GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 8.0.1 at 2026-07-03T23:50:47Z,
for the dataset file:///shared/pune-mahanagar-parivahan-mahamandal-limited_df4ea850.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included


  • Pune Mahanagar Parivahan Mahamandal Limited

Feed Info


Publisher Name:
BLRTransit
Publisher URL:
https://blrtransit.com
Feed Email:
N/A
Feed Language:
English
Feed Start Date:
2026-06-05
Feed End Date:
2026-12-02

Files included


  1. agency.txt
  2. calendar.txt
  3. feed_info.txt
  4. routes.txt
  5. shapes.txt
  6. stop_times.txt
  7. stops.txt
  8. trips.txt

Counts


  • Agencies: 1
  • Blocks: 0
  • Routes: 290
  • Shapes: 579
  • Stops: 6238
  • Trips: 8881

Specification Compliance report

466 notices reported (0 errors, 85 warnings, 381 infos)

Notice Code Severity Total
fast_travel_between_consecutive_stops WARNING 43

fast_travel_between_consecutive_stops

A transit vehicle moves too fast between two consecutive stops.

The speed threshold depends on route type:

Route type Description Threshold, km/h
0 Light rail 100
1 Subway 150
2 Rail 500
3 Bus 150
4 Ferry 80
5 Cable tram 30
6 Aerial lift 50
7 Funicular 50
11 Trolleybus 150
12 Monorail 150
- Unknown 200

