{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Console Games Sales Decline "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You have been hired to join the in-house Data Science team of a video games design company. The company designs games for computers but is considering getting into the console games business.\n",
"\n",
"Note: consoles refer to devices that are attached to TV’s. For example, Play Station.\n",
"\n",
"However, the executives of the company have noticed that other rival console games design companies have been suffering increasing losses in the past couple of years. That’s why they want you to investigate the state of the industry to help them make the decision of whether to get into this business.\n",
"\n",
"On the Case Study page you will find a dataset with over 16,000 console game titles sold between 1980 and 2015. Sales are broken down into 4 regions and are shown in Millions of Dollars.\n",
"\n",
"The CSO (Chief Strategy Officer) has posed you the following questions:\n",
"1. How have the total sales of console games been declining over the years by different genres?\n",
"2. How do different platforms compare side-by-side in terms of aggregate global sales since their inceptions? Who is the leader?\n",
"3. How do different publishers compare side-by-side in terms of aggregate global sales since their inceptions? Who is the leader?\n",
"4. How do the New Generation (New Gen) consoles compare in terms of total global sales for combined 2014 and 2015? New Gen platforms in this dataset are PS4, XOne and WiiU.\n",
"5. What are the top 10 game titles with the highest global sales?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Credits"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook is a part of my learning path based on the workshop [Case Study 001 : [Tableau] Console Games Sales Decline](https://www.superdatascience.com/casestudy001/) presented on [Super Data Science](http://www.superdatascience.com) platform.\n",
"\n",
"SuperDataScience team publish a lot of courses (available on the [Udemy](https://www.udemy.com) platform) taught by [Kirill Eremenko](https://www.udemy.com/user/kirilleremenko/) and [Hadelin de Ponteves](https://www.udemy.com/user/hadelin-de-ponteves/) in the wide space of Data Science.\n",
"\n",
"Here are the most valuable one in the field of Data Science, Machine Learning and Deep Learning:\n",
"1. [Data Science A-Z™: Real-Life Data Science Exercises Included](https://www.udemy.com/datascience/learn/v4/overview)\n",
"2. [Python A-Z™: Python For Data Science With Real Exercises!](https://www.udemy.com/python-coding/learn/v4/overview)\n",
"3. [R Programming A-Z™: R For Data Science With Real Exercises!](https://www.udemy.com/r-programming/learn/v4/overview)\n",
"4. [Machine Learning A-Z™: Hands-On Python & R In Data Science](https://www.udemy.com/machinelearning/learn/v4/overview)\n",
"5. [Deep Learning A-Z™: Hands-On Artificial Neural Networks](https://www.udemy.com/deeplearning/learn/v4/overview)\n",
"6. [Artificial Intelligence A-Z™: Learn How To Build An AI](https://www.udemy.com/artificial-intelligence-az/learn/v4/overview)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Preparation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Import libraries**"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"\n",
"# Use Seaborn styles.\n",
"# See 'Controlling figure aesthetics': https://seaborn.pydata.org/tutorial/aesthetics.html\n",
"sns.set()\n",
"sns.set_style('darkgrid')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Load the data**"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"../../data/ConsoleGames.csv\")\n",
"# See '10 Minutes to pandas': https://pandas.pydata.org/pandas-docs/stable/10min.html"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Check the structure of the data**\n",
"\n",
"First, let's get a feel of what our data look like."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rank</th>\n",
