text_plain_output_1.png
import pandas as pd

train = pd.read_csv('/kaggle/input/e-commerce-shoppers-behaviour-understanding/train_data_v2.csv')
test = pd.read_csv('/kaggle/input/e-commerce-shoppers-behaviour-understanding/test_data_v2.csv')

train.shape

train.columns

train.isna().sum()

var = train.corr()

target = train['Made_Purchase']
features = train.drop('Made_Purchase', axis=1)

col_float = []
col_str = []
for i in features.columns:
    if features[i].dtype == 'float64':
        col_float.append(i)
    else:
        col_str.append(i)
print('String columns names : \n', col_str)
print()
print('Float columns names : \n', col_float)