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the problematic trip. tripId (?) `trip_id` of the problematic trip. routeId (?) `route_id` of the problematic trip. speedKph (?) Travel speed (km/h). distanceKm (?) Distance between stops (km). csvRowNumber1 (?) The row number of the first stop time. stopSequence1 (?) `stop_sequence` of the first stop. stopId1 (?) `stop_id` of the first stop. stopName1 (?) `stop_name` of the first stop. departureTime1 (?) `departure_time` of the first stop. csvRowNumber2 (?) The row number of the second stop time. stopSequence2 (?) `stop_sequence` of the second stop. stopId2 (?) `stop_id` of the second stop. stopName2 (?) `stop_name` of the second stop. arrivalTime2 (?) `arrival_time` of the second stop.
3810 "trip_477_3" "257" 220.63426763910593 4.1062488699500275 160130 10 "5089" "Solugaon" "09:24:07" 160131 11 "5088" "Thakur Vasti" "09:25:14"
3800 "trip_476_9" "257" 172.09035748198824 3.5374129037964246 159820 14 "5087" "Dattawadi Wajan Kata" "11:24:30" 159821 15 "5088" "Thakur Vasti" "11:25:44"
4718 "trip_567_1" "303A" 180.9792695294973 3.0163211588249546 194982 19 "1014" "Nano Home Ravet" "11:12:01" 194983 20 "1015" "Walhekarwadi Phata" "11:13:01"
4868 "trip_573_4" "305A" 160.5735396923367 2.676225661538945 199761 18 "5926" "Mask Company" "13:07:12" 199762 19 "5927" "Vishal Lawns" "13:08:12"
3811 "trip_477_4" "257" 220.63426763910593 4.1062488699500275 160155 10 "5089" "Solugaon" "10:04:07" 160156 11 "5088" "Thakur Vasti" "10:05:14"
4863 "trip_573_0" "305A" 160.5735396923367 2.676225661538945 199519 18 "5926" "Mask Company" "07:17:12" 199520 19 "5927" "Vishal Lawns" "07:18:12"
7322 "trip_857_4" "45" 197.42548393286236 5.813083693578726 309862 10 "7938" "Vadgaon Budruk Highway" "11:26:28" 309863 11 "7781" "Ved Bhavan" "11:28:14"
3796 "trip_476_5" "257" 172.09035748198824 3.5374129037964246 159720 14 "5087" "Dattawadi Wajan Kata" "08:44:30" 159721 15 "5088" "Thakur Vasti" "08:45:44"
7321 "trip_857_3" "45" 197.42548393286236 5.813083693578726 309828 10 "7938" "Vadgaon Budruk Highway" "11:16:28" 309829 11 "7781" "Ved Bhavan" "11:18:14"
4695 "trip_567_0" "303A" 180.9792695294973 3.0163211588249546 194648 19 "1014" "Nano Home Ravet" "09:27:01" 194649 20 "1015" "Walhekarwadi Phata" "09:28:01"
4722 "trip_567_3" "303A" 180.9792695294973 3.0163211588249546 195090 19 "1014" "Nano Home Ravet" "15:52:01" 195091 20 "1015" "Walhekarwadi Phata" "15:53:01"
