Downloading_Data.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf\n",
    "import pandas as pd\n",
    "import os\n",
    "from pystock.portfolio import Stock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_DIR = 'Data'"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading Data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pystock` modules loads the data from local directory. Furthermore, `pystock` assumes that your data is in standard format. The standard format is a csv file with the following columns:\n",
    "1. **Date**: Date of the data\n",
    "2. **Close**: Closing price of the stock (**Adj Close** also works.)\n",
    "\n",
    "This two columns are the minimum requirement for the data. However, you can add more columns to the data. For example, you can add the following columns to the data:\n",
    "1. **Open**: Opening price of the stock\n",
    "2. **High**: Highest price of the stock\n",
    "3. **Low**: Lowest price of the stock"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best way to have the data in this format is by using Yahoo Finance. For this you can use the `yfinance` module. The following code downloads the data from Yahoo Finance and saves it in the `data` directory.\n",
    "\n",
    "```python\n",
    "    import yfinance as yf\n",
    "    import pandas as pd\n",
    "    \n",
    "    # Downloading data\n",
    "    data = yf.download('AAPL', start='2010-01-01', end='2020-01-01')\n",
    "    \n",
    "    # Saving data\n",
    "    data.to_csv('data/AAPL.csv')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we'll give some examples of how to use the `yfinance` module. For details, you can refer the `yfinance` [repository](https://github.com/ranaroussi/yfinance)."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading Indices"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downloading Single Indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>1116.560059</td>\n",
       "      <td>1133.869995</td>\n",
       "      <td>1116.560059</td>\n",
       "      <td>1132.989990</td>\n",
       "      <td>1132.989990</td>\n",
       "      <td>3991400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>1132.660034</td>\n",
       "      <td>1136.630005</td>\n",
       "      <td>1129.660034</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>1135.709961</td>\n",
       "      <td>1139.189941</td>\n",
       "      <td>1133.949951</td>\n",
       "      <td>1137.140015</td>\n",
       "      <td>1137.140015</td>\n",
       "      <td>4972660000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>1136.270020</td>\n",
       "      <td>1142.459961</td>\n",
       "      <td>1131.319946</td>\n",
       "      <td>1141.689941</td>\n",
       "      <td>1141.689941</td>\n",
       "      <td>5270680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>1140.520020</td>\n",
       "      <td>1145.390015</td>\n",
       "      <td>1136.219971</td>\n",
       "      <td>1144.979980</td>\n",
       "      <td>1144.979980</td>\n",
       "      <td>4389590000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Open         High          Low        Close    Adj Close  \\\n",
       "Date                                                                          \n",
       "2010-01-04  1116.560059  1133.869995  1116.560059  1132.989990  1132.989990   \n",
       "2010-01-05  1132.660034  1136.630005  1129.660034  1136.520020  1136.520020   \n",
       "2010-01-06  1135.709961  1139.189941  1133.949951  1137.140015  1137.140015   \n",
       "2010-01-07  1136.270020  1142.459961  1131.319946  1141.689941  1141.689941   \n",
       "2010-01-08  1140.520020  1145.390015  1136.219971  1144.979980  1144.979980   \n",
       "\n",
       "                Volume  \n",
       "Date                    \n",
       "2010-01-04  3991400000  \n",
       "2010-01-05  2491020000  \n",
       "2010-01-06  4972660000  \n",
       "2010-01-07  5270680000  \n",
       "2010-01-08  4389590000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start = '2010-01-01'\n",
    "end = '2022-12-30'\n",
    "\n",
    "snp = yf.download('^GSPC', start=start, end=end)\n",
    "snp.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's save this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "snp.to_csv(os.path.join(DATA_DIR, 'snp.csv'))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, you can easily load the data using `pystock`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Stock(name=S&P)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snp = Stock(\"S&P\", os.path.join(DATA_DIR, 'snp.csv'))\n",
