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Coursera_WebScraping_Exercise
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ScrapingExercise.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# ScrapingExercises"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Author\n",
"Stefano Raneri"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Requirements"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: requests in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (2.31.0)\n",
"Requirement already satisfied: pandas in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (2.2.2)\n",
"Requirement already satisfied: yfinance in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (0.2.37)\n",
"Requirement already satisfied: plotly in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (5.20.0)\n",
"Requirement already satisfied: nbformat in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (5.10.4)\n",
"Requirement already satisfied: bs4 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (0.0.2)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests) (3.7)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests) (2.2.1)\n",
"Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests) (2024.2.2)\n",
"Requirement already satisfied: numpy>=1.23.2 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas) (1.26.4)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from pandas) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas) (2024.1)\n",
"Requirement already satisfied: tzdata>=2022.7 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas) (2024.1)\n",
"Requirement already satisfied: multitasking>=0.0.7 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (0.0.11)\n",
"Requirement already satisfied: lxml>=4.9.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (5.2.1)\n",
"Requirement already satisfied: appdirs>=1.4.4 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (1.4.4)\n",
"Requirement already satisfied: frozendict>=2.3.4 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (2.4.2)\n",
"Requirement already satisfied: peewee>=3.16.2 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (3.17.1)\n",
"Requirement already satisfied: beautifulsoup4>=4.11.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (4.12.3)\n",
"Requirement already satisfied: html5lib>=1.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from yfinance) (1.1)\n",
"Requirement already satisfied: tenacity>=6.2.0 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from plotly) (8.2.3)\n",
"Requirement already satisfied: packaging in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from plotly) (24.0)\n",
"Requirement already satisfied: fastjsonschema>=2.15 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbformat) (2.19.1)\n",
"Requirement already satisfied: jsonschema>=2.6 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbformat) (4.21.1)\n",
"Requirement already satisfied: jupyter-core!=5.0.*,>=4.12 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from nbformat) (5.7.2)\n",
"Requirement already satisfied: traitlets>=5.1 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from nbformat) (5.14.2)\n",
"Requirement already satisfied: soupsieve>1.2 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from beautifulsoup4>=4.11.1->yfinance) (2.5)\n",
"Requirement already satisfied: six>=1.9 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from html5lib>=1.1->yfinance) (1.16.0)\n",
"Requirement already satisfied: webencodings in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from html5lib>=1.1->yfinance) (0.5.1)\n",