3816 "trip_477_9" "257" 220.63426763910593 4.1062488699500275 160280 10 "5089" "Solugaon" "13:54:07" 160281 11 "5088" "Thakur Vasti" "13:55:14"
4869 "trip_573_5" "305A" 160.5735396923367 2.676225661538945 199821 18 "5926" "Mask Company" "14:07:12" 199822 19 "5927" "Vishal Lawns" "14:08:12"
3813 "trip_477_6" "257" 220.63426763910593 4.1062488699500275 160205 10 "5089" "Solugaon" "11:54:07" 160206 11 "5088" "Thakur Vasti" "11:55:14"
3815 "trip_477_8" "257" 220.63426763910593 4.1062488699500275 160255 10 "5089" "Solugaon" "13:14:07" 160256 11 "5088" "Thakur Vasti" "13:15:14"
4865 "trip_573_1" "305A" 160.5735396923367 2.676225661538945 199581 18 "5926" "Mask Company" "08:22:12" 199582 19 "5927" "Vishal Lawns" "08:23:12"
7326 "trip_857_8" "45" 197.42548393286236 5.813083693578726 309998 10 "7938" "Vadgaon Budruk Highway" "18:46:28" 309999 11 "7781" "Ved Bhavan" "18:48:14"
7325 "trip_857_7" "45" 197.42548393286236 5.813083693578726 309964 10 "7938" "Vadgaon Budruk Highway" "14:06:28" 309965 11 "7781" "Ved Bhavan" "14:08:14"
3791 "trip_476_0" "257" 172.09035748198824 3.5374129037964246 159595 14 "5087" "Dattawadi Wajan Kata" "06:14:30" 159596 15 "5088" "Thakur Vasti" "06:15:44"
3799 "trip_476_8" "257" 172.09035748198824 3.5374129037964246 159795 14 "5087" "Dattawadi Wajan Kata" "10:44:30" 159796 15 "5088" "Thakur Vasti" "10:45:44"
4866 "trip_573_2" "305A" 160.5735396923367 2.676225661538945 199641 18 "5926" "Mask Company" "09:47:12" 199642 19 "5927" "Vishal Lawns" "09:48:12"
7318 "trip_857_0" "45" 197.42548393286236 5.813083693578726 309726 10 "7938" "Vadgaon Budruk Highway" "08:16:28" 309727 11 "7781" "Ved Bhavan" "08:18:14"
4951 "trip_575_1" "305B" 160.5735396923367 2.676225661538945 202262 24 "5926" "Mask Company" "11:41:03" 202263 25 "5927" "Vishal Lawns" "11:42:03"
7324 "trip_857_6" "45" 197.42548393286236 5.813083693578726 309930 10 "7938" "Vadgaon Budruk Highway" "13:56:28" 309931 11 "7781" "Ved Bhavan" "13:58:14"
3808 "trip_477_1" "257" 220.63426763910593 4.1062488699500275 160080 10 "5089" "Solugaon" "08:04:07" 160081 11 "5088" "Thakur Vasti" "08:05:14"
3798 "trip_476_7" "257" 172.09035748198824 3.5374129037964246 159770 14 "5087" "Dattawadi Wajan Kata" "10:04:30" 159771 15 "5088" "Thakur Vasti" "10:05:44"
3809 "trip_477_2" "257" 220.63426763910593 4.1062488699500275 160105 10 "5089" "Solugaon" "08:44:07" 160106 11 "5088" "Thakur Vasti" "08:45:14"
