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@@ -1,1221 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Getting Financial Data - Pandas Datareader"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Introduction:\n",
-    "\n",
-    "This time you will get data from a website.\n",
-    "\n",
-    "\n",
-    "### Step 1. Import the necessary libraries"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "# package to extract data from various Internet sources into a DataFrame\n",
-    "# make sure you have it installed\n",
-    "import pandas_datareader.data as web\n",
-    "\n",
-    "# package for dates\n",
-    "import datetime as dt"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 2. Create your time range (start and end variables). The start date should be 01/01/2015 and the end should today (whatever your today is)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "datetime.datetime(2015, 1, 1, 0, 0)"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "start = dt.datetime(2015, 1, 1)\n",
-    "end = dt.datetime.today()\n",
-    "\n",
-    "start"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 3. Get an API key for one of the APIs that are supported by Pandas Datareader, preferably for AlphaVantage.\n",
-    "\n",
-    "If you do not have an API key for any of the supported APIs, it is easiest to get one for [AlphaVantage](https://www.alphavantage.co/support/#api-key). (Note that the API key is shown directly after the signup. You do *not* receive it via e-mail.)\n",
-    "\n",
-    "(For a full list of the APIs that are supported by Pandas Datareader, [see here](https://pydata.github.io/pandas-datareader/readers/index.html). As the APIs are provided by third parties, this list may change.)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 4. Use Pandas Datarader to read the daily time series for the Apple stock (ticker symbol AAPL) between 01/01/2015 and today, assign it to df_apple and print it."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "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>open</th>\n",
-       "      <th>high</th>\n",
-       "      <th>low</th>\n",
-       "      <th>close</th>\n",
-       "      <th>volume</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2015-01-02</th>\n",
-       "      <td>111.3900</td>\n",
-       "      <td>111.4400</td>\n",
-       "      <td>107.350</td>\n",
-       "      <td>109.33</td>\n",
-       "      <td>53204626</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-05</th>\n",
-       "      <td>108.2900</td>\n",
-       "      <td>108.6500</td>\n",
-       "      <td>105.410</td>\n",
-       "      <td>106.25</td>\n",
-       "      <td>64285491</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-06</th>\n",
-       "      <td>106.5400</td>\n",
-       "      <td>107.4300</td>\n",
-       "      <td>104.630</td>\n",
-       "      <td>106.26</td>\n",
-       "      <td>65797116</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-07</th>\n",
-       "      <td>107.2000</td>\n",
-       "      <td>108.2000</td>\n",
-       "      <td>106.695</td>\n",
-       "      <td>107.75</td>\n",
-       "      <td>40105934</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-08</th>\n",
-       "      <td>109.2300</td>\n",
-       "      <td>112.1500</td>\n",
-       "      <td>108.700</td>\n",
-       "      <td>111.89</td>\n",
-       "      <td>59364547</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-24</th>\n",
-       "      <td>514.7900</td>\n",
-       "      <td>515.1400</td>\n",
-       "      <td>495.745</td>\n",
-       "      <td>503.43</td>\n",
-       "      <td>86484442</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-25</th>\n",
-       "      <td>498.7900</td>\n",
-       "      <td>500.7172</td>\n",
-       "      <td>492.210</td>\n",
-       "      <td>499.30</td>\n",
-       "      <td>52873947</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-26</th>\n",
-       "      <td>504.7165</td>\n",
-       "      <td>507.9700</td>\n",
-       "      <td>500.330</td>\n",
-       "      <td>506.09</td>\n",
-       "      <td>40755567</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-27</th>\n",
-       "      <td>508.5700</td>\n",
-       "      <td>509.9400</td>\n",
-       "      <td>495.330</td>\n",
-       "      <td>500.04</td>\n",
-       "      <td>38888096</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-28</th>\n",
-       "      <td>504.0500</td>\n",
-       "      <td>505.7700</td>\n",
-       "      <td>498.310</td>\n",
-       "      <td>499.23</td>\n",