"Requirement already satisfied: attrs>=22.2.0 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jsonschema>=2.6->nbformat) (23.2.0)\n",
"Requirement already satisfied: jsonschema-specifications>=2023.03.6 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jsonschema>=2.6->nbformat) (2023.12.1)\n",
"Requirement already satisfied: referencing>=0.28.4 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jsonschema>=2.6->nbformat) (0.34.0)\n",
"Requirement already satisfied: rpds-py>=0.7.1 in c:\\users\\stefa\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jsonschema>=2.6->nbformat) (0.18.0)\n",
"Requirement already satisfied: platformdirs>=2.5 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from jupyter-core!=5.0.*,>=4.12->nbformat) (4.2.0)\n",
"Requirement already satisfied: pywin32>=300 in c:\\users\\stefa\\appdata\\roaming\\python\\python311\\site-packages (from jupyter-core!=5.0.*,>=4.12->nbformat) (306)\n"
]
}
],
"source": [
"# Install requests, pandas, yfinance, plotly and Beautiful soup libraries\n",
"!pip install requests pandas yfinance plotly nbformat bs4"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Question 1 - Extracting Tesla Stock Data Using yfinance"
]
},
{
"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>Date</th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Dividends</th>\n",
" <th>Stock Splits</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2010-06-29 00:00:00-04:00</td>\n",
" <td>1.266667</td>\n",
" <td>1.666667</td>\n",
" <td>1.169333</td>\n",
" <td>1.592667</td>\n",
" <td>281494500</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2010-06-30 00:00:00-04:00</td>\n",
" <td>1.719333</td>\n",
" <td>2.028000</td>\n",
" <td>1.553333</td>\n",
" <td>1.588667</td>\n",
" <td>257806500</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2010-07-01 00:00:00-04:00</td>\n",
" <td>1.666667</td>\n",
" <td>1.728000</td>\n",
" <td>1.351333</td>\n",
" <td>1.464000</td>\n",
" <td>123282000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2010-07-02 00:00:00-04:00</td>\n",
" <td>1.533333</td>\n",
" <td>1.540000</td>\n",
" <td>1.247333</td>\n",
" <td>1.280000</td>\n",
" <td>77097000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2010-07-06 00:00:00-04:00</td>\n",
" <td>1.333333</td>\n",
" <td>1.333333</td>\n",
" <td>1.055333</td>\n",
" <td>1.074000</td>\n",
" <td>103003500</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Open High Low Close \\\n",
"0 2010-06-29 00:00:00-04:00 1.266667 1.666667 1.169333 1.592667 \n",
"1 2010-06-30 00:00:00-04:00 1.719333 2.028000 1.553333 1.588667 \n",
"2 2010-07-01 00:00:00-04:00 1.666667 1.728000 1.351333 1.464000 \n",
"3 2010-07-02 00:00:00-04:00 1.533333 1.540000 1.247333 1.280000 \n",
"4 2010-07-06 00:00:00-04:00 1.333333 1.333333 1.055333 1.074000 \n",
"\n",
" Volume Dividends Stock Splits \n",
"0 281494500 0.0 0.0 \n",
"1 257806500 0.0 0.0 \n",
"2 123282000 0.0 0.0 \n",
"3 77097000 0.0 0.0 \n",
"4 103003500 0.0 0.0 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import yfinance as yf\n",
"\n",
"# Create ticker for TESLA stocks data\n",
"ticker = yf.Ticker(\"TSLA\")\n",
"\n",
"# Retrieve the entire history into a dataframe\n",
"tesla_stock_data = ticker.history(period=\"max\")\n",
"\n",
"# Visualize data\n",
"tesla_stock_data.reset_index(inplace=True)\n",
"tesla_stock_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 2 - Extracting Tesla Revenue Data Using Webscraping "
]
},
{
