diff --git a/09_Time_Series/Getting_Financial_Data/Exercises_solutions.ipynb b/09_Time_Series/Getting_Financial_Data/Exercises_solutions.ipynb
new file mode 100644
index 000000000..7880b7e3d
--- /dev/null
+++ b/09_Time_Series/Getting_Financial_Data/Exercises_solutions.ipynb
@@ -0,0 +1,1194 @@
+{
+ "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 = dt.datetime(2015, 1, 1, 0, 0)\n",
+    "start_dt"
+   ]
+  },
+  {
+   "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>111.390</td>\n",
+       "      <td>111.440</td>\n",
+       "      <td>107.3500</td>\n",
+       "      <td>109.33</td>\n",
+       "      <td>53204626</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-05</th>\n",
+       "      <td>108.290</td>\n",
+       "      <td>108.650</td>\n",
+       "      <td>105.4100</td>\n",
+       "      <td>106.25</td>\n",
+       "      <td>64285491</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-06</th>\n",
+       "      <td>106.540</td>\n",
+       "      <td>107.430</td>\n",
+       "      <td>104.6300</td>\n",
+       "      <td>106.26</td>\n",
+       "      <td>65797116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-07</th>\n",
+       "      <td>107.200</td>\n",
+       "      <td>108.200</td>\n",
+       "      <td>106.6950</td>\n",
+       "      <td>107.75</td>\n",
+       "      <td>40105934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-08</th>\n",
+       "      <td>109.230</td>\n",
+       "      <td>112.150</td>\n",
+       "      <td>108.7000</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>2021-11-15</th>\n",
+       "      <td>150.370</td>\n",
+       "      <td>151.880</td>\n",
+       "      <td>149.4300</td>\n",
+       "      <td>150.00</td>\n",
+       "      <td>59222803</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-16</th>\n",
+       "      <td>149.940</td>\n",
+       "      <td>151.488</td>\n",
+       "      <td>149.3400</td>\n",
+       "      <td>151.00</td>\n",
+       "      <td>59256210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-17</th>\n",
+       "      <td>150.995</td>\n",
+       "      <td>155.000</td>\n",
+       "      <td>150.9900</td>\n",
+       "      <td>153.49</td>\n",
+       "      <td>88807000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-18</th>\n",
+       "      <td>153.710</td>\n",
+       "      <td>158.670</td>\n",
+       "      <td>153.0500</td>\n",
+       "      <td>157.87</td>\n",
+       "      <td>137827673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-19</th>\n",
+       "      <td>157.650</td>\n",
+       "      <td>161.020</td>\n",
+       "      <td>156.5328</td>\n",
+       "      <td>160.55</td>\n",
+       "      <td>116744360</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1735 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               open     high       low   close     volume\n",
+       "2015-01-02  111.390  111.440  107.3500  109.33   53204626\n",
+       "2015-01-05  108.290  108.650  105.4100  106.25   64285491\n",
+       "2015-01-06  106.540  107.430  104.6300  106.26   65797116\n",
+       "2015-01-07  107.200  108.200  106.6950  107.75   40105934\n",
+       "2015-01-08  109.230  112.150  108.7000  111.89   59364547\n",
+       "...             ...      ...       ...     ...        ...\n",
+       "2021-11-15  150.370  151.880  149.4300  150.00   59222803\n",
+       "2021-11-16  149.940  151.488  149.3400  151.00   59256210\n",
+       "2021-11-17  150.995  155.000  150.9900  153.49   88807000\n",
+       "2021-11-18  153.710  158.670  153.0500  157.87  137827673\n",
+       "2021-11-19  157.650  161.020  156.5328  160.55  116744360\n",
+       "\n",
+       "[1735 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_apple = web.DataReader(\"AAPL\", \"av-daily\", start=start_dt, api_key=\"AZOBAQ2SK8AC1MUD\")\n",
+    "df_apple\n"
+   ]
+  },
+  {
+   "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>111.390</td>\n",
+       "      <td>111.440</td>\n",
+       "      <td>107.3500</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>108.290</td>\n",
+       "      <td>108.650</td>\n",
+       "      <td>105.4100</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>106.540</td>\n",