    "snp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>1132.989990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>1136.520020</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>1137.140015</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>1141.689941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>1144.979980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-26</th>\n",
       "      <td>3844.820068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27</th>\n",
       "      <td>3829.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28</th>\n",
       "      <td>3783.219971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29</th>\n",
       "      <td>3849.280029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30</th>\n",
       "      <td>3839.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4744 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Close\n",
       "Date                   \n",
       "2010-01-04  1132.989990\n",
       "2010-01-05  1136.520020\n",
       "2010-01-06  1137.140015\n",
       "2010-01-07  1141.689941\n",
       "2010-01-08  1144.979980\n",
       "...                 ...\n",
       "2022-12-26  3844.820068\n",
       "2022-12-27  3829.250000\n",
       "2022-12-28  3783.219971\n",
       "2022-12-29  3849.280029\n",
       "2022-12-30  3839.500000\n",
       "\n",
       "[4744 rows x 1 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snp.load_data(columns=['Adj Close'], rename_cols=['Close'], frequency='D')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downloading Multiple Indices"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This can be done by passing a list of indices to the `tickers` argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  2 of 2 completed\n"
     ]
    }
   ],
   "source": [
    "indices = [\"^DJI\", \"^FTSE\"]\n",
    "\n",
    "data = yf.download(indices, start=start, end=end, group_by='ticker')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You also need pass the argument `group_by='ticker'` to the `load_data` function. This will group the data by the ticker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th colspan=\"6\" halign=\"left\">^FTSE</th>\n",
       "      <th colspan=\"6\" halign=\"left\">^DJI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>5412.899902</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>5410.799805</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>7.509420e+08</td>\n",
       "      <td>10430.690430</td>\n",
       "      <td>10604.969727</td>\n",
       "      <td>10430.690430</td>\n",
       "      <td>10583.959961</td>\n",
       "      <td>10583.959961</td>\n",
       "      <td>179780000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>5500.299805</td>\n",
       "      <td>5536.399902</td>\n",
       "      <td>5480.700195</td>\n",
       "      <td>5522.500000</td>\n",
       "      <td>5522.500000</td>\n",
       "      <td>1.149301e+09</td>\n",
       "      <td>10584.559570</td>\n",
       "      <td>10584.559570</td>\n",
       "      <td>10522.519531</td>\n",
       "      <td>10572.019531</td>\n",
       "      <td>10572.019531</td>\n",
       "      <td>188540000.0</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>5522.500000</td>\n",
       "      <td>5536.500000</td>\n",
       "      <td>5497.700195</td>\n",
       "      <td>5530.000000</td>\n",
       "      <td>5530.000000</td>\n",
       "      <td>9.982953e+08</td>\n",
       "      <td>10564.719727</td>\n",
       "      <td>10594.990234</td>\n",
       "      <td>10546.549805</td>\n",
       "      <td>10573.679688</td>\n",
       "      <td>10573.679688</td>\n",
       "      <td>186040000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>5530.000000</td>\n",
       "      <td>5551.700195</td>\n",
       "      <td>5499.799805</td>\n",
       "      <td>5526.700195</td>\n",
       "      <td>5526.700195</td>\n",
       "      <td>1.162934e+09</td>\n",
       "      <td>10571.110352</td>\n",
       "      <td>10612.370117</td>\n",
       "      <td>10505.209961</td>\n",
       "      <td>10606.860352</td>\n",
       "      <td>10606.860352</td>\n",
       "      <td>217390000.0</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>5526.700195</td>\n",
       "      <td>5549.299805</td>\n",
       "      <td>5494.799805</td>\n",
       "      <td>5534.200195</td>\n",
       "      <td>5534.200195</td>\n",
       "      <td>1.006421e+09</td>\n",
       "      <td>10606.400391</td>\n",
       "      <td>10619.400391</td>\n",
       "      <td>10554.330078</td>\n",
       "      <td>10618.190430</td>\n",
       "      <td>10618.190430</td>\n",
       "      <td>172710000.0</td>\n",