"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>Date</th>\n",
" <th>Revenue</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>53</th>\n",
" <td>2010-09-30</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>2010-06-30</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>2010-03-31</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td>2009-09-30</td>\n",
" <td>46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>2009-06-30</td>\n",
" <td>27</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Revenue\n",
"53 2010-09-30 31\n",
"54 2010-06-30 28\n",
"55 2010-03-31 21\n",
"56 2009-09-30 46\n",
"57 2009-06-30 27"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import requests\n",
"import pandas as pd\n",
"from bs4 import BeautifulSoup\n",
"\n",
"URL = \"https://www.macrotrends.net/stocks/charts/TSLA/tesla/revenue\"\n",
"headers = {\n",
" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:124.0) Gecko/20100101 Firefox/124.0\"\n",
"}\n",
"html = requests.get(URL, headers=headers, timeout=10).text\n",
"# Parse the HTML with BeautifulSoup\n",
"soup = BeautifulSoup(html, \"html5lib\")\n",
"\n",
"# Retrieve first table element as quarterly revenue table\n",
"revenue_table = soup.find_all(\"table\")[1]\n",
"\n",
"# Extract Revenue data into a Dataframe\n",
"revenue_data = []\n",
"\n",
"# Extract Date and Revenue data cells from table\n",
"for row in revenue_table.tbody.find_all(\"tr\"):\n",
" col = row.find_all(\"td\")\n",
" if not col:\n",
" continue\n",
" date = col[0].text\n",
" try:\n",
" revenue = int(col[1].text.replace(\"$\", \"\").replace(\",\", \"\"))\n",
" except ValueError:\n",
" continue\n",
" revenue_data.append({\"Date\": date, \"Revenue\": revenue})\n",
"\n",
"# Wrap data into DataFrame\n",
"tesla_revenue_dataframe = pd.DataFrame(revenue_data)\n",
"tesla_revenue_dataframe.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 3 - Extracting GameStop Stock Data Using yfinance"
]
},
{
"cell_type": "code",
"execution_count": 11,
"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>Date</th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Dividends</th>\n",
" <th>Stock Splits</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2002-02-13 00:00:00-05:00</td>\n",
" <td>1.620128</td>\n",
" <td>1.693350</td>\n",
" <td>1.603296</td>\n",
" <td>1.691667</td>\n",
" <td>76216000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2002-02-14 00:00:00-05:00</td>\n",
" <td>1.712707</td>\n",
" <td>1.716074</td>\n",
" <td>1.670626</td>\n",
" <td>1.683250</td>\n",
" <td>11021600</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2002-02-15 00:00:00-05:00</td>\n",
" <td>1.683250</td>\n",
" <td>1.687458</td>\n",
" <td>1.658002</td>\n",
" <td>1.674834</td>\n",
" <td>8389600</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2002-02-19 00:00:00-05:00</td>\n",
" <td>1.666418</td>\n",
" <td>1.666418</td>\n",
" <td>1.578047</td>\n",
" <td>1.607504</td>\n",
" <td>7410400</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2002-02-20 00:00:00-05:00</td>\n",
" <td>1.615920</td>\n",
" <td>1.662210</td>\n",
" <td>1.603296</td>\n",
" <td>1.662210</td>\n",
" <td>6892800</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Open High Low Close Volume \\\n",
"0 2002-02-13 00:00:00-05:00 1.620128 1.693350 1.603296 1.691667 76216000 \n",
"1 2002-02-14 00:00:00-05:00 1.712707 1.716074 1.670626 1.683250 11021600 \n",
"2 2002-02-15 00:00:00-05:00 1.683250 1.687458 1.658002 1.674834 8389600 \n",
"3 2002-02-19 00:00:00-05:00 1.666418 1.666418 1.578047 1.607504 7410400 \n",