" <th>Name</th>\n",
" <th>Platform</th>\n",
" <th>Year</th>\n",
" <th>Genre</th>\n",
" <th>Publisher</th>\n",
" <th>NA_Sales</th>\n",
" <th>EU_Sales</th>\n",
" <th>JP_Sales</th>\n",
" <th>Other_Sales</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>Wii Sports</td>\n",
" <td>Wii</td>\n",
" <td>2006</td>\n",
" <td>Sports</td>\n",
" <td>Nintendo</td>\n",
" <td>41.49</td>\n",
" <td>29.02</td>\n",
" <td>3.77</td>\n",
" <td>8.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>Super Mario Bros.</td>\n",
" <td>NES</td>\n",
" <td>1985</td>\n",
" <td>Platform</td>\n",
" <td>Nintendo</td>\n",
" <td>29.08</td>\n",
" <td>3.58</td>\n",
" <td>6.81</td>\n",
" <td>0.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>Mario Kart Wii</td>\n",
" <td>Wii</td>\n",
" <td>2008</td>\n",
" <td>Racing</td>\n",
" <td>Nintendo</td>\n",
" <td>15.85</td>\n",
" <td>12.88</td>\n",
" <td>3.79</td>\n",
" <td>3.31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>Wii Sports Resort</td>\n",
" <td>Wii</td>\n",
" <td>2009</td>\n",
" <td>Sports</td>\n",
" <td>Nintendo</td>\n",
" <td>15.75</td>\n",
" <td>11.01</td>\n",
" <td>3.28</td>\n",
" <td>2.96</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>Pokemon Red/Pokemon Blue</td>\n",
" <td>GB</td>\n",
" <td>1996</td>\n",
" <td>Role-Playing</td>\n",
" <td>Nintendo</td>\n",
" <td>11.27</td>\n",
" <td>8.89</td>\n",
" <td>10.22</td>\n",
" <td>1.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>Tetris</td>\n",
" <td>GB</td>\n",
" <td>1989</td>\n",
" <td>Puzzle</td>\n",
" <td>Nintendo</td>\n",
" <td>23.20</td>\n",
" <td>2.26</td>\n",
" <td>4.22</td>\n",
" <td>0.58</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>7</td>\n",
" <td>New Super Mario Bros.</td>\n",
" <td>DS</td>\n",
" <td>2006</td>\n",
" <td>Platform</td>\n",
" <td>Nintendo</td>\n",
" <td>11.38</td>\n",
" <td>9.23</td>\n",
" <td>6.50</td>\n",
" <td>2.90</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>8</td>\n",
" <td>Wii Play</td>\n",
" <td>Wii</td>\n",
" <td>2006</td>\n",
" <td>Misc</td>\n",
" <td>Nintendo</td>\n",
" <td>14.03</td>\n",
" <td>9.20</td>\n",
" <td>2.93</td>\n",
" <td>2.85</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>9</td>\n",
" <td>New Super Mario Bros. Wii</td>\n",
" <td>Wii</td>\n",
" <td>2009</td>\n",
" <td>Platform</td>\n",
" <td>Nintendo</td>\n",
" <td>14.59</td>\n",
" <td>7.06</td>\n",
" <td>4.70</td>\n",
" <td>2.26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>10</td>\n",
" <td>Duck Hunt</td>\n",
" <td>NES</td>\n",
" <td>1984</td>\n",
" <td>Shooter</td>\n",
" <td>Nintendo</td>\n",
" <td>26.93</td>\n",
" <td>0.63</td>\n",
" <td>0.28</td>\n",
" <td>0.47</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Rank Name Platform Year Genre Publisher \\\n",
"0 1 Wii Sports Wii 2006 Sports Nintendo \n",
"1 2 Super Mario Bros. NES 1985 Platform Nintendo \n",
"2 3 Mario Kart Wii Wii 2008 Racing Nintendo \n",
"3 4 Wii Sports Resort Wii 2009 Sports Nintendo \n",
"4 5 Pokemon Red/Pokemon Blue GB 1996 Role-Playing Nintendo \n",
"5 6 Tetris GB 1989 Puzzle Nintendo \n",
"6 7 New Super Mario Bros. DS 2006 Platform Nintendo \n",
"7 8 Wii Play Wii 2006 Misc Nintendo \n",
"8 9 New Super Mario Bros. Wii Wii 2009 Platform Nintendo \n",
"9 10 Duck Hunt NES 1984 Shooter Nintendo \n",
"\n",
" NA_Sales EU_Sales JP_Sales Other_Sales \n",
"0 41.49 29.02 3.77 8.46 \n",
"1 29.08 3.58 6.81 0.77 \n",
"2 15.85 12.88 3.79 3.31 \n",
"3 15.75 11.01 3.28 2.96 \n",
"4 11.27 8.89 10.22 1.00 \n",
"5 23.20 2.26 4.22 0.58 \n",
"6 11.38 9.23 6.50 2.90 \n",
"7 14.03 9.20 2.93 2.85 \n",
"8 14.59 7.06 4.70 2.26 \n",
"9 26.93 0.63 0.28 0.47 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's see the type of our data, to better understand the structure behind it."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 15979 entries, 0 to 15978\n",
"Data columns (total 10 columns):\n",
"Rank 15979 non-null int64\n",
"Name 15979 non-null object\n",
