GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 5.0.1 at 2024-06-08T04:02:22Z,
for the dataset file:///tmp/1_in.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Feed Info

Publisher Name:
Aplibus
Publisher URL:
https://www.aplibus.com
Feed Language:
French
Feed Start Date:
2024-03-25
Feed End Date:
2024-07-07

Files included

  1. agency.txt
  2. calendar.txt
  3. calendar_dates.txt
  4. feed_info.txt
  5. routes.txt
  6. shapes.txt
  7. stop_times.txt
  8. stops.txt
  9. transfers.txt
  10. translations.txt
  11. trips.txt

Counts

  • Agencies: 1
  • Blocks: 1
  • Routes: 15
  • Shapes: 94
  • Stops: 470
  • Trips: 10497

GTFS Features included (?) GTFS features provide a standardized vocabulary to define and describe features that are officially adopted in GTFS.

ShapesFeed InformationRoute ColorsHeadsignsWheelchair AccessibilityBikes AllowanceLocation Types

Specification Compliance report

9789 notices reported (0 errors, 9787 warnings, 2 infos)

Notice Code Severity Total
equal_shape_distance_diff_coordinates_distance_below_threshold WARNING 2477

equal_shape_distance_diff_coordinates_distance_below_threshold

Two consecutive points have equal shape_dist_traveled and different lat/lon coordinates in shapes.txt and the distance between the two points is less than 1.11m.

When sorted by shape.shape_pt_sequence, the values for shape_dist_traveled must increase along a shape. Two consecutive points with equal values for shape_dist_traveled and small difference of coordinates (less than 1.11 m distance) result in a warning.

You can see more about this notice here.

Only the first 50 of 2477 affected records are displayed below.

shapeId (?) The id of the faulty shape. csvRowNumber (?) The row number from `shapes.txt`. shapeDistTraveled (?) The faulty record's `shape_dist_traveled` value. shapePtSequence (?) The faulty record's `shapes.shape_pt_sequence`. prevCsvRowNumber (?) The row number from `shapes.txt` of the previous shape point. prevShapeDistTraveled (?) The previous shape point's `shape_dist_traveled` value. prevShapePtSequence (?) The previous record's `shapes.shape_pt_sequence`. actualDistanceBetweenShapePoints (?) Actual distance traveled along the shape from the first shape point to the previous shape point.
"44" 21613 0.0 2 21612 0.0 1 0.07294935956879288
"44" 21625 0.582 14 21624 0.582 13 9.346170433327935E-10
"44" 21626 0.582 15 21625 0.582 14 0.04616428245360347
"44" 21627 0.582 16 21626 0.582 15 0.046164282465885664
"44" 21697 4.153 86 21696 4.153 85 0.3906533766963948
"44" 21699 4.154 88 21698 4.154 87 6.111114418123989E-10
"44" 21747 6.57 136 21746 6.57 135 0.5076964021813399
"44" 21749 6.571 138 21748 6.571 137 1.222219761060418E-9
"44" 21754 6.898 143 21753 6.898 142 0.17517640384015912
"44" 21755 6.898 144 21754 6.898 143 0.17517640376013185
"44" 21756 6.898 145 21755 6.898 144 8.959848551007732E-10
"44" 21775 7.514 164 21774 7.514 163 1.5662522518963105E-9
"44" 21776 7.514 165 21775 7.514 164 0.4702658908128079
"45" 6103 0.0 2 6102 0.0 1 0.07294935956879288
"45" 6115 0.582 14 6114 0.582 13 9.346170433327935E-10
"45" 6116 0.582 15 6115 0.582 14 0.04616428245360347
"45" 6117 0.582 16 6116 0.582 15 0.046164282465885664
"45" 6187 4.153 86 6186 4.153 85 0.3906533766963948
"45" 6189 4.154 88 6188 4.154 87 6.111114418123989E-10
"45" 6221 5.714 120 6220 5.714 119 9.758200155167697E-10
"45" 6222 5.714 121 6221 5.714 120 0.3892154609598156
"45" 6223 5.714 122 6222 5.714 121 0.3892154619100457
"45" 6241 6.199 140 6240 6.199 139 1.5662477766438227E-9
"47" 9205 0.0 2 9204 0.0 1 0.021427647605145442
"47" 9240 2.175 37 9239 2.175 36 6.112332105810245E-10
"47" 9241 2.175 38 9240 2.175 37 0.7186216051924145
"47" 9276 2.902 73 9275 2.902 72 0.09251604139101693
"47" 9278 2.902 75 9277 2.902 74 0.09251604139101693
"47" 9305 3.934 102 9304 3.934 101 0.08678729382083109
"47" 9306 3.934 103 9305 3.934 102 0.08678729485960802
"47" 9307 3.934 104 9306 3.934 103 1.1100819882921644E-9
"47" 9341 5.144 138 9340 5.144 137 2.5641089688625984E-9
"47" 9342 5.144 139 9341 5.144 138 0.17524136529649387
"47" 9415 8.599 212 9414 8.599 211 0.6010269994956701
"47" 9480 11.086 277 9479 11.086 276 0.27467040926369213
"47" 9482 11.087 279 9481 11.087 278 0.27986811751640933
"47" 9535 13.999 332 9534 13.999 331 1.4199130654405624E-9
"151" 17718 0.0 2 17717 0.0 1 3.01252753964773E-9
"151" 17758 1.395 42 17757 1.395 41 0.008560584454160013
"151" 17760 1.396 44 17759 1.396 43 0.20237397493302695
"151" 17762 1.705 46 17761 1.705 45 6.417420537746165E-4
"151" 17763 1.705 47 17762 1.705 46 7.610620434290228E-6
"151" 17764 1.705 48 17763 1.705 47 0.16507278340386114
"151" 17785 4.102 69 17784 4.102 68 0.27870588606886776
"151" 17801 6.238 85 17800 6.238 84 2.8292967968468474E-9
"151" 17810 7.408 94 17809 7.408 93 2.1219725976351356E-9
"151" 17818 7.908 102 17817 7.908 101 2.1219725976351356E-9
"151" 17838 9.856 122 17837 9.856 121 0.3340348708763818
"151" 17839 9.856 123 17838 9.856 122 0.15055052186743934
"151" 17870 11.731 154 17869 11.731 153 6.103839357224394E-10
equal_shape_distance_same_coordinates WARNING 423

