def hourly_frequencies(gtfs, st, et, route_type):
timeframe = et-st<EOL>hours = timeframe/ <NUM_LIT><EOL>day = gtfs.get_suitable_date_for_daily_extract()<EOL>stops = gtfs.get_stops_for_route_type(route_type).T.drop_duplicates().T<EOL>query = ("<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>".format(h=hours, st=st, et=et, day=day))<EOL>try:<EOL><INDENT>trips_frequency = gtfs.execute_custom_query_pandas(query).T.drop_duplicates().T<EOL>df = pd.merge(stops[['<STR_LIT>', '<STR_LIT>', '<STR_LIT>']], trips_frequency[['<STR_LIT>', '<STR_LIT>']],<EOL>on='<STR_LIT>', how='<STR_LIT>')<EOL>return df.apply(pd.to_numeric)<EOL><DEDENT>except:<EOL><INDENT>raise ValueError("<STR_LIT>")<EOL><DEDENT>
Return all the number of vehicles (i.e. busses,trams,etc) that pass hourly through a stop in a time frame.

Parameters
----------
gtfs: GTFS
st : int
    start time of the time framein unix time
et : int
    end time of the time frame in unix time
route_type: int

Returns
-------
numeric pandas.DataFrame with columns
    stop_I, lat, lon, frequency