"Platform 15979 non-null object\n",
"Year 15979 non-null int64\n",
"Genre 15979 non-null object\n",
"Publisher 15945 non-null object\n",
"NA_Sales 15979 non-null float64\n",
"EU_Sales 15979 non-null float64\n",
"JP_Sales 15979 non-null float64\n",
"Other_Sales 15979 non-null float64\n",
"dtypes: float64(4), int64(2), object(4)\n",
"memory usage: 1.2+ MB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's see the informations on the numerical distribution of our dataset."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rank</th>\n",
" <th>Year</th>\n",
" <th>NA_Sales</th>\n",
" <th>EU_Sales</th>\n",
" <th>JP_Sales</th>\n",
" <th>Other_Sales</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>15979.000000</td>\n",
" <td>15979.000000</td>\n",
" <td>15979.00000</td>\n",
" <td>15979.000000</td>\n",
" <td>15979.000000</td>\n",
" <td>15979.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>8224.104262</td>\n",
" <td>2006.197071</td>\n",
" <td>0.26976</td>\n",
" <td>0.149093</td>\n",
" <td>0.079514</td>\n",
" <td>0.048892</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>4775.817280</td>\n",
" <td>5.714810</td>\n",
" <td>0.82956</td>\n",
" <td>0.512557</td>\n",
" <td>0.314536</td>\n",
" <td>0.191612</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000</td>\n",
" <td>1980.000000</td>\n",
" <td>0.00000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>4080.500000</td>\n",
" <td>2003.000000</td>\n",
" <td>0.00000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>8207.000000</td>\n",
" <td>2007.000000</td>\n",
" <td>0.08000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>12332.500000</td>\n",
" <td>2010.000000</td>\n",
" <td>0.24000</td>\n",
" <td>0.110000</td>\n",
" <td>0.040000</td>\n",
" <td>0.040000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>16600.000000</td>\n",
" <td>2015.000000</td>\n",
" <td>41.49000</td>\n",
" <td>29.020000</td>\n",
" <td>10.220000</td>\n",
" <td>10.570000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Rank Year NA_Sales EU_Sales JP_Sales \\\n",
"count 15979.000000 15979.000000 15979.00000 15979.000000 15979.000000 \n",
"mean 8224.104262 2006.197071 0.26976 0.149093 0.079514 \n",
"std 4775.817280 5.714810 0.82956 0.512557 0.314536 \n",
"min 1.000000 1980.000000 0.00000 0.000000 0.000000 \n",
"25% 4080.500000 2003.000000 0.00000 0.000000 0.000000 \n",
"50% 8207.000000 2007.000000 0.08000 0.020000 0.000000 \n",
"75% 12332.500000 2010.000000 0.24000 0.110000 0.040000 \n",
"max 16600.000000 2015.000000 41.49000 29.020000 10.220000 \n",
"\n",
" Other_Sales \n",
"count 15979.000000 \n",
"mean 0.048892 \n",
"std 0.191612 \n",
"min 0.000000 \n",
"25% 0.000000 \n",
"50% 0.010000 \n",
"75% 0.040000 \n",
"max 10.570000 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's see the informations on the categorical distribution of our dataset."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
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" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rank</th>\n",
" <th>Name</th>\n",
" <th>Platform</th>\n",
" <th>Year</th>\n",
" <th>Genre</th>\n",
" <th>Publisher</th>\n",
" <th>NA_Sales</th>\n",
" <th>EU_Sales</th>\n",
" <th>JP_Sales</th>\n",
" <th>Other_Sales</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>15979.000000</td>\n",
" <td>15979</td>\n",
" <td>15979</td>\n",
" <td>15979.000000</td>\n",
" <td>15979</td>\n",
" <td>15945</td>\n",
" <td>15979.00000</td>\n",
" <td>15979.000000</td>\n",
" <td>15979.000000</td>\n",
" <td>15979.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
" <td>NaN</td>\n",
" <td>11163</td>\n",
" <td>31</td>\n",
" <td>NaN</td>\n",
" <td>12</td>\n",
" <td>564</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>top</th>\n",
" <td>NaN</td>\n",
" <td>Need for Speed: Most Wanted</td>\n",
" <td>DS</td>\n",
" <td>NaN</td>\n",
" <td>Action</td>\n",
" <td>Electronic Arts</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freq</th>\n",