equal_shape_distance_same_coordinates

Two consecutive points have equal shape_dist_traveled and the same lat/lon coordinates in shapes.txt.

When sorted by shape.shape_pt_sequence, the values for shape_dist_traveled must increase along a shape. Two consecutive points with equal values for shape_dist_traveled and the same coordinates indicate a duplicative shape point.

You can see more about this notice here.

Only the first 50 of 423 affected records are displayed below.

shapeId (?) The id of the faulty shape. csvRowNumber (?) The row number from `shapes.txt`. shapeDistTraveled (?) Actual distance traveled along the shape from the first shape point to the faulty record. shapePtSequence (?) The faulty record's `shapes.shape_pt_sequence`. prevCsvRowNumber (?) The row number from `shapes.txt` of the previous shape point. prevShapeDistTraveled (?) Actual distance traveled along the shape from the first shape point to the previous shape point. prevShapePtSequence (?) The previous record's `shapes.shape_pt_sequence`.
"47" 9277 2.902 74 9276 2.902 73
"151" 17784 4.102 68 17783 4.102 67
"151" 17886 12.199 170 17885 12.199 169
"151" 17902 13.389 186 17901 13.389 185
"151" 18001 20.771 285 18000 20.771 284
"151" 18013 21.425 297 18012 21.425 296
"151" 18041 24.13 325 18040 24.13 324
"151" 18136 28.879 420 18135 28.879 419
"110" 4864 0.939 15 4863 0.939 14
"110" 4873 1.403 24 4872 1.403 23
"110" 4954 4.102 105 4953 4.102 104
"110" 4970 4.577 121 4969 4.577 120
"110" 5001 5.631 152 5000 5.631 151
"110" 5023 6.463 174 5022 6.463 173
"110" 5031 6.953 182 5030 6.953 181
"110" 5053 7.513 204 5052 7.513 203
"110" 5064 7.836 215 5063 7.836 214
"110" 5067 8.146 218 5066 8.146 217
"110" 5077 8.502 228 5076 8.502 227
"110" 5102 9.609 253 5101 9.609 252
"155" 20192 4.102 68 20191 4.102 67
"155" 20262 13.46 138 20261 13.46 137
"113" 47 1.595 46 46 1.595 45
"113" 82 2.785 81 81 2.785 80
"113" 94 3.245 93 93 3.245 92
"113" 98 3.454 97 97 3.454 96
"113" 110 3.952 109 109 3.952 108
"113" 130 5.031 129 129 5.031 128
"113" 145 5.731 144 144 5.731 143
"157" 15753 4.226 71 15752 4.226 70
"157" 15823 13.584 141 15822 13.584 140
"114" 4191 0.498 18 4190 0.498 17
"114" 4212 0.944 39 4211 0.944 38
"114" 4235 1.732 62 4234 1.732 61
"114" 4256 2.471 83 4255 2.471 82
"114" 4259 2.781 86 4258 2.781 85
"114" 4277 3.341 104 4276 3.341 103
"114" 4335 5.393 162 4334 5.393 161
"114" 4370 6.584 197 4369 6.584 196
"114" 4382 7.043 209 4381 7.043 208
"114" 4386 7.252 213 4385 7.252 212
"114" 4398 7.75 225 4397 7.75 224
"114" 4418 8.829 245 4417 8.829 244
"114" 4433 9.53 260 4432 9.53 259
"115" 1347 1.38 27 1346 1.38 26
"115" 1368 2.259 48 1367 2.259 47
"115" 1387 3.822 67 1386 3.822 66
"115" 1403 4.383 83 1402 4.383 82
"116" 5139 1.38 27 5138 1.38 26
"116" 5160 2.259 48 5159 2.259 47
expired_calendar WARNING 10