"4 2002-02-20 00:00:00-05:00 1.615920 1.662210 1.603296 1.662210 6892800 \n",
"\n",
" Dividends Stock Splits \n",
"0 0.0 0.0 \n",
"1 0.0 0.0 \n",
"2 0.0 0.0 \n",
"3 0.0 0.0 \n",
"4 0.0 0.0 "
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import yfinance as yf\n",
"\n",
"# Create ticker for GameStop stocks data\n",
"ticker = yf.Ticker(\"GME\")\n",
"\n",
"# Retrieve the entire history into a dataframe\n",
"game_stop_stock_data = ticker.history(period=\"max\")\n",
"\n",
"# Visualize data\n",
"game_stop_stock_data.reset_index(inplace=True)\n",
"game_stop_stock_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 4 - Extracting GameStop Revenue Data Using Webscraping"
]
},
{
"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>Date</th>\n",
" <th>Revenue</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>2010-01-31</td>\n",
" <td>3524</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td>2009-10-31</td>\n",
" <td>1835</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>2009-07-31</td>\n",
" <td>1739</td>\n",
" </tr>\n",
" <tr>\n",
" <th>58</th>\n",
" <td>2009-04-30</td>\n",
" <td>1981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td>2009-01-31</td>\n",
" <td>3492</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Revenue\n",
"55 2010-01-31 3524\n",
"56 2009-10-31 1835\n",
"57 2009-07-31 1739\n",
"58 2009-04-30 1981\n",
"59 2009-01-31 3492"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import requests\n",
"import pandas as pd\n",
"from bs4 import BeautifulSoup\n",
"\n",
"# Change the URL to target GameStop data\n",
"URL = \"https://www.macrotrends.net/stocks/charts/GME/gamestop/revenue\"\n",
"headers = {\n",
" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:124.0) Gecko/20100101 Firefox/124.0\"\n",
"}\n",
"html = requests.get(URL, headers=headers, timeout=10).text\n",
"# Parse the HTML with BeautifulSoup\n",
"soup = BeautifulSoup(html, \"html5lib\")\n",
"\n",
"# Retrieve first table element as quarterly revenue table\n",
"revenue_table = soup.find_all(\"table\")[1]\n",
"\n",
"# Extract Revenue data into a Dataframe\n",
"revenue_data = []\n",
"\n",
"# Extract Date and Revenue data cells from table\n",
"for row in revenue_table.tbody.find_all(\"tr\"):\n",
" col = row.find_all(\"td\")\n",
" if not col:\n",
" continue\n",
" date = col[0].text\n",
" try:\n",
" revenue = int(col[1].text.replace(\"$\", \"\").replace(\",\", \"\"))\n",
" except ValueError:\n",
" continue\n",
" revenue_data.append({\"Date\": date, \"Revenue\": revenue})\n",
"\n",
"# Wrap data into DataFrame\n",
"gamestop_revenue_dataframe = pd.DataFrame(revenue_data)\n",
"gamestop_revenue_dataframe.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Define make_graph function"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"\n",
"import plotly.graph_objects as go\n",
"from plotly.subplots import make_subplots\n",
"def make_graph(stock_data, revenue_data, stock):\n",
" fig = make_subplots(rows=2, cols=1, shared_xaxes=True, subplot_titles=(\"Historical Share Price\", \"Historical Revenue\"), vertical_spacing = .3)\n",
" fig.add_trace(go.Scatter(x=pd.to_datetime(stock_data.Date, infer_datetime_format=True), y=stock_data.Close.astype(\"float\"), name=\"Share Price\"), row=1, col=1)\n",
" fig.add_trace(go.Scatter(x=pd.to_datetime(revenue_data.Date, infer_datetime_format=True), y=revenue_data.Revenue.astype(\"float\"), name=\"Revenue\"), row=2, col=1)\n",
" fig.update_xaxes(title_text=\"Date\", row=1, col=1)\n",
" fig.update_xaxes(title_text=\"Date\", row=2, col=1)\n",
" fig.update_yaxes(title_text=\"Price ($US)\", row=1, col=1)\n",
