y_column = "churn"
X_columns = df_X_train.columns

data_plot = df_X_train.copy()
data_plot[y_column] = y_train

plt.figure(figsize=(15, 30))

for i_col in range(len(X_columns)):

    # Create subplot for each column
    plt.subplot(7, 3, i_col+1)

    # Get column and label values
    x_col = data_plot[X_columns[i_col]].values
    y_col = data_plot[y_column].values

    # Plot histograms
    bins = np.linspace(0, x_col.max(), 21)
    plt.hist(x_col[y_col == 0], bins=bins, color='r', alpha=0.5, label='0')
    plt.hist(x_col[y_col == 1], bins=bins, color='b', alpha=0.5, label='1')

    # Labels and legend
    plt.xlabel(X_columns[i_col])
    plt.ylabel('Counts')
    plt.legend(loc='best')

plt.show()