-       "      <td>46907479</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1425 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                open      high      low   close    volume\n",
-       "2015-01-02  111.3900  111.4400  107.350  109.33  53204626\n",
-       "2015-01-05  108.2900  108.6500  105.410  106.25  64285491\n",
-       "2015-01-06  106.5400  107.4300  104.630  106.26  65797116\n",
-       "2015-01-07  107.2000  108.2000  106.695  107.75  40105934\n",
-       "2015-01-08  109.2300  112.1500  108.700  111.89  59364547\n",
-       "...              ...       ...      ...     ...       ...\n",
-       "2020-08-24  514.7900  515.1400  495.745  503.43  86484442\n",
-       "2020-08-25  498.7900  500.7172  492.210  499.30  52873947\n",
-       "2020-08-26  504.7165  507.9700  500.330  506.09  40755567\n",
-       "2020-08-27  508.5700  509.9400  495.330  500.04  38888096\n",
-       "2020-08-28  504.0500  505.7700  498.310  499.23  46907479\n",
-       "\n",
-       "[1425 rows x 5 columns]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_apple = web.DataReader(name=\"AAPL\",\n",
-    "                          data_source=\"av-daily\",\n",
-    "                          start=start,\n",
-    "                          end=end,\n",
-    "                          api_key=\"your_alpha_vantage_api_key_goes_here\")\n",
-    "\n",
-    "df_apple"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 5. Add a new column \"stock\" to the dataframe and add the ticker symbol"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "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>open</th>\n",
-       "      <th>high</th>\n",
-       "      <th>low</th>\n",
-       "      <th>close</th>\n",
-       "      <th>volume</th>\n",
-       "      <th>stock</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2015-01-02</th>\n",
-       "      <td>111.3900</td>\n",
-       "      <td>111.4400</td>\n",
-       "      <td>107.350</td>\n",
-       "      <td>109.33</td>\n",
-       "      <td>53204626</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-05</th>\n",
-       "      <td>108.2900</td>\n",
-       "      <td>108.6500</td>\n",
-       "      <td>105.410</td>\n",
-       "      <td>106.25</td>\n",
-       "      <td>64285491</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-06</th>\n",
-       "      <td>106.5400</td>\n",
-       "      <td>107.4300</td>\n",
-       "      <td>104.630</td>\n",
-       "      <td>106.26</td>\n",
-       "      <td>65797116</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-07</th>\n",
-       "      <td>107.2000</td>\n",
-       "      <td>108.2000</td>\n",
-       "      <td>106.695</td>\n",
-       "      <td>107.75</td>\n",
-       "      <td>40105934</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-08</th>\n",
-       "      <td>109.2300</td>\n",
-       "      <td>112.1500</td>\n",
-       "      <td>108.700</td>\n",
-       "      <td>111.89</td>\n",
-       "      <td>59364547</td>\n",
-       "      <td>AAPL</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",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-24</th>\n",
-       "      <td>514.7900</td>\n",
-       "      <td>515.1400</td>\n",
-       "      <td>495.745</td>\n",
-       "      <td>503.43</td>\n",
-       "      <td>86484442</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-25</th>\n",
-       "      <td>498.7900</td>\n",
-       "      <td>500.7172</td>\n",
-       "      <td>492.210</td>\n",
-       "      <td>499.30</td>\n",
-       "      <td>52873947</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-26</th>\n",
-       "      <td>504.7165</td>\n",
-       "      <td>507.9700</td>\n",
-       "      <td>500.330</td>\n",
-       "      <td>506.09</td>\n",
-       "      <td>40755567</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-27</th>\n",
-       "      <td>508.5700</td>\n",
-       "      <td>509.9400</td>\n",
-       "      <td>495.330</td>\n",
-       "      <td>500.04</td>\n",
-       "      <td>38888096</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-28</th>\n",
-       "      <td>504.0500</td>\n",
-       "      <td>505.7700</td>\n",
-       "      <td>498.310</td>\n",
-       "      <td>499.23</td>\n",
-       "      <td>46907479</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1425 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                open      high      low   close    volume stock\n",
-       "2015-01-02  111.3900  111.4400  107.350  109.33  53204626  AAPL\n",
-       "2015-01-05  108.2900  108.6500  105.410  106.25  64285491  AAPL\n",
-       "2015-01-06  106.5400  107.4300  104.630  106.26  65797116  AAPL\n",