+       "      <td>107.430</td>\n",
+       "      <td>104.6300</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>107.200</td>\n",
+       "      <td>108.200</td>\n",
+       "      <td>106.6950</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>109.230</td>\n",
+       "      <td>112.150</td>\n",
+       "      <td>108.7000</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>2021-11-15</th>\n",
+       "      <td>150.370</td>\n",
+       "      <td>151.880</td>\n",
+       "      <td>149.4300</td>\n",
+       "      <td>150.00</td>\n",
+       "      <td>59222803</td>\n",
+       "      <td>AAPL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-16</th>\n",
+       "      <td>149.940</td>\n",
+       "      <td>151.488</td>\n",
+       "      <td>149.3400</td>\n",
+       "      <td>151.00</td>\n",
+       "      <td>59256210</td>\n",
+       "      <td>AAPL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-17</th>\n",
+       "      <td>150.995</td>\n",
+       "      <td>155.000</td>\n",
+       "      <td>150.9900</td>\n",
+       "      <td>153.49</td>\n",
+       "      <td>88807000</td>\n",
+       "      <td>AAPL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-18</th>\n",
+       "      <td>153.710</td>\n",
+       "      <td>158.670</td>\n",
+       "      <td>153.0500</td>\n",
+       "      <td>157.87</td>\n",
+       "      <td>137827673</td>\n",
+       "      <td>AAPL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-19</th>\n",
+       "      <td>157.650</td>\n",
+       "      <td>161.020</td>\n",
+       "      <td>156.5328</td>\n",
+       "      <td>160.55</td>\n",
+       "      <td>116744360</td>\n",
+       "      <td>AAPL</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1735 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               open     high       low   close     volume stock\n",
+       "2015-01-02  111.390  111.440  107.3500  109.33   53204626  AAPL\n",
+       "2015-01-05  108.290  108.650  105.4100  106.25   64285491  AAPL\n",
+       "2015-01-06  106.540  107.430  104.6300  106.26   65797116  AAPL\n",
+       "2015-01-07  107.200  108.200  106.6950  107.75   40105934  AAPL\n",
+       "2015-01-08  109.230  112.150  108.7000  111.89   59364547  AAPL\n",
+       "...             ...      ...       ...     ...        ...   ...\n",
+       "2021-11-15  150.370  151.880  149.4300  150.00   59222803  AAPL\n",
+       "2021-11-16  149.940  151.488  149.3400  151.00   59256210  AAPL\n",
+       "2021-11-17  150.995  155.000  150.9900  153.49   88807000  AAPL\n",
+       "2021-11-18  153.710  158.670  153.0500  157.87  137827673  AAPL\n",
+       "2021-11-19  157.650  161.020  156.5328  160.55  116744360  AAPL\n",
+       "\n",
+       "[1735 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": [
+    "df_tesla = web.DataReader(\"TSLA\", \"av-daily\", start=start_dt, api_key=\"AZOBAQ2SK8AC1MUD\")\n",
+    "df_tesla['stock'] = \"TSLA\"\n",
+    "\n",
+    "df_ibm = web.DataReader(\"IBM\", \"av-daily\", start=start_dt, api_key=\"AZOBAQ2SK8AC1MUD\")\n",
+    "df_ibm['stock'] = \"IBM\"\n",
+    "\n",
+    "df_microsoft = web.DataReader(\"MSFT\", \"av-daily\", start=start_dt, api_key=\"AZOBAQ2SK8AC1MUD\")\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>111.44</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>108.65</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>107.43</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>108.20</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>112.15</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>2021-11-15</th>\n",
+       "      <td>337.54</td>\n",
+       "      <td>337.88</td>\n",
+       "      <td>334.034</td>\n",
+       "      <td>336.07</td>\n",
+       "      <td>16723009</td>\n",
+       "      <td>MSFT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-16</th>\n",
+       "      <td>335.68</td>\n",
+       "      <td>340.67</td>\n",
+       "      <td>335.510</td>\n",
+       "      <td>339.51</td>\n",
+       "      <td>20886832</td>\n",
+       "      <td>MSFT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-17</th>\n",
+       "      <td>338.94</td>\n",
