text_plain_output_1.png
from sklearn.preprocessing import StandardScaler

import matplotlib.pyplot as plt

import pandas as pd

dataset = pd.read_csv('../input/Mall_Customers.csv')
pd.set_option('display.max_columns', 10)

scaler = StandardScaler()
df = pd.DataFrame(scaler.fit_transform(dataset[['Age', 'Annual Income (k$)', 'Spending Score (1-100)']]))
df.columns = ['age', 'income', 'spending']
df.insert(0, 'gender', dataset['Gender_code'])

plot_gender = sns.distplot(df['gender'], label='gender', color='grey')
plot_age = sns.distplot(df['age'], label='age', color='blue')
plot_income = sns.distplot(df['income'], label='income', color='lightgreen')
plot_spend = sns.distplot(df['spending'], label='spend', color='orange')
plt.xlabel('')
plt.legend()
plt.show()