" <td>NaN</td>\n",
" <td>12</td>\n",
" <td>2132</td>\n",
" <td>NaN</td>\n",
" <td>3133</td>\n",
" <td>1319</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>8224.104262</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2006.197071</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.26976</td>\n",
" <td>0.149093</td>\n",
" <td>0.079514</td>\n",
" <td>0.048892</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>4775.817280</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>5.714810</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.82956</td>\n",
" <td>0.512557</td>\n",
" <td>0.314536</td>\n",
" <td>0.191612</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1980.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.00000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>4080.500000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2003.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.00000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>8207.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2007.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.08000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>12332.500000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2010.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.24000</td>\n",
" <td>0.110000</td>\n",
" <td>0.040000</td>\n",
" <td>0.040000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>16600.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2015.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>41.49000</td>\n",
" <td>29.020000</td>\n",
" <td>10.220000</td>\n",
" <td>10.570000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Rank Name Platform Year \\\n",
"count 15979.000000 15979 15979 15979.000000 \n",
"unique NaN 11163 31 NaN \n",
"top NaN Need for Speed: Most Wanted DS NaN \n",
"freq NaN 12 2132 NaN \n",
"mean 8224.104262 NaN NaN 2006.197071 \n",
"std 4775.817280 NaN NaN 5.714810 \n",
"min 1.000000 NaN NaN 1980.000000 \n",
"25% 4080.500000 NaN NaN 2003.000000 \n",
"50% 8207.000000 NaN NaN 2007.000000 \n",
"75% 12332.500000 NaN NaN 2010.000000 \n",
"max 16600.000000 NaN NaN 2015.000000 \n",
"\n",
" Genre Publisher NA_Sales EU_Sales JP_Sales \\\n",
"count 15979 15945 15979.00000 15979.000000 15979.000000 \n",
"unique 12 564 NaN NaN NaN \n",
"top Action Electronic Arts NaN NaN NaN \n",
"freq 3133 1319 NaN NaN NaN \n",
"mean NaN NaN 0.26976 0.149093 0.079514 \n",
"std NaN NaN 0.82956 0.512557 0.314536 \n",
"min NaN NaN 0.00000 0.000000 0.000000 \n",
"25% NaN NaN 0.00000 0.000000 0.000000 \n",
"50% NaN NaN 0.08000 0.020000 0.000000 \n",
"75% NaN NaN 0.24000 0.110000 0.040000 \n",
"max NaN NaN 41.49000 29.020000 10.220000 \n",
"\n",
" Other_Sales \n",
"count 15979.000000 \n",
"unique NaN \n",
"top NaN \n",
"freq NaN \n",
"mean 0.048892 \n",
"std 0.191612 \n",
"min 0.000000 \n",
"25% 0.000000 \n",
"50% 0.010000 \n",
"75% 0.040000 \n",
"max 10.570000 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe(include = 'all') # include also non-numerical columns"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"def category_describe(data, col) :\n",
" print(data[col].value_counts())\n",
" print(data[col].value_counts().describe())"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DS 2132\n",
"PS2 2127\n",
"Wii 1290\n",
"PS3 1272\n",
"X360 1227\n",
"PSP 1197\n",
"PS 1189\n",
"PC 905\n",
"GBA 811\n",
"XB 803\n",
"GC 542\n",
"3DS 465\n",
"PSV 350\n",
"N64 316\n",
"SNES 239\n",
"PS4 228\n",
"SAT 173\n",
"XOne 159\n",
"WiiU 133\n",
"2600 116\n",
"NES 98\n",
"GB 97\n",
"DC 52\n",
"GEN 27\n",
"NG 12\n",
"WS 6\n",
"SCD 6\n",
"3DO 3\n",
"TG16 2\n",
"GG 1\n",
"PCFX 1\n",
"Name: Platform, dtype: int64\n",
"count 31.000000\n",
"mean 515.451613\n",
"std 620.197057\n",
"min 1.000000\n",
"25% 39.500000\n",
"50% 228.000000\n",
"75% 858.000000\n",
"max 2132.000000\n",
"Name: Platform, dtype: float64\n"
]
}
],
"source": [