3802 "trip_476_11" "257" 172.09035748198824 3.5374129037964246 159870 14 "5087" "Dattawadi Wajan Kata" "13:14:30" 159871 15 "5088" "Thakur Vasti" "13:15:44"
3794 "trip_476_3" "257" 172.09035748198824 3.5374129037964246 159670 14 "5087" "Dattawadi Wajan Kata" "07:24:30" 159671 15 "5088" "Thakur Vasti" "07:25:44"
4867 "trip_573_3" "305A" 160.5735396923367 2.676225661538945 199701 18 "5926" "Mask Company" "11:02:12" 199702 19 "5927" "Vishal Lawns" "11:03:12"
3812 "trip_477_5" "257" 220.63426763910593 4.1062488699500275 160180 10 "5089" "Solugaon" "10:44:07" 160181 11 "5088" "Thakur Vasti" "10:45:14"
7320 "trip_857_2" "45" 197.42548393286236 5.813083693578726 309794 10 "7938" "Vadgaon Budruk Highway" "10:16:28" 309795 11 "7781" "Ved Bhavan" "10:18:14"
3797 "trip_476_6" "257" 172.09035748198824 3.5374129037964246 159745 14 "5087" "Dattawadi Wajan Kata" "09:24:30" 159746 15 "5088" "Thakur Vasti" "09:25:44"
3795 "trip_476_4" "257" 172.09035748198824 3.5374129037964246 159695 14 "5087" "Dattawadi Wajan Kata" "08:04:30" 159696 15 "5088" "Thakur Vasti" "08:05:44"
7319 "trip_857_1" "45" 197.42548393286236 5.813083693578726 309760 10 "7938" "Vadgaon Budruk Highway" "09:16:28" 309761 11 "7781" "Ved Bhavan" "09:18:14"
4720 "trip_567_2" "303A" 180.9792695294973 3.0163211588249546 195036 19 "1014" "Nano Home Ravet" "13:02:01" 195037 20 "1015" "Walhekarwadi Phata" "13:03:01"
3793 "trip_476_2" "257" 172.09035748198824 3.5374129037964246 159645 14 "5087" "Dattawadi Wajan Kata" "06:54:30" 159646 15 "5088" "Thakur Vasti" "06:55:44"
3792 "trip_476_1" "257" 172.09035748198824 3.5374129037964246 159620 14 "5087" "Dattawadi Wajan Kata" "06:44:30" 159621 15 "5088" "Thakur Vasti" "06:45:44"
3814 "trip_477_7" "257" 220.63426763910593 4.1062488699500275 160230 10 "5089" "Solugaon" "12:34:07" 160231 11 "5088" "Thakur Vasti" "12:35:14"
4950 "trip_575_0" "305B" 160.5735396923367 2.676225661538945 202197 24 "5926" "Mask Company" "08:46:03" 202198 25 "5927" "Vishal Lawns" "08:47:03"
3801 "trip_476_10" "257" 172.09035748198824 3.5374129037964246 159845 14 "5087" "Dattawadi Wajan Kata" "12:34:30" 159846 15 "5088" "Thakur Vasti" "12:35:44"
7323 "trip_857_5" "45" 197.42548393286236 5.813083693578726 309896 10 "7938" "Vadgaon Budruk Highway" "13:36:28" 309897 11 "7781" "Ved Bhavan" "13:38:14"
3807 "trip_477_0" "257" 220.63426763910593 4.1062488699500275 160055 10 "5089" "Solugaon" "07:24:07" 160056 11 "5088" "Thakur Vasti" "07:25:14"
missing_recommended_field WARNING 1

