text_plain_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

dftrain = pd.read_csv('../input/tabular-playground-series-aug-2022/train.csv')

dftest = pd.read_csv('../input/tabular-playground-series-aug-2022/test.csv')

dftotal = dftrain.append(dftest)

dftotal.reset_index(inplace=True)

dftotal.columns

dftotal.isnull().sum()

dftotal.isnull().sum()

dftotal = dftotal[dftotal['loading'].notna()]

f = plt.figure(figsize=(20, 10))
sns.heatmap(dftotal.corr());

corrtable = dftotal.corr()

irow, icol = corrtable.shape
for row in range(0, irow):
    for col in range(0, icol):
        corval = corrtable.iloc[row, col]
        if corval > 0.4:
            if corrtable.index[row] != corrtable.columns[col]:
                print('correlation with {} and {} is {}'.format(corrtable.index[row], corrtable.columns[col], corrtable.iloc[row, col]))