text_plain_output_1.png
import matplotlib.pyplot as plt

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

playstore = pd.read_csv('/kaggle/input/google-play-store-apps/googleplaystore.csv')

playstore.isnull().sum()

playstore.loc[playstore['Reviews'] == '3.0M', 'Reviews'] = 3000000
playstore.loc[playstore['Size'] == 'Varies with device', 'Size'] = '-1M'
playstore.loc[playstore['Size'] == '1,000+', 'Size'] = '-1M'
playstore.loc[:, 'Size'] = playstore.loc[:, 'Size'].apply(lambda x: float(x[:-1]) * 1000 if x[-1] == 'M' else float(x[:-1]))

def drawBarChart(df, col):
    tmp = df.reset_index()
    tmp = tmp.groupby(col).index.count()

playstore.groupby('Category')['App'].count().plot(kind = 'bar', figsize = (15, 7))
_ = plt.title('Number of app with different category')

sns.kdeplot(playstore.groupby('App').agg({'Rating':'mean'})['Rating'], shade = True)
_ = plt.xlim(0,5)
_ = plt.title('rating distribution for all available app')

playstore.loc[playstore['Reviews'] == '3.0M', 'Reviews'] = 3000000
playstore['Reviews'] = playstore['Reviews'].astype('int64')
tmp = playstore.groupby('Category').agg({'Reviews': 'sum'})
tmp.plot(kind='bar', figsize=(15, 7))
_ = plt.title('number of user reviws for cagetory')