# import modules
import matplotlib.pyplot as mp
import pandas as pd
import seaborn as sb
# import file with data
data = pd.read_csv("C:UsersVanshiDesktopestsellers.csv")
# prints data that will be plotted
# columns shown here are selected by corr() since
# they are ideal for the plot
print(data.corr())
# plotting correlation heatmap
dataplot = sb.heatmap(data.corr(), cmap="YlGnBu", annot=True)
# displaying heatmap
mp.show()
x = data_1_numeric.drop(['log_Kilometer_per_liter','Kilometer_per_liter'],axis = 1)
fig , ax = plt.subplots(figsize = (16,13))
sns.heatmap(x.corr(),annot=True,center = 0 , cmap ='PuRd_r')
plt.show()