text_plain_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

train = pd.read_csv('../input/breast-cancer-detection/train.csv')
test = pd.read_csv('../input/breast-cancer-detection/test.csv')

train.columns = ['_'.join(col.split(' ')).lower() for col in train.columns]
test.columns = ['_'.join(col.split(' ')).lower() for col in test.columns]

a = train.columns
b = test.columns

train = train.drop('unnamed:_32', axis=1)
test = test.drop('unnamed:_32', axis=1)

a = train.isnull().sum()
b = test.isnull().sum()

corr = train.corr()
fig, ax = plt.subplots(figsize=(7, 7))
sns.heatmap(corr, xticklabels=corr.columns.values, yticklabels=corr.columns.values)