import matplotlib.pyplot as plt

import seaborn as sns

import pandas as pd

import numpy as np

ads = pd.read_csv("Ads.csv")

ads.head(5)

plt.scatter(ads['Age'],ads['EstimatedSalary'])

plt.xlabel('Age')

plt.ylabel('EstimatedSalary')

plt.title('Scatter plot between Age vs Estimated Salary')

sns.set_style('whitegrid')

sns.FacetGrid(ads,hue='Purchased',height=7).map(plt.scatter,'Age','EstimatedSalary').add_legend()

plt.show()

ads.drop(columns=['User ID'],inplace=True)

sns.set_style('whitegrid')

sns.pairplot(ads,hue='Purchased',height=5)

plt.show()

sns.boxplot(x='Purchased',y='EstimatedSalary',data=ads)

sns.jointplot(x='Age',y='EstimatedSalary',data=ads)

sns.regplot(x='Age',y='EstimatedSalary',data=ads,fit_reg=True,order =6)

sns.lmplot(x='Age',y='EstimatedSalary',data=ads,hue='Purchased')

sns.clustermap(ads.corr(),figsize=(7,7),annot=True)

plt.show()

sns.heatmap(ads.corr(),annot =True,cbar_kws={'orientation':'horizontal'})

plt.show()

ads.isnull().sum()

ads.info()

ads.describe()