expired_calendar

Dataset should not contain date ranges for services that have already expired.

This warning takes into account the calendar_dates.txt file as well as the calendar.txt file.

You can see more about this notice here.

csvRowNumber (?) The row of the faulty record. serviceId (?) The service id of the faulty record.
18 "6_2024_01_01_"
19 "7_2024_04_15_"
17 "5_2024_04_15_"
21 "9_2024_05_02_"
2 "1_2024_01_22_"
7 "14_2024_05_02_"
13 "2_2024_01_22_"
20 "8_2024_04_29_"
15 "3_2024_01_22_"
16 "4_2024_01_22_"
fast_travel_between_consecutive_stops WARNING 16

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.
1184 "40000025" "C" 336.41374973035 0.28034479144195834 112223 7 "T_COR2" "Corniche" "08:25:00" 112224 8 "T_BELA2" "Bel Air" "08:25:03"
4956 "10000394" "C" 336.41374973035 0.28034479144195834 16503 7 "T_COR2" "Corniche" "08:25:00" 16504 8 "T_BELA2" "Bel Air" "08:25:03"
8312 "20000389" "C" 336.41374973035 0.28034479144195834 100187 7 "T_COR2" "Corniche" "08:25:00" 100188 8 "T_BELA2" "Bel Air" "08:25:03"
1184 "40000025" "C" 371.10168529815405 0.3092514044151284 112226 10 "T_JJROU2" "Stade Moynat" "08:27:00" 112227 11 "T_CAEP2" "Froid lieu" "08:27:03"
4956 "10000394" "C" 371.10168529815405 0.3092514044151284 16506 10 "T_JJROU2" "Stade Moynat" "08:27:00" 16507 11 "T_CAEP2" "Froid lieu" "08:27:03"
8312 "20000389" "C" 371.10168529815405 0.3092514044151284 100190 10 "T_JJROU2" "Stade Moynat" "08:27:00" 100191 11 "T_CAEP2" "Froid lieu" "08:27:03"
1184 "40000025" "C" 383.70704927659807 0.319755874397165 112231 15 "T_Pinso2" "Pinsons" "08:32:00" 112232 16 "T_CoPar2" "Corzent Parc" "08:32:03"
4956 "10000394" "C" 383.70704927659807 0.319755874397165 16511 15 "T_Pinso2" "Pinsons" "08:32:00" 16512 16 "T_CoPar2" "Corzent Parc" "08:32:03"
8312 "20000389" "C" 383.70704927659807 0.319755874397165 100195 15 "T_Pinso2" "Pinsons" "08:32:00" 100196 16 "T_CoPar2" "Corzent Parc" "08:32:03"
1184 "40000025" "C" 250.629758402566 0.20885813200213835 112236 20 "AT_CHEn2" "Chênes" "08:36:00" 112237 21 "AT_SAVo2" "Savoyances" "08:36:03"
4956 "10000394" "C" 250.629758402566 0.20885813200213835 16516 20 "AT_CHEn2" "Chênes" "08:36:00" 16517 21 "AT_SAVo2" "Savoyances" "08:36:03"
8312 "20000389" "C" 250.629758402566 0.20885813200213835 100200 20 "AT_CHEn2" "Chênes" "08:36:00" 100201 21 "AT_SAVo2" "Savoyances" "08:36:03"
100 "30000242" "C" 336.41374973035 0.28034479144195834 105473 2 "T_COR2" "Corniche" "08:25:00" 105474 3 "T_BELA2" "Bel Air" "08:25:03"
100 "30000242" "C" 371.10168529815405 0.3092514044151284 105476 5 "T_JJROU2" "Stade Moynat" "08:27:00" 105477 6 "T_CAEP2" "Froid lieu" "08:27:03"
100 "30000242" "C" 383.70704927659807 0.319755874397165 105481 10 "T_Pinso2" "Pinsons" "08:32:00" 105482 11 "T_CoPar2" "Corzent Parc" "08:32:03"
100 "30000242" "C" 250.629758402566 0.20885813200213835 105486 15 "AT_CHEn2" "Chênes" "08:36:00" 105487 16 "AT_SAVo2" "Savoyances" "08:36:03"
feed_expiration_date30_days WARNING 1

