missing value function

missing_value_function.py

def missing_values_table(df):
    # Total missing values
    mis_val = df.isnull().sum()

    # Percentage of missing values
    mis_val_percent = 100 * df.isnull().sum() / len(df)

    # Make a table with the results
    mis_val_table = pd.concat([mis_val, mis_val_percent],
                              axis=1)

    # Rename the columns
    mis_val_table_ren_columns = mis_val_table.rename(
        columns={0: 'Missing Values', 1: '% of Total Values'})

    # Sort the table by percentage of missing descending
    mis_val_table_ren_columns = (mis_val_table_ren_columns[
        mis_val_table_ren_columns.iloc[:, 1] != 0].sort_values(
        '% of Total Values', ascending=False).round(1))

    # Print some summary information
    print("Your selected dataframe has " + str(df.shape[1]) + " columns.\n"
          "There are " + str(mis_val_table_ren_columns.shape[0]) +
          " columns that have missing values.")

    # Return the dataframe with missing information
    return mis_val_table_ren_columns