+       "      <td>342.19</td>\n",
+       "      <td>338.000</td>\n",
+       "      <td>339.12</td>\n",
+       "      <td>19053380</td>\n",
+       "      <td>MSFT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-18</th>\n",
+       "      <td>338.18</td>\n",
+       "      <td>342.45</td>\n",
+       "      <td>337.120</td>\n",
+       "      <td>341.27</td>\n",
+       "      <td>22463533</td>\n",
+       "      <td>MSFT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-19</th>\n",
+       "      <td>342.64</td>\n",
+       "      <td>345.10</td>\n",
+       "      <td>342.200</td>\n",
+       "      <td>343.11</td>\n",
+       "      <td>21095274</td>\n",
+       "      <td>MSFT</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6940 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              open    high      low   close    volume stock\n",
+       "2015-01-02  111.39  111.44  107.350  109.33  53204626  AAPL\n",
+       "2015-01-05  108.29  108.65  105.410  106.25  64285491  AAPL\n",
+       "2015-01-06  106.54  107.43  104.630  106.26  65797116  AAPL\n",
+       "2015-01-07  107.20  108.20  106.695  107.75  40105934  AAPL\n",
+       "2015-01-08  109.23  112.15  108.700  111.89  59364547  AAPL\n",
+       "...            ...     ...      ...     ...       ...   ...\n",
+       "2021-11-15  337.54  337.88  334.034  336.07  16723009  MSFT\n",
+       "2021-11-16  335.68  340.67  335.510  339.51  20886832  MSFT\n",
+       "2021-11-17  338.94  342.19  338.000  339.12  19053380  MSFT\n",
+       "2021-11-18  338.18  342.45  337.120  341.27  22463533  MSFT\n",
+       "2021-11-19  342.64  345.10  342.200  343.11  21095274  MSFT\n",
+       "\n",
+       "[6940 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_all = pd.concat([df_apple, df_tesla, df_ibm, df_microsoft])\n",
+    "df_all"
+   ]
+  },
+  {
+   "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>111.44</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>108.65</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>107.43</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>108.20</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>112.15</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>2021-11-15</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>337.54</td>\n",
+       "      <td>337.88</td>\n",
+       "      <td>334.034</td>\n",
+       "      <td>336.07</td>\n",
+       "      <td>16723009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-16</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>335.68</td>\n",
+       "      <td>340.67</td>\n",
+       "      <td>335.510</td>\n",
+       "      <td>339.51</td>\n",
+       "      <td>20886832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-17</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>338.94</td>\n",
+       "      <td>342.19</td>\n",
+       "      <td>338.000</td>\n",
+       "      <td>339.12</td>\n",
+       "      <td>19053380</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-18</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>338.18</td>\n",
+       "      <td>342.45</td>\n",
+       "      <td>337.120</td>\n",
+       "      <td>341.27</td>\n",
+       "      <td>22463533</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-19</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>342.64</td>\n",
+       "      <td>345.10</td>\n",
+       "      <td>342.200</td>\n",
+       "      <td>343.11</td>\n",
+       "      <td>21095274</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6940 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    open    high      low   close    volume\n",
+       "           stock                                           \n",
+       "2015-01-02 AAPL   111.39  111.44  107.350  109.33  53204626\n",
+       "2015-01-05 AAPL   108.29  108.65  105.410  106.25  64285491\n",
+       "2015-01-06 AAPL   106.54  107.43  104.630  106.26  65797116\n",
+       "2015-01-07 AAPL   107.20  108.20  106.695  107.75  40105934\n",
+       "2015-01-08 AAPL   109.23  112.15  108.700  111.89  59364547\n",
+       "...                  ...     ...      ...     ...       ...\n",
+       "2021-11-15 MSFT   337.54  337.88  334.034  336.07  16723009\n",