" fig.update_yaxes(title_text=\"Revenue ($US Millions)\", row=2, col=1)\n",
" fig.update_layout(showlegend=False,\n",
" height=900,\n",
" title=stock,\n",
" xaxis_rangeslider_visible=True)\n",
" fig.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 5 - Plot Tesla Stock Graph"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\stefa\\AppData\\Local\\Temp\\ipykernel_25308\\3194230702.py:5: UserWarning:\n",
"\n",
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
"\n",
"C:\\Users\\stefa\\AppData\\Local\\Temp\\ipykernel_25308\\3194230702.py:6: UserWarning:\n",
"\n",
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
"\n"
]
},
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"name": "Share Price",
"type": "scatter",
"x": [
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"2010-07-06T00:00:00-04:00",
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"2010-07-08T00:00:00-04:00",
"2010-07-09T00:00:00-04:00",
"2010-07-12T00:00:00-04:00",
"2010-07-13T00:00:00-04:00",
"2010-07-14T00:00:00-04:00",
"2010-07-15T00:00:00-04:00",
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"2010-08-17T00:00:00-04:00",
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"2010-08-23T00:00:00-04:00",
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"2010-08-25T00:00:00-04:00",
"2010-08-26T00:00:00-04:00",
"2010-08-27T00:00:00-04:00",
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"2010-08-31T00:00:00-04:00",
"2010-09-01T00:00:00-04:00",
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"2010-09-03T00:00:00-04:00",
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"2010-09-14T00:00:00-04:00",
"2010-09-15T00:00:00-04:00",
"2010-09-16T00:00:00-04:00",
"2010-09-17T00:00:00-04:00",
"2010-09-20T00:00:00-04:00",
"2010-09-21T00:00:00-04:00",
"2010-09-22T00:00:00-04:00",
"2010-09-23T00:00:00-04:00",
"2010-09-24T00:00:00-04:00",
"2010-09-27T00:00:00-04:00",
"2010-09-28T00:00:00-04:00",
"2010-09-29T00:00:00-04:00",
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"2010-10-01T00:00:00-04:00",
"2010-10-04T00:00:00-04:00",
"2010-10-05T00:00:00-04:00",
"2010-10-06T00:00:00-04:00",
"2010-10-07T00:00:00-04:00",
"2010-10-08T00:00:00-04:00",
"2010-10-11T00:00:00-04:00",
"2010-10-12T00:00:00-04:00",
"2010-10-13T00:00:00-04:00",
"2010-10-14T00:00:00-04:00",
"2010-10-15T00:00:00-04:00",
"2010-10-18T00:00:00-04:00",
"2010-10-19T00:00:00-04:00",
"2010-10-20T00:00:00-04:00",
"2010-10-21T00:00:00-04:00",
"2010-10-22T00:00:00-04:00",
"2010-10-25T00:00:00-04:00",
"2010-10-26T00:00:00-04:00",
"2010-10-27T00:00:00-04:00",
"2010-10-28T00:00:00-04:00",
"2010-10-29T00:00:00-04:00",
"2010-11-01T00:00:00-04:00",
"2010-11-02T00:00:00-04:00",
"2010-11-03T00:00:00-04:00",
"2010-11-04T00:00:00-04:00",
"2010-11-05T00:00:00-04:00",
"2010-11-08T00:00:00-05:00",
"2010-11-09T00:00:00-05:00",
"2010-11-10T00:00:00-05:00",
"2010-11-11T00:00:00-05:00",
"2010-11-12T00:00:00-05:00",
"2010-11-15T00:00:00-05:00",
"2010-11-16T00:00:00-05:00",
"2010-11-17T00:00:00-05:00",
"2010-11-18T00:00:00-05:00",
"2010-11-19T00:00:00-05:00",
"2010-11-22T00:00:00-05:00",
"2010-11-23T00:00:00-05:00",
"2010-11-24T00:00:00-05:00",
"2010-11-26T00:00:00-05:00",
"2010-11-29T00:00:00-05:00",
"2010-11-30T00:00:00-05:00",
"2010-12-01T00:00:00-05:00",
"2010-12-02T00:00:00-05:00",
"2010-12-03T00:00:00-05:00",
"2010-12-06T00:00:00-05:00",
"2010-12-07T00:00:00-05:00",
"2010-12-08T00:00:00-05:00",
"2010-12-09T00:00:00-05:00",
"2010-12-10T00:00:00-05:00",
"2010-12-13T00:00:00-05:00",
"2010-12-14T00:00:00-05:00",
