{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "initial_id",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Merge gdp and recession on date using merge_asof()\n",
    "gdp_recession = pd.merge_asof(gdp, recession, on='date')\n",
    "\n",
    "# Create a list based on the row value of gdp_recession['econ_status']\n",
    "is_recession = ['r' if s=='recession' else 'g' for s in gdp_recession['econ_status']]\n",
    "\n",
    "# Plot a bar chart of gdp_recession\n",
    "gdp_recession.plot(kind='bar', y='gdp', x='date', color=is_recession, rot=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "351ecea5054d8f6e"
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'ind_pop_data.csv'",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mFileNotFoundError\u001B[0m                         Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[1], line 39\u001B[0m\n\u001B[0;32m     36\u001B[0m fn \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mind_pop_data.csv\u001B[39m\u001B[38;5;124m'\u001B[39m\n\u001B[0;32m     38\u001B[0m \u001B[38;5;66;03m# Call plot_pop for country code 'CEB'\u001B[39;00m\n\u001B[1;32m---> 39\u001B[0m \u001B[43mplot_pop\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mind_pop_data.csv\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mCEB\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[0;32m     41\u001B[0m \u001B[38;5;66;03m# Call plot_pop for country code 'ARB'\u001B[39;00m\n\u001B[0;32m     42\u001B[0m plot_pop(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mind_pop_data.csv\u001B[39m\u001B[38;5;124m'\u001B[39m,\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mARB\u001B[39m\u001B[38;5;124m'\u001B[39m)\n",
      "Cell \u001B[1;32mIn[1], line 8\u001B[0m, in \u001B[0;36mplot_pop\u001B[1;34m(filename, country_code)\u001B[0m\n\u001B[0;32m      5\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mplot_pop\u001B[39m(filename, country_code):\n\u001B[0;32m      6\u001B[0m \n\u001B[0;32m      7\u001B[0m     \u001B[38;5;66;03m# Initialize reader object: urb_pop_reader\u001B[39;00m\n\u001B[1;32m----> 8\u001B[0m     urb_pop_reader \u001B[38;5;241m=\u001B[39m \u001B[43mpd\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mread_csv\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilename\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mchunksize\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;241;43m1000\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[0;32m     10\u001B[0m     \u001B[38;5;66;03m# Initialize empty DataFrame: data\u001B[39;00m\n\u001B[0;32m     11\u001B[0m     data \u001B[38;5;241m=\u001B[39m pd\u001B[38;5;241m.\u001B[39mDataFrame()\n",
      "File \u001B[1;32mC:\\Program Files\\Python312\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:948\u001B[0m, in \u001B[0;36mread_csv\u001B[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001B[0m\n\u001B[0;32m    935\u001B[0m kwds_defaults \u001B[38;5;241m=\u001B[39m _refine_defaults_read(\n\u001B[0;32m    936\u001B[0m     dialect,\n\u001B[0;32m    937\u001B[0m     delimiter,\n\u001B[1;32m   (...)\u001B[0m\n\u001B[0;32m    944\u001B[0m     dtype_backend\u001B[38;5;241m=\u001B[39mdtype_backend,\n\u001B[0;32m    945\u001B[0m )\n\u001B[0;32m    946\u001B[0m kwds\u001B[38;5;241m.\u001B[39mupdate(kwds_defaults)\n\u001B[1;32m--> 948\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43m_read\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilepath_or_buffer\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mkwds\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[1;32mC:\\Program Files\\Python312\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:611\u001B[0m, in \u001B[0;36m_read\u001B[1;34m(filepath_or_buffer, kwds)\u001B[0m\n\u001B[0;32m    608\u001B[0m _validate_names(kwds\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mnames\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28;01mNone\u001B[39;00m))\n\u001B[0;32m    610\u001B[0m \u001B[38;5;66;03m# Create the parser.\u001B[39;00m\n\u001B[1;32m--> 611\u001B[0m parser \u001B[38;5;241m=\u001B[39m \u001B[43mTextFileReader\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilepath_or_buffer\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwds\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m    613\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m chunksize \u001B[38;5;129;01mor\u001B[39;00m iterator:\n\u001B[0;32m    614\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m parser\n",
      "File \u001B[1;32mC:\\Program Files\\Python312\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1448\u001B[0m, in \u001B[0;36mTextFileReader.__init__\u001B[1;34m(self, f, engine, **kwds)\u001B[0m\n\u001B[0;32m   1445\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moptions[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhas_index_names\u001B[39m\u001B[38;5;124m\"\u001B[39m] \u001B[38;5;241m=\u001B[39m kwds[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhas_index_names\u001B[39m\u001B[38;5;124m\"\u001B[39m]\n\u001B[0;32m   1447\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles: IOHandles \u001B[38;5;241m|\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m-> 1448\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_engine \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_make_engine\u001B[49m\u001B[43m(\u001B[49m\u001B[43mf\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mengine\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[1;32mC:\\Program Files\\Python312\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1705\u001B[0m, in \u001B[0;36mTextFileReader._make_engine\u001B[1;34m(self, f, engine)\u001B[0m\n\u001B[0;32m   1703\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mb\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;129;01min\u001B[39;00m mode:\n\u001B[0;32m   1704\u001B[0m         mode \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mb\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m-> 1705\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles \u001B[38;5;241m=\u001B[39m \u001B[43mget_handle\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m   1706\u001B[0m \u001B[43m    \u001B[49m\u001B[43mf\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1707\u001B[0m \u001B[43m    \u001B[49m\u001B[43mmode\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1708\u001B[0m \u001B[43m    \u001B[49m\u001B[43mencoding\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mencoding\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mNone\u001B[39;49;00m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1709\u001B[0m \u001B[43m    \u001B[49m\u001B[43mcompression\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mcompression\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mNone\u001B[39;49;00m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1710\u001B[0m \u001B[43m    \u001B[49m\u001B[43mmemory_map\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mmemory_map\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1711\u001B[0m \u001B[43m    \u001B[49m\u001B[43mis_text\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mis_text\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1712\u001B[0m \u001B[43m    \u001B[49m\u001B[43merrors\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mencoding_errors\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mstrict\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1713\u001B[0m \u001B[43m    \u001B[49m\u001B[43mstorage_options\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mstorage_options\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mNone\u001B[39;49;00m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m   1714\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m   1715\u001B[0m \u001B[38;5;28;01massert\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[0;32m   1716\u001B[0m f \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles\u001B[38;5;241m.\u001B[39mhandle\n",
      "File \u001B[1;32mC:\\Program Files\\Python312\\Lib\\site-packages\\pandas\\io\\common.py:863\u001B[0m, in \u001B[0;36mget_handle\u001B[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001B[0m\n\u001B[0;32m    858\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(handle, \u001B[38;5;28mstr\u001B[39m):\n\u001B[0;32m    859\u001B[0m     \u001B[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001B[39;00m\n\u001B[0;32m    860\u001B[0m     \u001B[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001B[39;00m\n\u001B[0;32m    861\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m ioargs\u001B[38;5;241m.\u001B[39mencoding \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mb\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;129;01min\u001B[39;00m ioargs\u001B[38;5;241m.\u001B[39mmode:\n\u001B[0;32m    862\u001B[0m         \u001B[38;5;66;03m# Encoding\u001B[39;00m\n\u001B[1;32m--> 863\u001B[0m         handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mopen\u001B[39;49m\u001B[43m(\u001B[49m\n\u001B[0;32m    864\u001B[0m \u001B[43m            \u001B[49m\u001B[43mhandle\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m    865\u001B[0m \u001B[43m            \u001B[49m\u001B[43mioargs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmode\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m    866\u001B[0m \u001B[43m            \u001B[49m\u001B[43mencoding\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mioargs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mencoding\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m    867\u001B[0m \u001B[43m            \u001B[49m\u001B[43merrors\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43merrors\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m    868\u001B[0m \u001B[43m            \u001B[49m\u001B[43mnewline\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[0;32m    869\u001B[0m \u001B[43m        \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m    870\u001B[0m     \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m    871\u001B[0m         \u001B[38;5;66;03m# Binary mode\u001B[39;00m\n\u001B[0;32m    872\u001B[0m         handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mopen\u001B[39m(handle, ioargs\u001B[38;5;241m.\u001B[39mmode)\n",
      "\u001B[1;31mFileNotFoundError\u001B[0m: [Errno 2] No such file or directory: 'ind_pop_data.csv'"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define plot_pop()\n",
    "def plot_pop(filename, country_code):\n",
    "\n",
    "    # Initialize reader object: urb_pop_reader\n",
    "    urb_pop_reader = pd.read_csv(filename, chunksize=1000)\n",
    "\n",
    "    # Initialize empty DataFrame: data\n",
    "    data = pd.DataFrame()\n",
    "    \n",
    "    # Iterate over each DataFrame chunk\n",
    "    for df_urb_pop in urb_pop_reader:\n",
    "        # Check out specific country: df_pop_ceb\n",
    "        df_pop_ceb = df_urb_pop[df_urb_pop['CountryCode'] == country_code]\n",
    "\n",
    "        # Zip DataFrame columns of interest: pops\n",
    "        pops = zip(df_pop_ceb['Total Population'],\n",
    "                    df_pop_ceb['Urban population (% of total)'])\n",
    "\n",
    "        # Turn zip object into list: pops_list\n",
    "        pops_list = list(pops)\n",
    "\n",
    "        # Use list comprehension to create new DataFrame column 'Total Urban Population'\n",
    "        df_pop_ceb['Total Urban Population'] = [int(tup[0] * tup[1] * 0.01) for tup in pops_list]\n",
    "        \n",
    "        # Concatenate DataFrame chunk to the end of data: data\n",
    "        data = pd.concat([data, df_pop_ceb])\n",
    "\n",
    "    # Plot urban population data\n",
    "    data.plot(kind='scatter', x='Year', y='Total Urban Population')\n",
    "    plt.show()\n",
    "\n",
    "# Set the filename: fn\n",
    "fn = 'ind_pop_data.csv'\n",
    "\n",
    "# Call plot_pop for country code 'CEB'\n",
    "plot_pop('ind_pop_data.csv','CEB')\n",
    "\n",
    "# Call plot_pop for country code 'ARB'\n",
    "plot_pop('ind_pop_data.csv','ARB')"
   ],
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