-       "2015-01-07  107.2000  108.2000  106.695  107.75  40105934  AAPL\n",
-       "2015-01-08  109.2300  112.1500  108.700  111.89  59364547  AAPL\n",
-       "...              ...       ...      ...     ...       ...   ...\n",
-       "2020-08-24  514.7900  515.1400  495.745  503.43  86484442  AAPL\n",
-       "2020-08-25  498.7900  500.7172  492.210  499.30  52873947  AAPL\n",
-       "2020-08-26  504.7165  507.9700  500.330  506.09  40755567  AAPL\n",
-       "2020-08-27  508.5700  509.9400  495.330  500.04  38888096  AAPL\n",
-       "2020-08-28  504.0500  505.7700  498.310  499.23  46907479  AAPL\n",
-       "\n",
-       "[1425 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_apple[\"stock\"] = \"AAPL\"\n",
-    "df_apple"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 6. Repeat the two previous steps for a few other stocks, always creating a new dataframe: Tesla, IBM and Microsoft. (Ticker symbols TSLA, IBM and MSFT.)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Tesla\n",
-    "df_tesla = web.DataReader(name=\"TSLA\",\n",
-    "                          data_source=\"av-daily\",\n",
-    "                          start=start,\n",
-    "                          end=end,\n",
-    "                          api_key=\"your_alpha_vantage_api_key_goes_here\")\n",
-    "\n",
-    "df_tesla[\"stock\"] = \"TSLA\"\n",
-    "\n",
-    "# IBM\n",
-    "df_ibm = web.DataReader(name=\"IBM\",\n",
-    "                        data_source=\"av-daily\",\n",
-    "                        start=start,\n",
-    "                        end=end,\n",
-    "                        api_key=\"your_alpha_vantage_api_key_goes_here\")\n",
-    "\n",
-    "df_ibm[\"stock\"] = \"IBM\"\n",
-    "\n",
-    "# Microsoft\n",
-    "df_microsoft = web.DataReader(name=\"MSFT\",\n",
-    "                              data_source=\"av-daily\",\n",
-    "                              start=start,\n",
-    "                              end=end,\n",
-    "                              api_key=\"your_alpha_vantage_api_key_goes_here\")\n",
-    "\n",
-    "df_microsoft[\"stock\"] = \"MSFT\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 7. Combine the four separate dataFrames into one combined dataFrame df that holds the information for all four stocks"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "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>open</th>\n",
-       "      <th>high</th>\n",
-       "      <th>low</th>\n",
-       "      <th>close</th>\n",
-       "      <th>volume</th>\n",
-       "      <th>stock</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2015-01-02</th>\n",
-       "      <td>111.39</td>\n",
-       "      <td>111.440</td>\n",
-       "      <td>107.350</td>\n",
-       "      <td>109.33</td>\n",
-       "      <td>53204626</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-05</th>\n",
-       "      <td>108.29</td>\n",
-       "      <td>108.650</td>\n",
-       "      <td>105.410</td>\n",
-       "      <td>106.25</td>\n",
-       "      <td>64285491</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-06</th>\n",
-       "      <td>106.54</td>\n",
-       "      <td>107.430</td>\n",
-       "      <td>104.630</td>\n",
-       "      <td>106.26</td>\n",
-       "      <td>65797116</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-07</th>\n",
-       "      <td>107.20</td>\n",
-       "      <td>108.200</td>\n",
-       "      <td>106.695</td>\n",
-       "      <td>107.75</td>\n",
-       "      <td>40105934</td>\n",
-       "      <td>AAPL</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-08</th>\n",
-       "      <td>109.23</td>\n",
-       "      <td>112.150</td>\n",
-       "      <td>108.700</td>\n",
-       "      <td>111.89</td>\n",
-       "      <td>59364547</td>\n",
-       "      <td>AAPL</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",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-24</th>\n",
-       "      <td>214.79</td>\n",
-       "      <td>215.520</td>\n",
-       "      <td>212.430</td>\n",
-       "      <td>213.69</td>\n",
-       "      <td>25460147</td>\n",
-       "      <td>MSFT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-25</th>\n",
-       "      <td>213.10</td>\n",
-       "      <td>216.610</td>\n",
-       "      <td>213.100</td>\n",
-       "      <td>216.47</td>\n",
-       "      <td>23043696</td>\n",
-       "      <td>MSFT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-26</th>\n",
-       "      <td>217.88</td>\n",
-       "      <td>222.090</td>\n",
-       "      <td>217.360</td>\n",
-       "      <td>221.15</td>\n",
-       "      <td>39600828</td>\n",