feed_expiration_date30_days

Dataset should cover at least the next 30 days of service.

At any time, the GTFS dataset should cover at least the next 30 days of service, and ideally for as long as the operator is confident that the schedule will continue to be operated.

You can see more about this notice here.

csvRowNumber (?) The row number of the faulty record. currentDate (?) Current date (YYYYMMDD format). feedEndDate (?) Feed end date (YYYYMMDD format). suggestedExpirationDate (?) Suggested expiration date (YYYYMMDD format).
2 "20240608" "20240707" "20240708"
missing_feed_contact_email_and_url WARNING 1

missing_feed_contact_email_and_url

Best Practices for feed_info.txt suggest providing at least one of feed_contact_email and feed_contact_url.

You can see more about this notice here.

csvRowNumber (?) The row number of the validated record.
2
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 5930

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.

Only the first 50 of 5930 affected records are displayed below.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 37
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 38
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 39
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 40
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 41
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 42
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 43
"trips.txt" "trip_headsign" "THO_Z.I. VONGY" 44
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 132
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 133
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 134
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 135
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 136
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 137
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 138
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 139
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 140
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 141
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 142
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 143
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 144
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 145
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 146
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 147
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 148
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 149
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 150
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 151
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 152
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 153
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 154
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 155
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 156
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 157
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 158
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 159
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 160
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 161
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 162
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 163
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 164
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 165
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 166
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 167
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 168
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 169
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 170
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 171
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 172
"trips.txt" "trip_headsign" "THO_CENTRE MED. CHABL." 173
route_color_contrast WARNING 1

route_color_contrast

Insufficient route color contrast.

A route's color and route_text_color should be contrasting.

You can see more about this notice here.

routeId (?) The id of the faulty record. csvRowNumber (?) The row number of the faulty record. routeColor (?) The faulty record's HTML route color. routeTextColor (?) The faulty record's HTML route text color.
"N" 13 "#FCB729" "#FFFFFF"
route_long_name_contains_short_name WARNING 15

route_long_name_contains_short_name

Long name should not contain short name for a single route.

In routes.txt, route_long_name should not contain the value for route_short_name, because when both are provided, they are often combined by transit applications. Note that only one of the two fields is required. If there is no short name used for a route, use route_long_name only.

