text_html_output_1.png
import matplotlib.pyplot as plt

import os

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

import seaborn as sns

import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.ticker as ticker
sns.set(rc={'figure.figsize': (11.7, 8.27)})
from sklearn.neighbors import KNeighborsClassifier
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        file = os.path.join(dirname, filename)

data = pd.read_csv(file)

data.columns

data.shape

data_pie = [73452, 56428]
labels = ['1', '0']
explode = [0.1, 0]

fig, ax = plt.subplots(1, 2)
sns.histplot(x='Gender', data=data, stat='density', shrink=0.9, color='steelblue', ax=ax[0])
sns.histplot(x='Customer Type', data=data, stat='density', shrink=0.9, color='steelblue', ax=ax[1])
fig.show()