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      "text/plain": [
       "                  ^FTSE                                                      \\\n",
       "                   Open         High          Low        Close    Adj Close   \n",
       "Date                                                                          \n",
       "2010-01-04  5412.899902  5500.299805  5410.799805  5500.299805  5500.299805   \n",
       "2010-01-05  5500.299805  5536.399902  5480.700195  5522.500000  5522.500000   \n",
       "2010-01-06  5522.500000  5536.500000  5497.700195  5530.000000  5530.000000   \n",
       "2010-01-07  5530.000000  5551.700195  5499.799805  5526.700195  5526.700195   \n",
       "2010-01-08  5526.700195  5549.299805  5494.799805  5534.200195  5534.200195   \n",
       "\n",
       "                                  ^DJI                              \\\n",
       "                  Volume          Open          High           Low   \n",
       "Date                                                                 \n",
       "2010-01-04  7.509420e+08  10430.690430  10604.969727  10430.690430   \n",
       "2010-01-05  1.149301e+09  10584.559570  10584.559570  10522.519531   \n",
       "2010-01-06  9.982953e+08  10564.719727  10594.990234  10546.549805   \n",
       "2010-01-07  1.162934e+09  10571.110352  10612.370117  10505.209961   \n",
       "2010-01-08  1.006421e+09  10606.400391  10619.400391  10554.330078   \n",
       "\n",
       "                                                     \n",
       "                   Close     Adj Close       Volume  \n",
       "Date                                                 \n",
       "2010-01-04  10583.959961  10583.959961  179780000.0  \n",
       "2010-01-05  10572.019531  10572.019531  188540000.0  \n",
       "2010-01-06  10573.679688  10573.679688  186040000.0  \n",
       "2010-01-07  10606.860352  10606.860352  217390000.0  \n",
       "2010-01-08  10618.190430  10618.190430  172710000.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, you can separate the data by the ticker:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>10430.690430</td>\n",
       "      <td>10604.969727</td>\n",
       "      <td>10430.690430</td>\n",
       "      <td>10583.959961</td>\n",
       "      <td>10583.959961</td>\n",
       "      <td>179780000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>10584.559570</td>\n",
       "      <td>10584.559570</td>\n",
       "      <td>10522.519531</td>\n",
       "      <td>10572.019531</td>\n",
       "      <td>10572.019531</td>\n",
       "      <td>188540000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>10564.719727</td>\n",
       "      <td>10594.990234</td>\n",
       "      <td>10546.549805</td>\n",
       "      <td>10573.679688</td>\n",
       "      <td>10573.679688</td>\n",
       "      <td>186040000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>10571.110352</td>\n",
       "      <td>10612.370117</td>\n",
       "      <td>10505.209961</td>\n",
       "      <td>10606.860352</td>\n",
       "      <td>10606.860352</td>\n",
       "      <td>217390000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>10606.400391</td>\n",
       "      <td>10619.400391</td>\n",
       "      <td>10554.330078</td>\n",
       "      <td>10618.190430</td>\n",
       "      <td>10618.190430</td>\n",
       "      <td>172710000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Open          High           Low         Close  \\\n",
       "Date                                                                 \n",
       "2010-01-04  10430.690430  10604.969727  10430.690430  10583.959961   \n",
       "2010-01-05  10584.559570  10584.559570  10522.519531  10572.019531   \n",
       "2010-01-06  10564.719727  10594.990234  10546.549805  10573.679688   \n",
       "2010-01-07  10571.110352  10612.370117  10505.209961  10606.860352   \n",
       "2010-01-08  10606.400391  10619.400391  10554.330078  10618.190430   \n",
       "\n",
       "               Adj Close       Volume  \n",
       "Date                                   \n",
       "2010-01-04  10583.959961  179780000.0  \n",
       "2010-01-05  10572.019531  188540000.0  \n",
       "2010-01-06  10573.679688  186040000.0  \n",
       "2010-01-07  10606.860352  217390000.0  \n",
       "2010-01-08  10618.190430  172710000.0  "
      ]
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>5412.899902</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>5410.799805</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>5500.299805</td>\n",
       "      <td>7.509420e+08</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>5500.299805</td>\n",
