import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler

data = pd.read_csv('../input/churn-predictions-personal/Churn_Predictions.csv')
data.head()

# X = data.iloc[:, 3:13]
# y = data.iloc[:, 13]
X = data.drop(['RowNumber','CustomerId','Surname','Exited'], axis=1)
y = data['Exited']

geo = pd.get_dummies(X['Geography'])
gen = pd.get_dummies(X['Gender'])

X = pd.concat([X, geo, gen], axis=1)