-       "      <td>MSFT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-27</th>\n",
-       "      <td>222.89</td>\n",
-       "      <td>231.150</td>\n",
-       "      <td>219.400</td>\n",
-       "      <td>226.58</td>\n",
-       "      <td>57602195</td>\n",
-       "      <td>MSFT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-28</th>\n",
-       "      <td>228.18</td>\n",
-       "      <td>230.644</td>\n",
-       "      <td>226.580</td>\n",
-       "      <td>228.91</td>\n",
-       "      <td>26292896</td>\n",
-       "      <td>MSFT</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5700 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "              open     high      low   close    volume stock\n",
-       "2015-01-02  111.39  111.440  107.350  109.33  53204626  AAPL\n",
-       "2015-01-05  108.29  108.650  105.410  106.25  64285491  AAPL\n",
-       "2015-01-06  106.54  107.430  104.630  106.26  65797116  AAPL\n",
-       "2015-01-07  107.20  108.200  106.695  107.75  40105934  AAPL\n",
-       "2015-01-08  109.23  112.150  108.700  111.89  59364547  AAPL\n",
-       "...            ...      ...      ...     ...       ...   ...\n",
-       "2020-08-24  214.79  215.520  212.430  213.69  25460147  MSFT\n",
-       "2020-08-25  213.10  216.610  213.100  216.47  23043696  MSFT\n",
-       "2020-08-26  217.88  222.090  217.360  221.15  39600828  MSFT\n",
-       "2020-08-27  222.89  231.150  219.400  226.58  57602195  MSFT\n",
-       "2020-08-28  228.18  230.644  226.580  228.91  26292896  MSFT\n",
-       "\n",
-       "[5700 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "frames = [df_apple, df_tesla, df_ibm, df_microsoft]\n",
-    "\n",
-    "df = pd.concat(frames)\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 8. Shift the stock column into the index (making it a multi-level index consisting of the ticker symbol and the date)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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></th>\n",
-       "      <th>open</th>\n",
-       "      <th>high</th>\n",
-       "      <th>low</th>\n",
-       "      <th>close</th>\n",
-       "      <th>volume</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th></th>\n",
-       "      <th>stock</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>2015-01-02</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>111.39</td>\n",
-       "      <td>111.440</td>\n",
-       "      <td>107.350</td>\n",
-       "      <td>109.33</td>\n",
-       "      <td>53204626</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-05</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>108.29</td>\n",
-       "      <td>108.650</td>\n",
-       "      <td>105.410</td>\n",
-       "      <td>106.25</td>\n",
-       "      <td>64285491</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-06</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>106.54</td>\n",
-       "      <td>107.430</td>\n",
-       "      <td>104.630</td>\n",
-       "      <td>106.26</td>\n",
-       "      <td>65797116</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-07</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>107.20</td>\n",
-       "      <td>108.200</td>\n",
-       "      <td>106.695</td>\n",
-       "      <td>107.75</td>\n",
-       "      <td>40105934</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-08</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>109.23</td>\n",
-       "      <td>112.150</td>\n",
-       "      <td>108.700</td>\n",
-       "      <td>111.89</td>\n",
-       "      <td>59364547</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-24</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>214.79</td>\n",
-       "      <td>215.520</td>\n",
-       "      <td>212.430</td>\n",
-       "      <td>213.69</td>\n",
-       "      <td>25460147</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-25</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>213.10</td>\n",
-       "      <td>216.610</td>\n",
-       "      <td>213.100</td>\n",
-       "      <td>216.47</td>\n",
-       "      <td>23043696</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-26</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>217.88</td>\n",
-       "      <td>222.090</td>\n",
-       "      <td>217.360</td>\n",
-       "      <td>221.15</td>\n",
-       "      <td>39600828</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-27</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>222.89</td>\n",
-       "      <td>231.150</td>\n",
-       "      <td>219.400</td>\n",
-       "      <td>226.58</td>\n",
