td>1.068081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>71.006684</td>\n",
       "      <td>1.423602</td>\n",
       "      <td>1.423602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>88.596009</td>\n",
       "      <td>1.778689</td>\n",
       "      <td>1.778689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0  Angle      Range  Time of Flight  Maximum Height\n",
       "0           0      1  17.805866        0.356172        0.356172\n",
       "1           1      2  35.590038        0.712235        0.712235\n",
       "2           2      3  53.330849        1.068081        1.068081\n",
       "3           3      4  71.006684        1.423602        1.423602\n",
       "4           4      5  88.596009        1.778689        1.778689"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pro=pd.read_csv('projectile.csv')\n",
    "pro.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.plot(pro.Angle, pro.Range, '-', color='r', label='Range')\n",
    "plt.plot(pro.Angle, pro['Time of Flight'],'-',color='m',lw=3,label='Time of Flight')\n",
    "plt.plot(pro.Angle, pro['Maximum Height'],'-.',color='g',lw=3, label='Maximum Height')\n",
    "plt.legend(fontsize=20, loc='center')\n",
    "plt.xlabel('Angle of Projection(in Degree)', fontsize=20, color='b')\n",
    "plt.ylabel('Range, Maximum Height, Time of Flight', fontsize=20, color='b')\n",
    "plt.xticks(fontsize=20, color='r')\n",
    "plt.yticks(fontsize=20,color='r')\n",
    "plt.axvline(x=45,color='k',lw=3)\n",
    "plt.savefig('Projectile.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}