text_plain_output_1.png
from sklearn.preprocessing import LabelEncoder

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)

target.value_counts()

from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
new_target = le.fit_transform(target)
new_target