Transportation Ridership Heatmap Data

This dataset provides detailed, time-stamped ridership counts across transportation routes and stops, including passenger boardings and alightings, vehicle types, and contextual factors such as weather and holidays. It enables granular analysis of transit demand patterns for network optimization, service planning, and infrastructure investment. The data is ideal for generating heatmaps, forecasting ridership, and identifying peak usage periods.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Transit network optimization and route planning

Sample rows

preview · 8 of 200 rows · all 15 columns
ridership_idstringvehicle_typestringcapacityintegeris_holidaybooleanroute_idstringroute_namestringstop_idstringstop_namestringstop_latitudefloatstop_longitudefloatdatedatetime_periodstringboardingsintegeralightingsintegerweather_conditionstring
RID00001bus50falseR1Downtown ExpressS1001Central Station40.7127-74.00592024-06-0308:00-09:004421clear
RID00002ferry140trueR2Harbor FerryS2001Pier 3937.8086-122.40982024-07-0409:00-10:00105fog
RID00003tram35falseR3City Center LoopS3001Market Square38.8895-77.03532024-06-0412:00-13:002719cloudy
RID00004metro280falseR4Uptown MetroS4001Main Terminal34.0522-118.24372024-06-05AM peak18063clear
RID00005bus40falseR5Eastside ShuttleS1002Elm Avenue41.8781-87.62982024-06-05PM peak3617rain
RID00006train300trueR6Coastal TrainS6001Ocean View47.6062-122.33212024-12-2507:00-08:0000snow
RID00007bus35falseR7South District BusS1003Maple Street39.9526-75.16522024-06-0610:00-11:002513clear
RID00008metro180falseR8Metro NorthS4002North Station42.3601-71.05892024-06-07AM peak12045cloudy

What the 200 rows show

from the 200-row sample

Train (vehicle type) stands out: mean capacity is 300.0, against 89.3 for the rest.

  • 24%is_holiday = true
  • 50median capacity
  • 6weather conditions
  • 16time periods
  • 50route names
  • 36median boardings
Mean capacity by vehicle_type200 rows
020040040.5bus65 rows300.0train26 rows35.0tram28 rows189.5metro42 rows135.9ferry28 rows15.0other11 rows
capacity200 rows, in bands of 50
050100941233169360150300capacity →

Median 50, from 15 to 300.

route_id200 rows · top 10 of 17 values
  1. R819
  2. R117
  3. R316
  4. R516
  5. R716
  6. R1215
  7. R1013
  8. R412
  9. R612
  10. R1111
15 columns by typefrom the column list below
  • string 8
  • integer 3
  • float 2
  • date 1
  • boolean 1

Columns

15 columns in four groups
blueprint · 15 columns
columntypedescriptionexample
Text 8 columns
ridership_idstringUnique identifier for each ridership recorduniqueRID00001
route_idstringUnique identifier for the transportation routeR1
route_namestringName of the transportation routeDowntown Express
vehicle_typestringType of vehicle used on the route (e.g., bus, train, tram)6 valuesbus
stop_idstringUnique identifier for the stop/stationS1001
stop_namestringName of the stop/stationCentral Station
time_periodstringTime period of the ridership count (e.g., 08:00-09:00, AM peak, PM peak)08:00-09:00
weather_conditionstringWeather condition during the time period (e.g., clear, rain, snow, fog)6 values · optionalclear
Numbers 5 columns
stop_latitudefloatLatitude coordinate of the stop location-90 to 9040.7127
stop_longitudefloatLongitude coordinate of the stop location-180 to 180-74.0059
boardingsintegerNumber of passengers boarding at the stop during the time period0 or more44
alightingsintegerNumber of passengers alighting at the stop during the time period0 or more21
capacityintegerMaximum passenger capacity of the vehicle for the route0 or more · optional50
Dates and times 1 column
datedateDate of the ridership count2024-06-03
True or false 1 column
is_holidaybooleanIndicates if the date is a public holidayoptionalfalse

Use it for

  • is holiday24%48 of 200 rowsmean capacity by vehi…40.5bus300.0train35.0tram189.5metro

    A transportation dashboard

    The is_holiday rate, capacity by vehicle_type and a breakdown of route_id. Excel, Power BI or Tableau.

  • Why do the 26 train rows have a mean capacity of 300.0?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable riderships with route_id, route_name and vehicle_type to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 15 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows15 columns
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blueprint · transportation-ridership-heatmap-data

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Include route ID and timestamp
  • Track passenger counts per stop
  • Segment by time of day
  • Flag peak demand periods
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
transportation-ridership-heatmap-data

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