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       "      <td>1.149301e+09</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>5522.500000</td>\n",
       "      <td>5536.500000</td>\n",
       "      <td>5497.700195</td>\n",
       "      <td>5530.000000</td>\n",
       "      <td>5530.000000</td>\n",
       "      <td>9.982953e+08</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>5530.000000</td>\n",
       "      <td>5551.700195</td>\n",
       "      <td>5499.799805</td>\n",
       "      <td>5526.700195</td>\n",
       "      <td>5526.700195</td>\n",
       "      <td>1.162934e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>5526.700195</td>\n",
       "      <td>5549.299805</td>\n",
       "      <td>5494.799805</td>\n",
       "      <td>5534.200195</td>\n",
       "      <td>5534.200195</td>\n",
       "      <td>1.006421e+09</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                   Open         High          Low        Close    Adj Close  \\\n",
       "Date                                                                          \n",
       "2010-01-04  5412.899902  5500.299805  5410.799805  5500.299805  5500.299805   \n",
       "2010-01-05  5500.299805  5536.399902  5480.700195  5522.500000  5522.500000   \n",
       "2010-01-06  5522.500000  5536.500000  5497.700195  5530.000000  5530.000000   \n",
       "2010-01-07  5530.000000  5551.700195  5499.799805  5526.700195  5526.700195   \n",
       "2010-01-08  5526.700195  5549.299805  5494.799805  5534.200195  5534.200195   \n",
       "\n",
       "                  Volume  \n",
       "Date                      \n",
       "2010-01-04  7.509420e+08  \n",
       "2010-01-05  1.149301e+09  \n",
       "2010-01-06  9.982953e+08  \n",
       "2010-01-07  1.162934e+09  \n",
       "2010-01-08  1.006421e+09  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dji = data[\"^DJI\"]\n",
    "ftse = data[\"^FTSE\"]\n",
    "display(dji.head())\n",
    "display(ftse.head())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading Stocks and Other Securities"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same procedure can be used for downloading stocks and other securities. For example, let's download the data for the some securities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  4 of 4 completed\n"
     ]
    }
   ],
   "source": [
    "tickers = ['AAPL', 'MSFT', 'AMZN', 'GOOG']\n",
    "data = yf.download(tickers, start='2010-01-01', end='2020-01-01', group_by='ticker')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>6.8125</td>\n",
       "      <td>6.8305</td>\n",
       "      <td>6.6570</td>\n",
       "      <td>6.6950</td>\n",
       "      <td>6.6950</td>\n",
       "      <td>151998000</td>\n",
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       "      <th>2010-01-05</th>\n",
       "      <td>6.6715</td>\n",
       "      <td>6.7740</td>\n",
       "      <td>6.5905</td>\n",
       "      <td>6.7345</td>\n",
       "      <td>6.7345</td>\n",
       "      <td>177038000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>6.7300</td>\n",
       "      <td>6.7365</td>\n",
       "      <td>6.5825</td>\n",
       "      <td>6.6125</td>\n",
       "      <td>6.6125</td>\n",
       "      <td>143576000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>6.6005</td>\n",
       "      <td>6.6160</td>\n",
       "      <td>6.4400</td>\n",
       "      <td>6.5000</td>\n",
       "      <td>6.5000</td>\n",
       "      <td>220604000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>6.5280</td>\n",
       "      <td>6.6840</td>\n",
       "      <td>6.4515</td>\n",
       "      <td>6.6760</td>\n",
       "      <td>6.6760</td>\n",
       "      <td>196610000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close  Adj Close     Volume\n",
       "Date                                                            \n",
       "2010-01-04  6.8125  6.8305  6.6570  6.6950     6.6950  151998000\n",
       "2010-01-05  6.6715  6.7740  6.5905  6.7345     6.7345  177038000\n",
       "2010-01-06  6.7300  6.7365  6.5825  6.6125     6.6125  143576000\n",
       "2010-01-07  6.6005  6.6160  6.4400  6.5000     6.5000  220604000\n",
       "2010-01-08  6.5280  6.6840  6.4515  6.6760     6.6760  196610000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "amazon = data[\"AMZN\"]\n",
    "display(amazon.head())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> For the time being, `pystock` requires you to pass the stock data as a file directory. In the future, we'll add the functionality to pass the data as a `pandas` dataframe."
   ]
  }
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