There is a df_new Pandas dataframe: id route operator group_name district injury_result incident_type victim_category victim_age 2 3.0 1 London General Go-Ahead Southwark NaN Onboard Injuries 7 10 3 4.0 4 Metroline Metroline Islington NaN Onboard Injuries 7 2 4 5.0 5 East London Stagecoach Havering NaN Onboard Injuries 7 8 5 6.0 5 East London Stagecoach None London Borough NaN Onboard Injuries 7 8 Count which routes had the most incidents_type. Sort them in descending order by incident_type column

def get_most_incidents_route(df):
    # count incident_type by the route
    df_count = df.groupby('route').count()
    # sort the df_count by incident_type and get the first row
    df_count.sort_values(by='incident_type', inplace=True, ascending=False)
    return df_count.iloc[0]

get_most_incidents_route(df_tfl)