"category_describe(df, 'Platform')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Action 3133\n",
"Sports 2266\n",
"Misc 1692\n",
"Role-Playing 1429\n",
"Shooter 1250\n",
"Adventure 1242\n",
"Racing 1206\n",
"Platform 866\n",
"Simulation 841\n",
"Fighting 822\n",
"Strategy 661\n",
"Puzzle 571\n",
"Name: Genre, dtype: int64\n",
"count 12.000000\n",
"mean 1331.583333\n",
"std 740.599445\n",
"min 571.000000\n",
"25% 836.250000\n",
"50% 1224.000000\n",
"75% 1494.750000\n",
"max 3133.000000\n",
"Name: Genre, dtype: float64\n"
]
}
],
"source": [
"category_describe(df, 'Genre')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Electronic Arts 1319\n",
"Activision 952\n",
"Ubisoft 904\n",
"Namco Bandai Games 888\n",
"Konami Digital Entertainment 815\n",
"THQ 712\n",
"Nintendo 686\n",
"Sony Computer Entertainment 677\n",
"Sega 622\n",
"Take-Two Interactive 400\n",
"Capcom 358\n",
"Atari 346\n",
"Tecmo Koei 321\n",
"Disney Interactive Studios 214\n",
"Square Enix 211\n",
"Warner Bros. Interactive Entertainment 203\n",
"Eidos Interactive 196\n",
"Midway Games 196\n",
"Microsoft Game Studios 185\n",
"505 Games 185\n",
"Acclaim Entertainment 184\n",
"D3Publisher 180\n",
"Vivendi Games 161\n",
"Codemasters 144\n",
"Idea Factory 120\n",
"Deep Silver 110\n",
"Zoo Digital Publishing 104\n",
"Unknown 96\n",
"Nippon Ichi Software 92\n",
"Majesco Entertainment 90\n",
" ... \n",
"KSS 1\n",
"Team17 Software 1\n",
"Tetris Online 1\n",
"DreamWorks Interactive 1\n",
"Starpath Corp. 1\n",
"Evolution Games 1\n",
"CokeM Interactive 1\n",
"Paon Corporation 1\n",
"Just Flight 1\n",
"DigiCube 1\n",
"Genterprise 1\n",
"Xing Entertainment 1\n",
"Universal Gamex 1\n",
"Fortyfive 1\n",
"Intergrow 1\n",
"Mystique 1\n",
"Wargaming.net 1\n",
"Pony Canyon 1\n",
"King Records 1\n",
"Commseed 1\n",
"T&E Soft 1\n",
"Warp 1\n",
"NDA Productions 1\n",
"On Demand 1\n",
"PM Studios 1\n",
"Origin Systems 1\n",
"Mirai Shounen 1\n",
"2D Boy 1\n",
"EON Digital Entertainment 1\n",
"Yumedia 1\n",
"Name: Publisher, Length: 564, dtype: int64\n",
"count 564.000000\n",
"mean 28.271277\n",
"std 114.470187\n",
"min 1.000000\n",
"25% 1.000000\n",
"50% 3.000000\n",
"75% 11.000000\n",
"max 1319.000000\n",
"Name: Publisher, dtype: float64\n"
]
}
],
"source": [
"category_describe(df, 'Publisher')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's find out which columns has Nan values."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Are there missing values? True\n"
]
},
{
"data": {
"text/plain": [
"Rank 0\n",
"Name 0\n",
"Platform 0\n",
"Year 0\n",
"Genre 0\n",
"Publisher 34\n",
"NA_Sales 0\n",
"EU_Sales 0\n",
"JP_Sales 0\n",
"Other_Sales 0\n",
"dtype: int64"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# checking for missing values\n",
"print(\"Are there missing values? {}\".format(df.isnull().any().any()))\n",
"\n",
"df.isnull().sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's try to know more about the games with unidentified Publisher"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rank</th>\n",
" <th>Name</th>\n",
" <th>Platform</th>\n",
" <th>Year</th>\n",
" <th>Genre</th>\n",
" <th>Publisher</th>\n",
" <th>NA_Sales</th>\n",
" <th>EU_Sales</th>\n",
" <th>JP_Sales</th>\n",
" <th>Other_Sales</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1632</th>\n",
" <td>1664</td>\n",
" <td>Shrek / Shrek 2 2-in-1 Gameboy Advance Video</td>\n",
" <td>GBA</td>\n",
" <td>2007</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.87</td>\n",
" <td>0.32</td>\n",
" <td>0.0</td>\n",
" <td>0.02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2178</th>\n",
" <td>2224</td>\n",
" <td>Bentley's Hackpack</td>\n",
" <td>GBA</td>\n",
" <td>2005</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.67</td>\n",
" <td>0.25</td>\n",
" <td>0.0</td>\n",
" <td>0.02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3090</th>\n",
" <td>3161</td>\n",
" <td>Nicktoons Collection: Game Boy Advance Video V...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.46</td>\n",