missing_recommended_field

A recommended field is missing.

The given field has no value in some input row, even though values are recommended.

You can see more about this notice here.

filename (?) The name of the faulty file. csvRowNumber (?) The row of the faulty record. fieldName (?) The name of the missing field.
"feed_info.txt" 2 "feed_version"
mixed_case_recommended_field WARNING 5

mixed_case_recommended_field

This field has customer-facing text and should use Mixed Case (should contain upper and lower case letters).

This field contains customer-facing text and should use Mixed Case (upper and lower case letters) to ensure good readability when displayed to riders. Avoid the use of abbreviations throughout the feed (e.g. St. for Street) unless a location is called by its abbreviated name (e.g. “JFK Airport”). Abbreviations may be problematic for accessibility by screen reader software and voice user interfaces.

Good examples:
Field Text Dataset
"Schwerin, Hauptbahnhof" Verkehrsverbund Berlin-Brandenburg
"Red Hook/Atlantic Basin" NYC Ferry
"Campo Grande Norte" Carris
Bad examples:
Field Text
"GALLERIA MALL"
"3427 GG 17"
"21 Clark Rd Est"

You can see more about this notice here.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"routes.txt" "route_short_name" "METRO SHUTTLE 13" 284
"routes.txt" "route_short_name" "METRO SHUTTLE 17" 285
"routes.txt" "route_short_name" "METRO SHUTTLE 2" 286
"routes.txt" "route_short_name" "METRO SHUTTLE 31" 287
"routes.txt" "route_short_name" "METRO SHUTTLE 32" 288
route_short_name_too_long WARNING 5

route_short_name_too_long

Short name of a route is too long (more than 12 characters).

You can see more about this notice here.

routeId (?) The id of the faulty record. csvRowNumber (?) The row number of the faulty record. routeShortName (?) The faulty record's `route_short_name`.
"METRO SHUTTLE 13" 284 "METRO SHUTTLE 13"
"METRO SHUTTLE 17" 285 "METRO SHUTTLE 17"
"METRO SHUTTLE 2" 286 "METRO SHUTTLE 2"
"METRO SHUTTLE 31" 287 "METRO SHUTTLE 31"
"METRO SHUTTLE 32" 288 "METRO SHUTTLE 32"
stop_too_far_from_shape WARNING 8

stop_too_far_from_shape

Stop too far from trip shape.

Per GTFS Best Practices, route alignments (in shapes.txt) should be within 100 meters of stop locations which a trip serves. This potentially indicates a problem with the location of the stop or the path of the shape.

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the faulty record from `trips.txt`. shapeId (?) The id of the shape that is referred to. tripId (?) The id of the trip that is referred to. stopTimeCsvRowNumber (?) The row number of the faulty record from `stop_times.txt`. stopId (?) The id of the stop that is referred to. stopName (?) The name of the stop that is referred to. match (?) Latitude and longitude pair of the location. geoDistanceToShape (?) Distance from stop to shape.
7941 "1001" "trip_1001_0" 335438 "4841" "Chandani Chowk" [18.50681526392907,73.78261579021314] 100.20354867739938
6917 "829" "trip_829_0" 291890 "7749" "Mahila Mandal" [18.49931379557429,73.85070827257229] 101.19247503212058
5213 "606" "trip_606_0" 214383 "1746" "Nigdi" [18.65978,73.77722] 126.59255711571376
8105 "1034" "trip_1034_0" 341526 "7749" "Mahila Mandal" [18.49926,73.85078] 101.65090864710352
5395 "635" "trip_635_0" 223221 "597" "Kalewadi Phata" [18.6038,73.77714] 141.2272531121191
5425 "636" "trip_636_0" 224540 "597" "Kalewadi Phata" [18.6038,73.77714] 141.2272531121191
5846 "696" "trip_696_0" 245350 "597" "Kalewadi Phata" [18.6038,73.77714] 141.2272531121191
1155 "135" "trip_135_0" 41517 "1704" "Magarpatta Dawakhana" [18.502420000000004,73.92737] 130.46769565228414
stops_match_shape_out_of_order WARNING 23

stops_match_shape_out_of_order

Two stop entries are different than their arrival-departure order defined by shapes.txt.

