text_plain_output_1.png
import matplotlib.pyplot as plt

import os

import pandas as pd

import seaborn as sns

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style='ticks')
sns.set_context('paper')
import plotly
import plotly.plotly as py
import plotly.graph_objs as go
import os

df = pd.read_csv('../input/googleplaystore.csv')

df = df[df['Category'] != '1.9']

c2 = df['Category'].value_counts(dropna=True, sort=True, normalize=True).plot.bar()
plt.title('Frequency of App Categories')

ax = sns.boxplot(x="Rating", y="Content Rating", data=df)
plt.xlabel('Rating counts from 0 to 5')

df['Price'] = df[df.columns[7]].replace('[\\$,]', '', regex=True).astype(float)

df_price = df[df['Price'] <= 50]

sns.regplot(x='Price', y='Rating', fit_reg=True, data=df_price)
plt.xlabel('Price')
plt.ylabel('Rating')
plt.title('The relationship between app price and rating from $0 to $50')