" <td>0.17</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3097</th>\n",
" <td>3168</td>\n",
" <td>SpongeBob SquarePants: Game Boy Advance Video ...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.46</td>\n",
" <td>0.17</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3685</th>\n",
" <td>3768</td>\n",
" <td>SpongeBob SquarePants: Game Boy Advance Video ...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.38</td>\n",
" <td>0.14</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4428</th>\n",
" <td>4528</td>\n",
" <td>The Fairly Odd Parents: Game Boy Advance Video...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.31</td>\n",
" <td>0.11</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4536</th>\n",
" <td>4637</td>\n",
" <td>The Fairly Odd Parents: Game Boy Advance Video...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.30</td>\n",
" <td>0.11</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5516</th>\n",
" <td>5649</td>\n",
" <td>Cartoon Network Collection: Game Boy Advance V...</td>\n",
" <td>GBA</td>\n",
" <td>2005</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.23</td>\n",
" <td>0.08</td>\n",
" <td>0.0</td>\n",
" <td>0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6272</th>\n",
" <td>6439</td>\n",
" <td>Sonic X: Game Boy Advance Video Volume 1</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.19</td>\n",
" <td>0.07</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6396</th>\n",
" <td>6564</td>\n",
" <td>Dora the Explorer: Game Boy Advance Video Volu...</td>\n",
" <td>GBA</td>\n",
" <td>2004</td>\n",
" <td>Misc</td>\n",
" <td>NaN</td>\n",
" <td>0.18</td>\n",
" <td>0.07</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Rank Name Platform Year \\\n",
"1632 1664 Shrek / Shrek 2 2-in-1 Gameboy Advance Video GBA 2007 \n",
"2178 2224 Bentley's Hackpack GBA 2005 \n",
"3090 3161 Nicktoons Collection: Game Boy Advance Video V... GBA 2004 \n",
"3097 3168 SpongeBob SquarePants: Game Boy Advance Video ... GBA 2004 \n",
"3685 3768 SpongeBob SquarePants: Game Boy Advance Video ... GBA 2004 \n",
"4428 4528 The Fairly Odd Parents: Game Boy Advance Video... GBA 2004 \n",
"4536 4637 The Fairly Odd Parents: Game Boy Advance Video... GBA 2004 \n",
"5516 5649 Cartoon Network Collection: Game Boy Advance V... GBA 2005 \n",
"6272 6439 Sonic X: Game Boy Advance Video Volume 1 GBA 2004 \n",
"6396 6564 Dora the Explorer: Game Boy Advance Video Volu... GBA 2004 \n",
"\n",
" Genre Publisher NA_Sales EU_Sales JP_Sales Other_Sales \n",
"1632 Misc NaN 0.87 0.32 0.0 0.02 \n",
"2178 Misc NaN 0.67 0.25 0.0 0.02 \n",
"3090 Misc NaN 0.46 0.17 0.0 0.01 \n",
"3097 Misc NaN 0.46 0.17 0.0 0.01 \n",
"3685 Misc NaN 0.38 0.14 0.0 0.01 \n",
"4428 Misc NaN 0.31 0.11 0.0 0.01 \n",
"4536 Misc NaN 0.30 0.11 0.0 0.01 \n",
"5516 Misc NaN 0.23 0.08 0.0 0.01 \n",
"6272 Misc NaN 0.19 0.07 0.0 0.00 \n",
"6396 Misc NaN 0.18 0.07 0.0 0.00 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Let's affect this specific dataframe, as we will use it several times\n",
"publisher_null_df = df[df['Publisher'].isnull()]\n",
"publisher_null_df.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rank</th>\n",
" <th>Year</th>\n",
" <th>NA_Sales</th>\n",
" <th>EU_Sales</th>\n",
" <th>JP_Sales</th>\n",
" <th>Other_Sales</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>34.000000</td>\n",
" <td>34.000000</td>\n",
" <td>34.000000</td>\n",
" <td>34.000000</td>\n",
" <td>34.0</td>\n",
" <td>34.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>9117.911765</td>\n",
" <td>2006.264706</td>\n",
" <td>0.170000</td>\n",
" <td>0.071471</td>\n",
" <td>0.0</td>\n",
" <td>0.002941</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>4554.649242</td>\n",
" <td>3.422818</td>\n",
" <td>0.199909</td>\n",
" <td>0.071314</td>\n",
" <td>0.0</td>\n",
" <td>0.005789</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1664.000000</td>\n",
