ratio_ex_to_im.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from plotnine import ggplot, aes, geom_density, geom_line, geom_point, ggtitle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ratio of non-oil exports to imports "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratio_ex_im= pd.read_csv('Cleaned_Data/Trading20_4_clean.csv')\n",
    "ratio_ex_im.drop('Unnamed: 0' axis=1, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratio_ex_im.drop('Imports (million SAR))', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Exports (million SAR)</th>\n",
       "      <th>Imports (million SAR)</th>\n",
       "      <th>Ratio of Non-oil Exports to Imports %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011.0</td>\n",
       "      <td>176567.731649</td>\n",
       "      <td>493449.082585</td>\n",
       "      <td>35.782361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012.0</td>\n",
       "      <td>190951.553513</td>\n",
       "      <td>583473.067875</td>\n",
       "      <td>32.726713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013.0</td>\n",
       "      <td>202443.212959</td>\n",
       "      <td>630582.433092</td>\n",
       "      <td>32.104163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>217029.903583</td>\n",
       "      <td>651875.760674</td>\n",
       "      <td>33.293139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>189901.077563</td>\n",
       "      <td>655033.363532</td>\n",
       "      <td>28.991054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016.0</td>\n",
       "      <td>177693.532214</td>\n",
       "      <td>525635.962804</td>\n",
       "      <td>33.805437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017.0</td>\n",
       "      <td>193479.004472</td>\n",
       "      <td>504446.616737</td>\n",
       "      <td>38.354704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>235458.083665</td>\n",
       "      <td>513992.690199</td>\n",
       "      <td>45.809617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019.0</td>\n",
       "      <td>229184.234637</td>\n",
       "      <td>574361.454604</td>\n",
       "      <td>39.902440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020.0</td>\n",
       "      <td>204352.737425</td>\n",
       "      <td>517490.594270</td>\n",
       "      <td>39.489169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021.0</td>\n",
       "      <td>274900.300000</td>\n",
       "      <td>578141.000000</td>\n",
       "      <td>47.549010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Exports (million SAR)  Imports (million SAR)  \\\n",
       "0   2011.0          176567.731649          493449.082585   \n",
       "1   2012.0          190951.553513          583473.067875   \n",
       "2   2013.0          202443.212959          630582.433092   \n",
       "3   2014.0          217029.903583          651875.760674   \n",
       "4   2015.0          189901.077563          655033.363532   \n",
       "5   2016.0          177693.532214          525635.962804   \n",
       "6   2017.0          193479.004472          504446.616737   \n",
       "7   2018.0          235458.083665          513992.690199   \n",
       "8   2019.0          229184.234637          574361.454604   \n",
       "9   2020.0          204352.737425          517490.594270   \n",
       "10  2021.0          274900.300000          578141.000000   \n",
       "\n",
       "    Ratio of Non-oil Exports to Imports %  \n",
       "0                               35.782361  \n",
       "1                               32.726713  \n",
       "2                               32.104163  \n",
       "3                               33.293139  \n",
       "4                               28.991054  \n",
       "5                               33.805437  \n",
       "6                               38.354704  \n",
       "7                               45.809617  \n",
       "8                               39.902440  \n",
       "9                               39.489169  \n",
       "10                              47.549010  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio_ex_im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6228482.026372001"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio_ex_im['Imports (million SAR)'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratio_ex_im.loc[10,'Imports (million SAR)'] = 578141\n",
    "ratio_ex_im.loc[10,'Year'] = 2021\n",
    "ratio_ex_im.loc[10,'Exports (million SAR)'] = 274900.300\n",
    "ratio_ex_im.loc[10,'Ratio of Non-oil Exports to Imports %'] = 47.54901"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratio_ex_im['Year'] = ratio_ex_im['Year'].astype(int)\n",
    "ratio_ex_im['Exports (million SAR)'] = ratio_ex_im['Exports (million SAR)'].astype(float)\n",
    "ratio_ex_im['Imports (million SAR))'] = ratio_ex_im['Imports (million SAR)'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-darkgrid')\n",
    "plt.figure(figsize=[7,4])\n",
    "plt.scatter(ratio_ex_im['Year'], ratio_ex_im['Imports (million SAR)'])\n",
    "plt.plot(ratio_ex_im['Year'], ratio_ex_im['Imports (million SAR)'], c = 'red')\n",
    "plt.title('Imports from 2011 - 2021', fontsize= 15)\n",
    "plt.xlabel('Year', fontsize=13)\n",
    "plt.ylabel('Value in million SAR', fontsize=13)\n",
    "plt.xticks(np.arange(2011, 2022, 1), fontsize= 13, rotation=45)\n",
    "plt.savefig('Plots/Imports from 2011-2021')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratio_ex_im.to_csv('Cleaned_Data/Trading20_4_clean.csv')"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
  },
  "kernelspec": {
   "display_name": "Python 3.8.0 64-bit",
   "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": "3.8.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}