This could indicate a problem with the location of the stops, the path of the shape, or the sequence of the stops for their trip.

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the faulty record from `trips.txt`. shapeId (?) The id of the shape that is referred to. tripId (?) The id of the trip that is referred to. stopTimeCsvRowNumber1 (?) The row number of the first faulty record from `stop_times.txt`. stopId1 (?) The id of the first stop that is referred to. stopName1 (?) The name of the first stop that is referred to. match1 (?) Latitude and longitude pair of the first matching location. stopTimeCsvRowNumber2 (?) The row number of the second faulty record from `stop_times.txt`. stopId2 (?) The id of the second stop that is referred to. stopName2 (?) The name of the second stop that is referred to. match2 (?) Latitude and longitude pair of the second matching location.
7962 "1003" "trip_1003_0" 336518 "353" "Wireless Office" [18.54194801280258,73.82819364511906] 336517 "352" "Pune Vidhyapeeth Gate Pashan Road" [18.541862718986973,73.82758903221233]
6895 "824" "trip_824_0" 290796 "5278" "Masulkar Colony" [18.633603278679402,73.80718892097238] 290795 "5277" "Vitthal Mandir Masulkar" [18.633610288250697,73.80710452328779]
7996 "1013" "trip_1013_0" 337816 "353" "Wireless Office" [18.54194801280258,73.82819364511906] 337815 "352" "Pune Vidhyapeeth Gate Pashan Road" [18.541862718986973,73.82758903221233]
7313 "858" "trip_858_0" 309523 "7800" "Malwadi Kirkatwadi" [18.43862493402992,73.7931950540317] 309522 "7799" "Hagawne Padal" [18.438932203276686,73.79261824921726]
8718 "1082" "trip_1082_0" 356593 "1796" "Shatrunjay Mandir" [18.450430000000004,73.87941] 356592 "3140" "Iscon Mandir" [18.450160616081096,73.87879398372151]
1690 "200" "trip_200_0" 68840 "1128" "Shanti Nagar" [18.566970927304457,73.87914894051508] 68835 "1127" "Mental Corner" [18.567428747391737,73.87941208304264]
4694 "568" "trip_568_0" 194481 "5847" "Vahtuk Nagari" [18.662200000000002,73.76842] 194480 "5846" "Krushna Mandir Nigdi" [18.662166621610616,73.76811217305114]
4699 "570" "trip_570_0" 194637 "5847" "Vahtuk Nagari" [18.662200000000002,73.76842] 194636 "5846" "Krushna Mandir Nigdi" [18.662166621610616,73.76811217305114]
5754 "694" "trip_694_0" 240650 "832" "Sanjivani Hospital" [18.757645020738156,73.84109085165167] 240648 "831" "Kharabwadi" [18.75755952643282,73.84152284140873]
4952 "587" "trip_587_0" 202374 "6076" "Tapkir Nagar Moshi Road" [18.674158465241124,73.88595610849872] 202372 "6080" "Talekar Vasti Moshi Road" [18.67390285039514,73.88655429922217]
4953 "588" "trip_588_0" 202327 "6080" "Talekar Vasti Moshi Road" [18.67379915486979,73.88649659359513] 202325 "6076" "Tapkir Nagar Moshi Road" [18.674054115408126,73.88590583133332]
5047 "590" "trip_590_0" 206743 "353" "Wireless Office" [18.54194801280258,73.82819364511906] 206696 "352" "Pune Vidhyapeeth Gate Pashan Road" [18.541862718986973,73.82758903221233]
3073 "371" "trip_371_0" 124936 "3888" "Zende Wadi" [18.41379945282363,74.00697894046486] 124935 "3887" "Zende Vasti" [18.41467345247805,74.0062312218809]
3072 "372" "trip_372_0" 124917 "3910" "Zende Vasti" [18.414450741198984,74.00648149310386] 124916 "3909" "Zende Wadi" [18.41389522441457,74.00706789699294]
3137 "373" "trip_373_0" 127560 "3888" "Zende Wadi" [18.41379945282363,74.00697894046486] 127559 "3887" "Zende Vasti" [18.41467345247805,74.0062312218809]
3145 "379" "trip_379_0" 128052 "3910" "Zende Vasti" [18.414450741198984,74.00648149310386] 128051 "3909" "Zende Wadi" [18.41389522441457,74.00706789699294]
2333 "266" "trip_266_0" 95785 "3037" "Mundhwa Gaon" [18.53299,73.93298] 95784 "2364" "Mundhwa Chowk" [18.5330606978483,73.93310513283407]
3262 "392" "trip_392_0" 134331 "3888" "Zende Wadi" [18.41379945282363,74.00697894046486] 134319 "3887" "Zende Vasti" [18.41467345247805,74.0062312218809]
3238 "393" "trip_393_0" 133118 "3910" "Zende Vasti" [18.414450741198984,74.00648149310386] 133117 "3909" "Zende Wadi" [18.41389522441457,74.00706789699294]
1356 "153" "trip_153_0" 49858 "353" "Wireless Office" [18.54194801280258,73.82819364511906] 49857 "352" "Pune Vidhyapeeth Gate Pashan Road" [18.541862718986973,73.82758903221233]
3343 "396" "trip_396_0" 136810 "3888" "Zende Wadi" [18.41379945282363,74.00697894046486] 136809 "3887" "Zende Vasti" [18.41467345247805,74.0062312218809]
3345 "397" "trip_397_0" 136966 "3910" "Zende Vasti" [18.414450741198984,74.00648149310386] 136965 "3909" "Zende Wadi" [18.41389522441457,74.00706789699294]
1391 "167" "trip_167_0" 51179 "353" "Wireless Office" [18.54194801280258,73.82819364511906] 51178 "352" "Pune Vidhyapeeth Gate Pashan Road" [18.541862718986973,73.82758903221233]
trip_headsign_matches_intermediate_stop INFO 35