" <td>2004.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>6470.250000</td>\n",
" <td>2004.000000</td>\n",
" <td>0.015000</td>\n",
" <td>0.022500</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>8356.500000</td>\n",
" <td>2004.000000</td>\n",
" <td>0.120000</td>\n",
" <td>0.050000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>13617.500000</td>\n",
" <td>2009.250000</td>\n",
" <td>0.187500</td>\n",
" <td>0.095000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>16556.000000</td>\n",
" <td>2014.000000</td>\n",
" <td>0.870000</td>\n",
" <td>0.320000</td>\n",
" <td>0.0</td>\n",
" <td>0.020000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Rank Year NA_Sales EU_Sales JP_Sales Other_Sales\n",
"count 34.000000 34.000000 34.000000 34.000000 34.0 34.000000\n",
"mean 9117.911765 2006.264706 0.170000 0.071471 0.0 0.002941\n",
"std 4554.649242 3.422818 0.199909 0.071314 0.0 0.005789\n",
"min 1664.000000 2004.000000 0.000000 0.000000 0.0 0.000000\n",
"25% 6470.250000 2004.000000 0.015000 0.022500 0.0 0.000000\n",
"50% 8356.500000 2004.000000 0.120000 0.050000 0.0 0.000000\n",
"75% 13617.500000 2009.250000 0.187500 0.095000 0.0 0.000000\n",
"max 16556.000000 2014.000000 0.870000 0.320000 0.0 0.020000"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"publisher_null_df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's drop the null values. As there is not much of them (34 for 15979 in total), it won't make much of a difference."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"df = df.dropna()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. How have the total sales of console games been declining over the years by different genres?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Create the total sales of console games feature**"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"df['Total_Sales'] = df['NA_Sales'] + df['EU_Sales'] + df['JP_Sales'] + df['Other_Sales']"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db753b70>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# See 'Explore Happiness Data Using Python Pivot Tables': https://www.dataquest.io/blog/pandas-pivot-table/\n",
"\n",
"df_pivot_table = df.pivot_table(values = 'Total_Sales', index = 'Year', columns = 'Genre', aggfunc = 'sum')\n",
"df_pivot_table.plot(kind = 'area', figsize = (12, 6))\n",
"plt.title('Total sales over the years')\n",
"plt.ylabel('Total sales')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Observation** \n",
"Console games sales have been rapidly declining since 2008. Possibly, this could be attributed to the rising popularity of mobile devices and associated games."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. How do different platforms compare side-by-side in terms of aggregate global sales since their inceptions? Who is the leader? "
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db5b1908>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_pivot_table = df.pivot_table(values = 'Total_Sales', index = 'Platform', aggfunc = 'sum').sort_values('Total_Sales')\n",
"df_pivot_table = df_pivot_table[df_pivot_table['Total_Sales'] > 5] # filter out platforms with smaller total sales\n",
"df_pivot_table.plot(kind = 'barh', legend = None, figsize = (12, 12))\n",
"plt.xlabel('Total sales')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Observation** \n",
"The all-time leader in the Global Games Sales among platforms is PS2 making $1.2B+"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. How do different publishers compare side-by-side in terms of aggregate global sales since their inceptions? Who is the leader? "
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db477b00>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_pivot_table = df.pivot_table(values = 'Total_Sales', index = 'Publisher', aggfunc = 'sum').sort_values('Total_Sales', ascending = False)\n",