-       "      <td>57602195</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-28</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>228.18</td>\n",
-       "      <td>230.644</td>\n",
-       "      <td>226.580</td>\n",
-       "      <td>228.91</td>\n",
-       "      <td>26292896</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5700 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                    open     high      low   close    volume\n",
-       "           stock                                            \n",
-       "2015-01-02 AAPL   111.39  111.440  107.350  109.33  53204626\n",
-       "2015-01-05 AAPL   108.29  108.650  105.410  106.25  64285491\n",
-       "2015-01-06 AAPL   106.54  107.430  104.630  106.26  65797116\n",
-       "2015-01-07 AAPL   107.20  108.200  106.695  107.75  40105934\n",
-       "2015-01-08 AAPL   109.23  112.150  108.700  111.89  59364547\n",
-       "...                  ...      ...      ...     ...       ...\n",
-       "2020-08-24 MSFT   214.79  215.520  212.430  213.69  25460147\n",
-       "2020-08-25 MSFT   213.10  216.610  213.100  216.47  23043696\n",
-       "2020-08-26 MSFT   217.88  222.090  217.360  221.15  39600828\n",
-       "2020-08-27 MSFT   222.89  231.150  219.400  226.58  57602195\n",
-       "2020-08-28 MSFT   228.18  230.644  226.580  228.91  26292896\n",
-       "\n",
-       "[5700 rows x 5 columns]"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.set_index(keys=\"stock\", append=True, inplace=True)\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 7. Create a dataFrame called vol, with the volume values."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
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-       "\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></th>\n",
-       "      <th>volume</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th></th>\n",
-       "      <th>stock</th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2015-01-02</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>53204626</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-05</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>64285491</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-06</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>65797116</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-07</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>40105934</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015-01-08</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <td>59364547</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-24</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>25460147</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-25</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>23043696</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-26</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>39600828</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-27</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>57602195</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-08-28</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <td>26292896</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5700 rows × 1 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                    volume\n",
-       "           stock          \n",
-       "2015-01-02 AAPL   53204626\n",
-       "2015-01-05 AAPL   64285491\n",
-       "2015-01-06 AAPL   65797116\n",
-       "2015-01-07 AAPL   40105934\n",
-       "2015-01-08 AAPL   59364547\n",
-       "...                    ...\n",
-       "2020-08-24 MSFT   25460147\n",
-       "2020-08-25 MSFT   23043696\n",
-       "2020-08-26 MSFT   39600828\n",
-       "2020-08-27 MSFT   57602195\n",
-       "2020-08-28 MSFT   26292896\n",
-       "\n",
-       "[5700 rows x 1 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "vol = df['volume']\n",
-    "vol = pd.DataFrame(vol)\n",
-    "vol"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 8. Aggregate the data of volume to weekly.\n",
-    "Hint: Be careful to not sum data from the same week of 2015 and other years."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "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>stock</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <th>IBM</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <th>TSLA</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>year</th>\n",
-       "      <th>week</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
-       "      <th>1</th>\n",
-       "      <td>53204626</td>\n",
-       "      <td>5525341</td>\n",
-       "      <td>27913852</td>\n",
-       "      <td>4764443</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>282868187</td>\n",