Good examples:

route_short_name/route_long_name Dataset
"N"/"Judah" Muni San Fransisco
"6"/"ML King Jr Blvd" Trimet Portland Streetcar
"55"/"Boulevard Saint Laurent" STM Montreal
"1"/"Rangiora/Cashmere" Metro Christchurch

Bad examples:

route_short_name/route_long_name
"604"/"604"
"14"/"Route 14"
"2"/"Route 2: Bellows Falls In-Town"

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`. routeLongName (?) The faulty record's `route_long_name`.
"141" 2 "141" "141"
"142" 3 "142" "142"
"143" 4 "143" "143"
"151" 5 "151" "151"
"152" 6 "152" "152"
"A" 7 "A" "A"
"B" 8 "B" "B"
"C" 9 "C" "C"
"D" 10 "D" "D"
"F" 11 "F" "F"
"M" 12 "M" "M"
"N" 13 "N" "N"
"NB" 14 "NB" "NB"
"NL" 15 "NL" "NL"
"T" 16 "T" "T"
stop_too_far_from_shape_using_user_distance WARNING 912

stop_too_far_from_shape_using_user_distance

Stop time too far from shape.

A stop time entry that is a large distance away from the location of the shape in shapes.txt as defined by shape_dist_traveled values.

You can see more about this notice here.

Only the first 50 of 912 affected records are displayed below.

