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#%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set(style="darkgrid")
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data = pd.read_csv('./input/Video_Games_Sales_as_at_30_Nov_2016.csv')
data.head()
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fig = plt.figure()
ax1 = fig.add_subplot(411)
idx = 0
hcat1 = sorted(data.Platform.unique())
for cat_val in hcat1:
ax1.bar(idx,data[data['Platform']==cat_val].Global_Sales.sum(), color=np.random.rand(3,1))
idx = idx + 1
ax2 = fig.add_subplot(412)
idx = 0
hcat2 = sorted(data.Year_of_Release.unique())
for cat_val in hcat2:
ax2.bar(idx,data[data['Year_of_Release']==cat_val].Global_Sales.sum(), color=np.random.rand(3,1))
idx = idx + 1
ax3 = fig.add_subplot(413)
idx = 0
hcat3 = sorted(data.Genre.unique())
for cat_val in hcat3:
ax3.bar(idx,data[data['Genre']==cat_val].Global_Sales.sum(), color=np.random.rand(3,1))
idx = idx + 1
ax4 = fig.add_subplot(414)
idx = 0
hcat4 = sorted(data['Rating'].dropna().unique())
for cat_val in hcat4:
ax4.bar(idx,data[data['Rating']==cat_val].Global_Sales.sum(), color=np.random.rand(3,1))
idx = idx + 1
ax1.set_title('Global Sales by Platform')
ax2.set_title('Global Sales by Year')
ax3.set_title('Global Sales by Genre')
ax4.set_title('Global Sales by Rating')
ax1.set_xticklabels(hcat1)
ax2.set_xticklabels(hcat2)
ax3.set_xticklabels(hcat3)
ax4.set_xticklabels(hcat4)
fig.subplots_adjust(hspace=1)
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#data['User_Score'].dropna()
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