-       "      <td>24440360</td>\n",
-       "      <td>158596624</td>\n",
-       "      <td>22622034</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>304226647</td>\n",
-       "      <td>23272056</td>\n",
-       "      <td>157088136</td>\n",
-       "      <td>30799137</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>198737041</td>\n",
-       "      <td>31230797</td>\n",
-       "      <td>137352632</td>\n",
-       "      <td>16215501</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>465842684</td>\n",
-       "      <td>32927307</td>\n",
-       "      <td>437786778</td>\n",
-       "      <td>15720217</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th rowspan=\"5\" valign=\"top\">2020</th>\n",
-       "      <th>31</th>\n",
-       "      <td>211898609</td>\n",
-       "      <td>20010578</td>\n",
-       "      <td>149372422</td>\n",
-       "      <td>61152261</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32</th>\n",
-       "      <td>250852555</td>\n",
-       "      <td>17701697</td>\n",
-       "      <td>217598950</td>\n",
-       "      <td>37091084</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>235474473</td>\n",
-       "      <td>18634659</td>\n",
-       "      <td>141752091</td>\n",
-       "      <td>71049854</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>208464758</td>\n",
-       "      <td>15908978</td>\n",
-       "      <td>132258021</td>\n",
-       "      <td>90804281</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>265909531</td>\n",
-       "      <td>16959794</td>\n",
-       "      <td>171999762</td>\n",
-       "      <td>88736115</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>296 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "stock           AAPL       IBM       MSFT      TSLA\n",
-       "year week                                          \n",
-       "2015 1      53204626   5525341   27913852   4764443\n",
-       "     2     282868187  24440360  158596624  22622034\n",
-       "     3     304226647  23272056  157088136  30799137\n",
-       "     4     198737041  31230797  137352632  16215501\n",
-       "     5     465842684  32927307  437786778  15720217\n",
-       "...              ...       ...        ...       ...\n",
-       "2020 31    211898609  20010578  149372422  61152261\n",
-       "     32    250852555  17701697  217598950  37091084\n",
-       "     33    235474473  18634659  141752091  71049854\n",
-       "     34    208464758  15908978  132258021  90804281\n",
-       "     35    265909531  16959794  171999762  88736115\n",
-       "\n",
-       "[296 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "date = vol.index.get_level_values(0)\n",
-    "date = pd.DatetimeIndex(date) # ensure that it's a datetimeindex, instead of a regular index\n",
-    "\n",
-    "vol['week'] = date.isocalendar().week.values\n",
-    "# .values is necessary to obtain only the week *values*\n",
-    "# otherwise pandas interprets it as a part of an index; this would be a problem as the same week appears multiple times\n",
-    "# (same week number in different years, same week for different stocks)\n",
-    "\n",
-    "vol['year'] = date.year\n",
-    "\n",
-    "pd.pivot_table(vol, values='volume', index=['year', 'week'],\n",
-    "               columns=['stock'], aggfunc=np.sum)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step 9. Find all the volume traded in the year of 2015"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "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",
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-       "\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>stock</th>\n",
-       "      <th>AAPL</th>\n",
-       "      <th>IBM</th>\n",
-       "      <th>MSFT</th>\n",
-       "      <th>TSLA</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>year</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2015</th>\n",
-       "      <td>13064316775</td>\n",
-       "      <td>1105545521</td>\n",
-       "      <td>9057582311</td>\n",
-       "      <td>1086708380</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "stock         AAPL         IBM        MSFT        TSLA\n",
-       "year                                                  \n",
-       "2015   13064316775  1105545521  9057582311  1086708380"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "vol_2015 = vol[vol['year'] == 2015]\n",
-    "\n",
-    "pd.pivot_table(vol_2015, values='volume', index=['year'],\n",
-    "               columns=['stock'], aggfunc=np.sum)"
-   ]
-  }
- ],
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