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.
296 "47" "30000787" 110891 "BA_CHEC2" "Chef Lieu de Ballaison / École" [46.29489253574218,6.33174000128436] 551.1075039257821
296 "47" "30000787" 110892 "LO_CHL1" "Chef-Lieu de Loisin" [46.289731262484516,6.31431261968758] 363.90955169704114
296 "47" "30000787" 110893 "D_COBCH2" "Collège du Bas Chablais" [46.29982630024898,6.304571101767085] 658.3840499255631
562 "151" "30001379" 112081 "T_JJROU2" "Stade Moynat" [46.36818358320463,6.472254400788517] 369.29782612668026
562 "151" "30001379" 112082 "T_CAEP2" "Froid lieu" [46.36660000320376,6.468941213313013] 369.29943782492984
562 "151" "30001379" 112083 "T_GRAEG2" "Grangette Église" [46.36428639992897,6.464061355472623] 360.33233436196116
562 "151" "30001379" 112084 "T_CRANT2" "Croisee d'Anthy" [46.354081424439286,6.444164010230428] 372.58847551089235
562 "151" "30001379" 112085 "MA_5CHE2" "Cinq Chemins" [46.34551582416826,6.419662701601228] 382.5991015107669
562 "151" "30001379" 112086 "S_JUSS2" "Jussy" [46.34025401037604,6.406853055396007] 392.95135638709763
562 "151" "30001379" 112087 "S_CONT2" "Le Content" [46.33747747680191,6.4021727275103375] 399.4668071792568
562 "151" "30001379" 112088 "S_BONPO2" "Bonnatrait Route de Port" [46.335718564167564,6.398578745538999] 404.8157755639821
562 "151" "30001379" 112089 "S_BONN2" "Bonnatrait" [46.334062741571714,6.390700636188011] 422.3649077355267
562 "151" "30001379" 112090 "S_CHL2" "Chef-Lieu de Sciez" [46.33182676955893,6.379125044738112] 409.81256933140793
562 "151" "30001379" 112091 "EX_FATT2" "La Fattaz" [46.33797666682207,6.359578889403665] 450.41560465402824
562 "151" "30001379" 112092 "EX_PINE2" "La Pinède" [46.34157766666686,6.356753000002286] 427.8045779334773
562 "151" "30001379" 112093 "EX_CHL2" "Chef-Lieu d'Excenevex" [46.35163697232151,6.356412314778863] 456.3809349919875
562 "151" "30001379" 112094 "Y_MOTT2" "Les Mottes" [46.36665202952962,6.342745306083897] 438.3535038368417
562 "151" "30001379" 112095 "Y_PREP2" "Pré Ponce" [46.36812164438632,6.332355996563355] 500.1472555567201
562 "151" "30001379" 112096 "NER_CHL1" "Chef Lieu de Nernier" [46.360092307725,6.305283076745817] 327.50144729734996
562 "151" "30001379" 112097 "ME_VERE2" "Veret" [46.3530287580179,6.300242724770339] 335.4405976925495
562 "151" "30001379" 112098 "ME_CHL2" "Chef-Lieu de Messery" [46.351657915500915,6.297163173239598] 342.92301996927307
562 "151" "30001379" 112099 "ME_BROL2" "Brolliets" [46.35094170344645,6.292627289385954] 335.85947155247703
562 "151" "30001379" 112100 "ME_REPI2" "Repingeons" [46.34769024704214,6.288146532576855] 336.74421236665836
562 "151" "30001379" 112101 "CL_FICH2" "Fichards" [46.331818728516076,6.272612018929847] 342.64920708074914
562 "151" "30001379" 112102 "CL_CHL2" "Chef-Lieu de Chens-sur-Léman" [46.32838681843781,6.268839478050733] 322.9234359737855
562 "151" "30001379" 112103 "CL_VERE2" "Véreitre" [46.32006414286792,6.269476214142066] 360.40606219499307
562 "151" "30001379" 112104 "D_MAI1" "Mairie" [46.30633152566174,6.298178136141855] 335.4225510074481
562 "151" "30001379" 112105 "D_COBCH2" "Collège du Bas Chablais" [46.306591232985475,6.307273699402508] 337.67262910414786
132 "110" "30000307" 106475 "T_JULM2" "Jules Mercier" [46.37017200054752,6.479573100247009] 163.07669913867343
132 "110" "30000307" 106476 "T_PATH2" "Parc Thermal" [46.36984010678503,6.477398607893308] 200.09582159377518
132 "110" "30000307" 106477 "T_TROL2" "Trolliettes" [46.36774778792321,6.47300109463846] 200.81939755822518
132 "110" "30000307" 106478 "T_MASC2" "Mascottes" [46.367018359961406,6.473568315976555] 194.36749589271264
132 "110" "30000307" 106479 "T_VUL2" "Vulpins" [46.36559004013851,6.474398965811391] 202.6654221044991
132 "110" "30000307" 106480 "T_LYVER2" "Lycée de la Versoie" [46.36409353254952,6.472695895798592] 166.74489384897745
132 "110" "30000307" 106481 "T_AUMO2" "Aumônerie" [46.36372581824877,6.4710939548658475] 236.9656457864721
132 "110" "30000307" 106482 "T_JJROU2" "Stade Moynat" [46.36482022566519,6.470134680868741] 217.71670853746264
132 "110" "30000307" 106483 "T_CAEP2" "Froid lieu" [46.36608456618822,6.467839454380167] 267.17030524592303
132 "110" "30000307" 106484 "T_GREC2" "Grangette École" [46.36429856569409,6.464128085994203] 235.93995284213796
132 "110" "30000307" 106485 "T_PELE2" "Pélerins" [46.361502363333436,6.462671697517707] 272.9035483822335
132 "110" "30000307" 106486 "T_MARA2" "Marais" [46.36040787565165,6.460309844364394] 275.7542887058233
132 "110" "30000307" 106487 "T_ROSE2" "Roseaux" [46.358623363705554,6.458793272513828] 263.37015309861073
132 "110" "30000307" 106488 "T_MORC2" "Morcy" [46.357857625231105,6.456537873690776] 293.99836803119746
132 "110" "30000307" 106489 "T_CMED1" "Centre Médical du Chablais" [46.35608283625549,6.4544457221909175] 240.28970282577916
613 "155" "140000171" 38053 "T_JJROU2" "Stade Moynat" [46.36818358320463,6.472254400788517] 369.29782612668026
613 "155" "140000171" 38054 "T_CAEP2" "Froid lieu" [46.36660000320376,6.468941213313013] 369.29943782492984
613 "155" "140000171" 38055 "T_GRAEG2" "Grangette Église" [46.36428639992897,6.464061355472623] 360.33233436196116
613 "155" "140000171" 38056 "T_CRANT2" "Croisee d'Anthy" [46.354081424439286,6.444164010230428] 372.58847551089235
613 "155" "140000171" 38057 "MA_5CHE2" "Cinq Chemins" [46.34551582416826,6.419662701601228] 382.5991015107669
613 "155" "140000171" 38058 "S_JUSS2" "Jussy" [46.34025401037604,6.406853055396007] 392.95135638709763
613 "155" "140000171" 38059 "S_CONT2" "Le Content" [46.33747747680191,6.4021727275103375] 399.4668071792568
unknown_column INFO 2

unknown_column

A column name is unknown.

You can see more about this notice here.

filename (?) The name of the faulty file. fieldName (?) The name of the unknown column. index (?) The index of the faulty column.
"agency.txt" "agency_sort_order" 9
"translations.txt" "id" 1