application_vnd.jupyter.stderr_output_2.png text_plain_output_4.png text_plain_output_3.png text_plain_output_1.png
import matplotlib.pyplot as plt

import numpy as np

import numpy as np # linear algebra

import pandas as pd

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

import seaborn as sns

data = pd.read_csv('/kaggle/input/playground-series-s3e7/train.csv')

corrmat = data.corr()
cols = corrmat.nlargest(20, 'booking_status')['booking_status'].index
cm = np.corrcoef(data[cols].values.T)
fig = plt.gcf()
fig.set_size_inches(10, 8)
hm = sns.heatmap(cm, cbar=True, annot=True, square=True, fmt='.2f', annot_kws={'size': 10}, yticklabels=cols.values, xticklabels=cols.values)