"2010-12-15T00:00:00-05:00",
"2010-12-16T00:00:00-05:00",
"2010-12-17T00:00:00-05:00",
"2010-12-20T00:00:00-05:00",
"2010-12-21T00:00:00-05:00",
"2010-12-22T00:00:00-05:00",
"2010-12-23T00:00:00-05:00",
"2010-12-27T00:00:00-05:00",
"2010-12-28T00:00:00-05:00",
"2010-12-29T00:00:00-05:00",
"2010-12-30T00:00:00-05:00",
"2010-12-31T00:00:00-05:00",
"2011-01-03T00:00:00-05:00",
"2011-01-04T00:00:00-05:00",
"2011-01-05T00:00:00-05:00",
"2011-01-06T00:00:00-05:00",
"2011-01-07T00:00:00-05:00",
"2011-01-10T00:00:00-05:00",
"2011-01-11T00:00:00-05:00",
"2011-01-12T00:00:00-05:00",
"2011-01-13T00:00:00-05:00",
"2011-01-14T00:00:00-05:00",
"2011-01-18T00:00:00-05:00",
"2011-01-19T00:00:00-05:00",
"2011-01-20T00:00:00-05:00",
"2011-01-21T00:00:00-05:00",
"2011-01-24T00:00:00-05:00",
"2011-01-25T00:00:00-05:00",
"2011-01-26T00:00:00-05:00",
"2011-01-27T00:00:00-05:00",
"2011-01-28T00:00:00-05:00",
"2011-01-31T00:00:00-05:00",
"2011-02-01T00:00:00-05:00",
"2011-02-02T00:00:00-05:00",
"2011-02-03T00:00:00-05:00",
"2011-02-04T00:00:00-05:00",
"2011-02-07T00:00:00-05:00",
"2011-02-08T00:00:00-05:00",
"2011-02-09T00:00:00-05:00",
"2011-02-10T00:00:00-05:00",
"2011-02-11T00:00:00-05:00",
"2011-02-14T00:00:00-05:00",
"2011-02-15T00:00:00-05:00",
"2011-02-16T00:00:00-05:00",
"2011-02-17T00:00:00-05:00",
"2011-02-18T00:00:00-05:00",
"2011-02-22T00:00:00-05:00",
"2011-02-23T00:00:00-05:00",
"2011-02-24T00:00:00-05:00",
"2011-02-25T00:00:00-05:00",
"2011-02-28T00:00:00-05:00",
"2011-03-01T00:00:00-05:00",
"2011-03-02T00:00:00-05:00",
"2011-03-03T00:00:00-05:00",
"2011-03-04T00:00:00-05:00",
"2011-03-07T00:00:00-05:00",
"2011-03-08T00:00:00-05:00",
"2011-03-09T00:00:00-05:00",
"2011-03-10T00:00:00-05:00",
"2011-03-11T00:00:00-05:00",
"2011-03-14T00:00:00-04:00",
"2011-03-15T00:00:00-04:00",
"2011-03-16T00:00:00-04:00",
"2011-03-17T00:00:00-04:00",
"2011-03-18T00:00:00-04:00",
"2011-03-21T00:00:00-04:00",
"2011-03-22T00:00:00-04:00",
"2011-03-23T00:00:00-04:00",
"2011-03-24T00:00:00-04:00",
"2011-03-25T00:00:00-04:00",
"2011-03-28T00:00:00-04:00",
"2011-03-29T00:00:00-04:00",
"2011-03-30T00:00:00-04:00",
"2011-03-31T00:00:00-04:00",
"2011-04-01T00:00:00-04:00",
"2011-04-04T00:00:00-04:00",
"2011-04-05T00:00:00-04:00",
"2011-04-06T00:00:00-04:00",
"2011-04-07T00:00:00-04:00",
"2011-04-08T00:00:00-04:00",
"2011-04-11T00:00:00-04:00",
"2011-04-12T00:00:00-04:00",
"2011-04-13T00:00:00-04:00",
"2011-04-14T00:00:00-04:00",
"2011-04-15T00:00:00-04:00",
"2011-04-18T00:00:00-04:00",
"2011-04-19T00:00:00-04:00",
"2011-04-20T00:00:00-04:00",
"2011-04-21T00:00:00-04:00",
"2011-04-25T00:00:00-04:00",
"2011-04-26T00:00:00-04:00",
"2011-04-27T00:00:00-04:00",
"2011-04-28T00:00:00-04:00",
"2011-04-29T00:00:00-04:00",
"2011-05-02T00:00:00-04:00",
"2011-05-03T00:00:00-04:00",
"2011-05-04T00:00:00-04:00",
"2011-05-05T00:00:00-04:00",
"2011-05-06T00:00:00-04:00",
"2011-05-09T00:00:00-04:00",
"2011-05-10T00:00:00-04:00",
"2011-05-11T00:00:00-04:00",
"2011-05-12T00:00:00-04:00",
"2011-05-13T00:00:00-04:00",
"2011-05-16T00:00:00-04:00",
"2011-05-17T00:00:00-04:00",
"2011-05-18T00:00:00-04:00",
"2011-05-19T00:00:00-04:00",
"2011-05-20T00:00:00-04:00",
"2011-05-23T00:00:00-04:00",
"2011-05-24T00:00:00-04:00",
"2011-05-25T00:00:00-04:00",
"2011-05-26T00:00:00-04:00",
"2011-05-27T00:00:00-04:00",
"2011-05-31T00:00:00-04:00",
"2011-06-01T00:00:00-04:00",
"2011-06-02T00:00:00-04:00",
"2011-06-03T00:00:00-04:00",
"2011-06-06T00:00:00-04:00",
"2011-06-07T00:00:00-04:00",
"2011-06-08T00:00:00-04:00",
"2011-06-09T00:00:00-04:00",