+       "2021-11-16 MSFT   335.68  340.67  335.510  339.51  20886832\n",
+       "2021-11-17 MSFT   338.94  342.19  338.000  339.12  19053380\n",
+       "2021-11-18 MSFT   338.18  342.45  337.120  341.27  22463533\n",
+       "2021-11-19 MSFT   342.64  345.10  342.200  343.11  21095274\n",
+       "\n",
+       "[6940 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_all = df_all.set_index('stock', append=True)\n",
+    "df_all"
+   ]
+  },
+  {
+   "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",
+       "    }\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>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>2021-11-15</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>16723009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-16</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>20886832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-17</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>19053380</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-18</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>22463533</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11-19</th>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>21095274</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6940 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",
+       "2021-11-15 MSFT   16723009\n",
+       "2021-11-16 MSFT   20886832\n",
+       "2021-11-17 MSFT   19053380\n",
+       "2021-11-18 MSFT   22463533\n",
+       "2021-11-19 MSFT   21095274\n",
+       "\n",
+       "[6940 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vol = df_all.filter(['volume'])\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\">2021</th>\n",
+       "      <th>42</th>\n",
+       "      <td>340691290</td>\n",
+       "      <td>59731582</td>\n",
+       "      <td>91315937</td>\n",
+       "      <td>109982713</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>392739936</td>\n",
+       "      <td>34288134</td>\n",
+       "      <td>159314433</td>\n",
+       "      <td>220925116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>322688958</td>\n",
+       "      <td>29791780</td>\n",
+       "      <td>120621826</td>\n",
+       "      <td>178974628</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>281026556</td>\n",
+       "      <td>29109912</td>\n",
+       "      <td>106622220</td>\n",
+       "      <td>182318404</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>461858046</td>\n",
+       "      <td>24205817</td>\n",
+       "      <td>100222028</td>\n",
+       "      <td>134998459</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>360 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",
+       "2021 42    340691290  59731582   91315937  109982713\n",
+       "     43    392739936  34288134  159314433  220925116\n",
+       "     44    322688958  29791780  120621826  178974628\n",
+       "     45    281026556  29109912  106622220  182318404\n",
+       "     46    461858046  24205817  100222028  134998459\n",
+       "\n",
+       "[360 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vol_week = vol.rename_axis(index=['dt', 'stock'])\n",
+    "vol_week.reset_index(inplace=True)\n",
+    "vol_week.dt = pd.to_datetime(vol_week.dt)\n",
+    "vol_week['year'] = vol_week['dt'].map(lambda x: x.year)\n",
+    "vol_week['week'] = vol_week['dt'].map(lambda x: x.week)\n",
+    "vol_week.pop('dt')\n",
+    "\n",
+    "vol_week.set_index(['year', 'week', 'stock'], inplace=True)\n",
+    "vol_week = vol_week.groupby([pd.Grouper(level='stock'), pd.Grouper(level='year'), pd.Grouper(level='week')]).sum()\n",
+    "\n",
+    "vol_week = vol_week.reset_index()\n",
+    "vol_week = vol_week.pivot(index=['year', 'week'], columns='stock')\n",
+    "vol_week.columns.droplevel(0)\n",
+    "vol_week.columns = vol_week.columns.droplevel(0)\n",
+    "vol_week"
+   ]
+  },
+  {
+   "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",
+       "        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>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_year = vol_week.groupby('year').sum()\n",
+    "vol_year.loc[2015:2015]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}