trip_headsign_matches_intermediate_stop

Trip headsign matches the name of an intermediate stop, not the last stop.

The trip_headsign matches the stop_name of a stop that is not the last stop of the trip. This may confuse passengers boarding after that stop, since the headsign suggests the vehicle is heading to a stop it has already passed.

You can see more about this notice here.

csvRowNumber (?) The row number of the faulty record in `trips.txt`. tripId (?) The id of the trip with the problematic headsign. tripHeadsign (?) The headsign value that matches an intermediate stop name. stopId1 (?) The id of the intermediate stop whose name matches the headsign. stopSequence (?) The stop_sequence value of the intermediate stop that matches the headsign. stopId2 (?) The id of the actual last stop of the trip.
1341 "trip_168_0" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1342 "trip_168_1" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1343 "trip_168_2" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1344 "trip_168_3" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1345 "trip_168_4" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1346 "trip_168_5" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1347 "trip_168_6" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1348 "trip_168_7" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1349 "trip_168_8" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1350 "trip_168_9" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1351 "trip_168_10" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1352 "trip_168_11" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1353 "trip_168_12" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1354 "trip_168_13" "Pune Station Jayprakash Stand" "1777" 21 "1828"
1355 "trip_168_14" "Pune Station Jayprakash Stand" "1777" 21 "1828"
2581 "trip_318_0" "Jspm College" "3524" 12 "3524"
2582 "trip_318_1" "Jspm College" "3524" 12 "3524"
2583 "trip_318_2" "Jspm College" "3524" 12 "3524"
2584 "trip_318_3" "Jspm College" "3524" 12 "3524"
2585 "trip_318_4" "Jspm College" "3524" 12 "3524"
2586 "trip_318_5" "Jspm College" "3524" 12 "3524"
2587 "trip_318_6" "Jspm College" "3524" 12 "3524"
2588 "trip_318_7" "Jspm College" "3524" 12 "3524"
2589 "trip_318_8" "Jspm College" "3524" 12 "3524"
8823 "trip_1130_0" "Nigdi Pawale Chowk" "5844" 12 "5844"
8824 "trip_1130_1" "Nigdi Pawale Chowk" "5844" 12 "5844"
8825 "trip_1130_2" "Nigdi Pawale Chowk" "5844" 12 "5844"
8826 "trip_1130_3" "Nigdi Pawale Chowk" "5844" 12 "5844"
8827 "trip_1130_4" "Nigdi Pawale Chowk" "5844" 12 "5844"
8828 "trip_1130_5" "Nigdi Pawale Chowk" "5844" 12 "5844"
8829 "trip_1130_6" "Nigdi Pawale Chowk" "5844" 12 "5844"
8830 "trip_1130_7" "Nigdi Pawale Chowk" "5844" 12 "5844"
8831 "trip_1130_8" "Nigdi Pawale Chowk" "5844" 12 "5844"
8832 "trip_1130_9" "Nigdi Pawale Chowk" "5844" 12 "5844"
8833 "trip_1130_10" "Nigdi Pawale Chowk" "5844" 12 "5844"
unsorted_stop_times INFO 346

unsorted_stop_times

Stop times are not sorted by trip_id and stop_sequence.

'stop_times.txt' entries for a given trip are not sorted by stop_sequence, or are not contiguous in the file.

You can see more about this notice here.

Only the first 50 of 346 affected records are displayed below.

tripId (?) The faulty record's trip_id. startCsvRowNumber (?) CSV row number of the first stop_times entry for this trip. endCsvRowNumber (?) CSV row number of the last stop_times entry for this trip.
"trip_158_0" 49291 49332
"trip_800_0" 289566 289897
"trip_1076_0" 355320 355583
"trip_648_0" 228542 229016
"trip_696_0" 245325 245426
"trip_372_0" 124880 124934
"trip_813_0" 291989 292023
"trip_217_0" 83215 83996
"trip_502_0" 166527 166603
"trip_697_0" 245373 245713
"trip_311_0" 110085 110301
"trip_324_0" 105345 105762
"trip_457_0" 144817 144892
"trip_1001_0" 335411 335517
"trip_812_0" 290229 290441
"trip_1077_0" 355046 355071
"trip_562_0" 193760 194330
"trip_139_12" 45444 45505
"trip_139_14" 45569 45630
"trip_15_0" 7581 7648
"trip_322_0" 108249 108298
"trip_131_0" 47920 48334
"trip_224_16" 76000 76054
"trip_224_17" 76055 76109
"trip_6_3" 187 239
"trip_6_0" 2 79
"trip_838_0" 295363 295403
"trip_695_0" 240601 241394
"trip_1327_0" 237626 238378
"trip_994_0" 333806 333951
"trip_861_0" 308360 308382
"trip_501_0" 167875 168612
"trip_371_0" 124890 125863
"trip_456_0" 144889 145259
"trip_1002_0" 337101 337241
"trip_469_0" 156165 156599
"trip_887_1" 316168 316221
"trip_887_0" 315536 316129
"trip_336_0" 114496 114882
"trip_824_0" 290766 290810
"trip_561_0" 193708 193759
"trip_944_0" 329326 329382
"trip_931_0" 328398 328476
"trip_38_0" 9257 9351
"trip_574_0" 201214 201441
"trip_454_0" 142875 143005
"trip_659_0" 230238 230463
"trip_587_0" 202304 202382
"trip_1061_0" 351297 351334
"trip_539_3" 176378 176485