"2011-06-10T00:00:00-04:00",
"2011-06-13T00:00:00-04:00",
"2011-06-14T00:00:00-04:00",
"2011-06-15T00:00:00-04:00",
"2011-06-16T00:00:00-04:00",
"2011-06-17T00:00:00-04:00",
"2011-06-20T00:00:00-04:00",
"2011-06-21T00:00:00-04:00",
"2011-06-22T00:00:00-04:00",
"2011-06-23T00:00:00-04:00",
"2011-06-24T00:00:00-04:00",
"2011-06-27T00:00:00-04:00",
"2011-06-28T00:00:00-04:00",
"2011-06-29T00:00:00-04:00",
"2011-06-30T00:00:00-04:00",
"2011-07-01T00:00:00-04:00",
"2011-07-05T00:00:00-04:00",
"2011-07-06T00:00:00-04:00",
"2011-07-07T00:00:00-04:00",
"2011-07-08T00:00:00-04:00",
"2011-07-11T00:00:00-04:00",
"2011-07-12T00:00:00-04:00",
"2011-07-13T00:00:00-04:00",
"2011-07-14T00:00:00-04:00",
"2011-07-15T00:00:00-04:00",
"2011-07-18T00:00:00-04:00",
"2011-07-19T00:00:00-04:00",
"2011-07-20T00:00:00-04:00",
"2011-07-21T00:00:00-04:00",
"2011-07-22T00:00:00-04:00",
"2011-07-25T00:00:00-04:00",
"2011-07-26T00:00:00-04:00",
"2011-07-27T00:00:00-04:00",
"2011-07-28T00:00:00-04:00",
"2011-07-29T00:00:00-04:00",
"2011-08-01T00:00:00-04:00",
"2011-08-02T00:00:00-04:00",
"2011-08-03T00:00:00-04:00",
"2011-08-04T00:00:00-04:00",
"2011-08-05T00:00:00-04:00",
"2011-08-08T00:00:00-04:00",
"2011-08-09T00:00:00-04:00",
"2011-08-10T00:00:00-04:00",
"2011-08-11T00:00:00-04:00",
"2011-08-12T00:00:00-04:00",
"2011-08-15T00:00:00-04:00",
"2011-08-16T00:00:00-04:00",
"2011-08-17T00:00:00-04:00",
"2011-08-18T00:00:00-04:00",
"2011-08-19T00:00:00-04:00",
"2011-08-22T00:00:00-04:00",
"2011-08-23T00:00:00-04:00",
"2011-08-24T00:00:00-04:00",
"2011-08-25T00:00:00-04:00",
"2011-08-26T00:00:00-04:00",
"2011-08-29T00:00:00-04:00",
"2011-08-30T00:00:00-04:00",
"2011-08-31T00:00:00-04:00",
"2011-09-01T00:00:00-04:00",
"2011-09-02T00:00:00-04:00",
"2011-09-06T00:00:00-04:00",
"2011-09-07T00:00:00-04:00",
"2011-09-08T00:00:00-04:00",
"2011-09-09T00:00:00-04:00",
"2011-09-12T00:00:00-04:00",
"2011-09-13T00:00:00-04:00",
"2011-09-14T00:00:00-04:00",
"2011-09-15T00:00:00-04:00",
"2011-09-16T00:00:00-04:00",
"2011-09-19T00:00:00-04:00",
"2011-09-20T00:00:00-04:00",
"2011-09-21T00:00:00-04:00",
"2011-09-22T00:00:00-04:00",
"2011-09-23T00:00:00-04:00",
"2011-09-26T00:00:00-04:00",
"2011-09-27T00:00:00-04:00",
"2011-09-28T00:00:00-04:00",
"2011-09-29T00:00:00-04:00",
"2011-09-30T00:00:00-04:00",
"2011-10-03T00:00:00-04:00",
"2011-10-04T00:00:00-04:00",
"2011-10-05T00:00:00-04:00",
"2011-10-06T00:00:00-04:00",
"2011-10-07T00:00:00-04:00",
"2011-10-10T00:00:00-04:00",
"2011-10-11T00:00:00-04:00",
"2011-10-12T00:00:00-04:00",
"2011-10-13T00:00:00-04:00",
"2011-10-14T00:00:00-04:00",
"2011-10-17T00:00:00-04:00",
"2011-10-18T00:00:00-04:00",
"2011-10-19T00:00:00-04:00",
"2011-10-20T00:00:00-04:00",
"2011-10-21T00:00:00-04:00",
"2011-10-24T00:00:00-04:00",
"2011-10-25T00:00:00-04:00",
"2011-10-26T00:00:00-04:00",
"2011-10-27T00:00:00-04:00",
"2011-10-28T00:00:00-04:00",
"2011-10-31T00:00:00-04:00",
"2011-11-01T00:00:00-04:00",
"2011-11-02T00:00:00-04:00",
"2011-11-03T00:00:00-04:00",
"2011-11-04T00:00:00-04:00",
"2011-11-07T00:00:00-05:00",
"2011-11-08T00:00:00-05:00",
"2011-11-09T00:00:00-05:00",
"2011-11-10T00:00:00-05:00",
"2011-11-11T00:00:00-05:00",
"2011-11-14T00:00:00-05:00",
"2011-11-15T00:00:00-05:00",
"2011-11-16T00:00:00-05:00",
"2011-11-17T00:00:00-05:00",
"2011-11-18T00:00:00-05:00",
"2011-11-21T00:00:00-05:00",
"2011-11-22T00:00:00-05:00",
"2011-11-23T00:00:00-05:00",
"2011-11-25T00:00:00-05:00",
"2011-11-28T00:00:00-05:00",
"2011-11-29T00:00:00-05:00",
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