Import data for L1 Regularization in TensorFlow

tf_l1_reg_imports.py

import pandas as pd
import numpy as np
import tensorflow as tf

from sklearn.model_selection import train_test_split

#load training data
train_df = pd.read_csv('train.csv', index_col='ID')

#split into features and target
X = train_df.drop('medv', axis=1)
y = train_df['medv']

#engineer new features
X['crim_2'] = X['crim'] ** 2
X['zn_2'] = X['zn'] ** 2
X['indus_2'] = X['indus'] ** 2
X['chas_2'] = X['chas'] ** 2
X['nox_2'] = X['nox'] ** 2
X['rm_2'] = X['rm'] ** 2
X['age_2'] = X['age'] ** 2
X['dis_2'] = X['dis'] ** 2
X['rad_2'] = X['rad'] ** 2
X['tax_2'] = X['tax'] ** 2
X['ptratio_2'] = X['ptratio'] ** 2
X['black_2'] = X['black'] ** 2
X['lstat_2'] = X['lstat'] ** 2

#split into training and validation
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42, test_size=0.3)