"df_pivot_table = df_pivot_table[df_pivot_table['Total_Sales'] > 100] # filter out publishers with smaller total sales\n",
"df_pivot_table.plot(kind = 'bar', legend = None, figsize = (12, 6))\n",
"plt.ylabel('Total sales')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db381e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# See: https://github.com/laserson/squarify\n",
"import squarify\n",
"\n",
"# create a color palette, mapped to Total_Sales\n",
"total_sales = df_pivot_table['Total_Sales'].tolist()\n",
"cmap = matplotlib.cm.Reds\n",
"mini=min(total_sales)\n",
"maxi=max(total_sales)\n",
"norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)\n",
"colors = [cmap(norm(value)) for value in total_sales]\n",
"\n",
"max_label_size = 15\n",
"labels = df_pivot_table.index.tolist()\n",
"labels = [(label[:max_label_size] + '..') if len(label) > max_label_size else label for label in labels]\n",
"labels = [label + '\\n' + '${:,.0f} M'.format(total_sales[idx]) for idx, label in enumerate(labels)]\n",
"\n",
"plt.figure(figsize=(20, 10))\n",
"squarify.plot(sizes = total_sales, label = labels, alpha=.8, color=colors)\n",
"plt.axis('off')\n",
"plt.rc('font', size=16)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Observation** \n",
"In terms of publishers, Nintendo is the leader in Global Games Sales in $1.7B+ terms, however EA, Activision and Sony are leading in quantity of game titles."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. How do the New Generation (New Gen) consoles compare in terms of total global sales for combined 2014 and 2015?\n",
"\n",
"New Gen platforms in this dataset are **PS4**, **XOne** and **WiiU**."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"df_year_filter = df['Year'].between(2014, 2015, inclusive = True)\n",
"df_platform_filter = df['Platform'].isin(['PS4', 'XOne', 'WiiU'])\n",
"df_pivot_table = df[df_year_filter & df_platform_filter].pivot_table('Total_Sales', index = 'Platform', aggfunc = 'sum')\n"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db4cb358>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_pivot_table.plot(y = 'Total_Sales', labels = df_pivot_table.index, kind = 'pie',\n",
" autopct = '%1.1f%%', startangle = 90, legend = False, fontsize = 14, figsize = (12, 12))\n",
"plt.axis('off')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Observation** \n",
"The Global Games Sales leader among new Gen consoles is PS4 accounting for more than half of the sales of all three platforms."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. What are the top 10 game titles with the highest global sales?"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa4db1f06d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_pivot_table = df.pivot_table(values = 'Total_Sales', index = 'Name', aggfunc = 'sum').sort_values('Total_Sales', ascending = False)\n",
"df_pivot_table = df_pivot_table.head(10) # filter out 10 top game titles\n",
"\n",
"# create a color palette, mapped to Publisher\n",
"#\n",
"# unique_games = df.drop_duplicates('Name')[['Name', 'Publisher']].set_index('Name')\n",
"# df_pivot_table['Publisher'] = df_pivot_table.index.map(lambda game: unique_games.loc[game]['Publisher'])\n",
"# unique_publisher = df_pivot_table.drop_duplicates('Publisher')['Publisher'].tolist()\n",
"# cmap = matplotlib.cm.tab20c\n",
"# mini=0\n",
"# maxi=len(unique_publisher)\n",
"# norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)\n",
"# colors = [cmap(norm(unique_publisher.index(game[1]))) for game in df_pivot_table.values]\n",
"#\n",
"# df_pivot_table.plot(kind = 'bar', legend = None, color = colors, figsize = (12, 6))\n",
"\n",
"df_pivot_table.plot(kind = 'bar', legend = None, color = 'darkred', figsize = (12, 6))\n",
"plt.xlabel('Game title')\n",
"plt.ylabel('Total sales')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Observation** \n",
"Top 10 game titles in terms of all-time Global Games Sales."
]
}
],
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