combine_stocks.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Dividends</th>\n",
       "      <th>Stock Splits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1980-12-12 00:00:00-05:00</td>\n",
       "      <td>0.099722</td>\n",
       "      <td>0.100155</td>\n",
       "      <td>0.099722</td>\n",
       "      <td>0.099722</td>\n",
       "      <td>469033600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1980-12-15 00:00:00-05:00</td>\n",
       "      <td>0.094953</td>\n",
       "      <td>0.094953</td>\n",
       "      <td>0.094519</td>\n",
       "      <td>0.094519</td>\n",
       "      <td>175884800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1980-12-16 00:00:00-05:00</td>\n",
       "      <td>0.088015</td>\n",
       "      <td>0.088015</td>\n",
       "      <td>0.087581</td>\n",
       "      <td>0.087581</td>\n",
       "      <td>105728000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1980-12-17 00:00:00-05:00</td>\n",
       "      <td>0.089749</td>\n",
       "      <td>0.090183</td>\n",
       "      <td>0.089749</td>\n",
       "      <td>0.089749</td>\n",
       "      <td>86441600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1980-12-18 00:00:00-05:00</td>\n",
       "      <td>0.092351</td>\n",
       "      <td>0.092785</td>\n",
       "      <td>0.092351</td>\n",
       "      <td>0.092351</td>\n",
       "      <td>73449600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\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>2813</th>\n",
       "      <td>YELP</td>\n",
       "      <td>2023-05-08 00:00:00-04:00</td>\n",
       "      <td>28.07</td>\n",
       "      <td>28.889999</td>\n",
       "      <td>27.559999</td>\n",
       "      <td>28.030001</td>\n",
       "      <td>691500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2814</th>\n",
       "      <td>YELP</td>\n",
       "      <td>2023-05-09 00:00:00-04:00</td>\n",
       "      <td>27.76</td>\n",
       "      <td>27.959999</td>\n",
       "      <td>27.610001</td>\n",
       "      <td>27.75</td>\n",
       "      <td>579100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2815</th>\n",
       "      <td>YELP</td>\n",
       "      <td>2023-05-10 00:00:00-04:00</td>\n",
       "      <td>28.18</td>\n",
       "      <td>29.299999</td>\n",
       "      <td>27.91</td>\n",
       "      <td>28.48</td>\n",
       "      <td>725500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2816</th>\n",
       "      <td>YELP</td>\n",
       "      <td>2023-05-11 00:00:00-04:00</td>\n",
       "      <td>28.459999</td>\n",
       "      <td>30.040001</td>\n",
       "      <td>28.24</td>\n",
       "      <td>29.799999</td>\n",
       "      <td>1251800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>YELP</td>\n",
       "      <td>2023-05-12 00:00:00-04:00</td>\n",
       "      <td>29.82</td>\n",
       "      <td>29.84</td>\n",
       "      <td>29.4</td>\n",
       "      <td>29.440001</td>\n",
       "      <td>551369</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>105135 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ticker                       Date       Open       High        Low  \\\n",
       "0      AAPL  1980-12-12 00:00:00-05:00   0.099722   0.100155   0.099722   \n",
       "1      AAPL  1980-12-15 00:00:00-05:00   0.094953   0.094953   0.094519   \n",
       "2      AAPL  1980-12-16 00:00:00-05:00   0.088015   0.088015   0.087581   \n",
       "3      AAPL  1980-12-17 00:00:00-05:00   0.089749   0.090183   0.089749   \n",
       "4      AAPL  1980-12-18 00:00:00-05:00   0.092351   0.092785   0.092351   \n",
       "...     ...                        ...        ...        ...        ...   \n",
       "2813   YELP  2023-05-08 00:00:00-04:00      28.07  28.889999  27.559999   \n",
       "2814   YELP  2023-05-09 00:00:00-04:00      27.76  27.959999  27.610001   \n",
       "2815   YELP  2023-05-10 00:00:00-04:00      28.18  29.299999      27.91   \n",
       "2816   YELP  2023-05-11 00:00:00-04:00  28.459999  30.040001      28.24   \n",
       "2817   YELP  2023-05-12 00:00:00-04:00      29.82      29.84       29.4   \n",
       "\n",
       "          Close     Volume Dividends Stock Splits  \n",
       "0      0.099722  469033600       0.0          0.0  \n",
       "1      0.094519  175884800       0.0          0.0  \n",
       "2      0.087581  105728000       0.0          0.0  \n",
       "3      0.089749   86441600       0.0          0.0  \n",
       "4      0.092351   73449600       0.0          0.0  \n",
       "...         ...        ...       ...          ...  \n",
       "2813  28.030001     691500       0.0          0.0  \n",
       "2814      27.75     579100       0.0          0.0  \n",
       "2815      28.48     725500       0.0          0.0  \n",
       "2816  29.799999    1251800       0.0          0.0  \n",
       "2817  29.440001     551369       0.0          0.0  \n",
       "\n",
       "[105135 rows x 9 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns = 'Ticker','Date','Open','High','Low','Close','Volume','Dividends','Stock Splits'\n",
    "stocks = pd.DataFrame(columns=columns)\n",
    "TICKERS = [\n",
    "    'AAPL', 'MSFT', 'GOOG', 'AMZN', 'NVDA', 'META',\n",
    "    'TSLA', 'BABA', 'CRM', 'AMD', 'INTC', 'PYPL',\n",
    "    'ATVI', 'EA', 'TTD', 'ZG', 'MTCH', 'YELP',\n",
    "]\n",
    "for ticker in TICKERS:\n",
    "    stock_path = os.path.join(\"./\", \"results2/\", ticker + '.csv')\n",
    "    stock = pd.read_csv(stock_path)\n",
    "    stock[\"Ticker\"] = ticker\n",
    "    stocks = pd.concat([stocks, stock], sort=False)\n",
    "    \n",
    "stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.to_csv(\"./stocks.csv\", index=False)"
   ]
  }
 ],
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