train-test split for example churn analysis

churn_tts.py

## Read in dataset from csv file
model_data = pd.read_csv('Data/model_data.csv')

## Define target variable
target = 'Churn'

## Separate features (X) and target (y) for train-test split
X = model_data.drop(columns=[target], axis=1).copy()
y = model_data[target].copy()

## Define random seed to use for train-test-split and 
 ## classifiers for reproducibility
random_seed = 319

## Split the data into training and test sets prior to preprocessing
X_train, X_test, y_train, y_test = train_test_split(X, y,
                                                    test_size=0.25,
                                                    random_state=random_seed)