def check_processed_data(df,col_list,na_action):
    """ Checks if provided dataframe consists of required columns and no missing values
    """
    check_passed = True

    # Check columns
    df_cols = df.columns
    if set(df_cols) != set(col_list):
        check_passed = False
        print('Column names mismatched')

    # Check missing values
    n_missing = df.isnull().sum().sum()
    if n_missing > 0:
        print('Data contains missing {} values'.format(n_missing))
        if na_action == 'drop':
            print('Dropping rows with missing values')
        elif na_action == 'ignore':
            print('Keeping missing values as it is')
        else:
            print('Not adding this data into master dataframe')
            check_passed = False

    return check_passed