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How Bangalore Uses the metro
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Challaghatta
ವೈಟ್‌ಫೀಲ್ಡ್ (ಕಾಡುಗೋಡಿ)
Whitefield (Kadugodi)
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Vivek Matthew & Aman Bhargava
Published

On 10th August 2025, Bangalore’s Yellow Line metro was inaugurated, connecting to , and serving the major tech hub of . A week later, we filed a Right to Information (RTI) request with the Bangalore Metro Rail Corporation Limited (BMRCL) for data on hourly ridership at each station, from August 1st to 18th.

RTI Application Status

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CEG-Karnataka Govt. RTI WING

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Tue, Aug 19, 2025, 6:53 PM

Please note your Transaction ID for any future verification process.

Transaction ID
BMRCLR20250000000XXX

CEG-Karnataka Govt. RTI WING

to me

Tue, Aug 19, 2025, 6:54 PM

Your RTI Request has been filed with the following details for future reference.

Registration No.
BMRCL/R/2025/XXXXX
Registered Email
hello@diagramchasing.fun

A month later, BMRCL responded with the requested data. The data includes over 1.2 million rows of data, detailing the number of passengers between each pair of metro stations, at each hour of the day, on each of 18 different days. Here’s a sample of what the data looks like.

Origin
Destination
Commuters
Hour
Day
Date
TrinityNagasandra4418Mon2025-08-11
ChickpeteSilk Institute2717Wed2025-08-13
LalbaghBaiyappanahalli1313Sun2025-08-10
Hosa RoadKudlu Gate109Sun2025-08-17
SeetharampalyaYelachenahalli720Fri2025-08-01
HalasuruYelachenahalli415Thu2025-08-07
MajesticSri Sathya Sai Hospital36Mon2025-08-04
Whitefield (Kadugodi)Whitefield (Kadugodi)38Wed2025-08-06
BTM LayoutBTM Layout322Sat2025-08-16
GarudacharpalyaSilk Institute217Thu2025-08-14
KR MarketManjunathanagara220Wed2025-08-13
Kengeri Bus TerminalChickpete27Fri2025-08-15
Cubbon ParkThalaghattapura110Fri2025-08-01
Sri Sathya Sai HospitalSingasandra118Sat2025-08-16
JalahalliRR Nagar16Mon2025-08-11

The timing of the data captures the impact of the eagerly awaited (and much delayed) Yellow Line. Before the Yellow Line, the city’s network consisted of the west-east Purple Line and the north-south Green Line, which intersect at . The Yellow Line connects to the Green Line at , adding a second interchange to the city, and connecting to the rest of the city’s metro network. Overlaying the metro network on the city’s urban fabric shows how each line connects areas of varying urban growth and use, from the dense central business district, to various secondary business districts, and developing peripheries.

Shaded areas show commercial or industrial areas. Darker shades indicate higher density.

The granularity of the data helps us understand travel patterns in new ways. For example, in the week following the opening of the Yellow Line, only one person travelled from to . That sole trip was made at 5 PM on August 14th, an hour during which over 300 people travelled from to .

1 Person

Travelled from Beratena Agrahara to Mysore Road

Single traveler

300 People

Travelled from Benniganahalli to Majestic

Crowd of travelers

Which parts of the city have been the most enthusiastic about the Yellow Line? has seen it’s average daily ridership increase by nearly 40% since the Yellow Line was opened. On the other hand, a fall in ridership is seen at stations like and , popular locations to board BMTC buses bound for and surrounding areas. Before the Yellow Line, for a person living near and working in , the metro covered only a minor part of the journey. Now that the Yellow Line has opened, many such commuters can switch to the metro for a majority of the journey. Overall, Purple Line stations saw a minor impact compared to Green Line stations.

This chart shows the percentage change in ridership for metro stations after the Yellow Line opened. Most stations saw increases, with the largest increase being +38.7% at Lalbagh.

Change in Ridership (%)020 LalbaghManjunathanagaraMajesticJalahalliNagasandraRV RoadGoraguntepalyaSandal Soap FactoryBanashankariChickpete scale type mismatch for y (needs band) Chickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow LineChickpete and Banashankariconnect to buses for areasnow served by Yellow Line +38.7%+27.0%+26.3%+22.6%+22.2%+17.8%+16.3%+6.9%-12.9%-13.9%

On the other hand, when looking at footfall within stations, the impact on is immediately noticeable. From previously being one of the lower footfall stations on the network, to now being the sole interchange point between the Yellow Line and the rest of the network, footfall has increased from the earlier 15,000 passengers to now over 75,000 passengers per day. The increase in footfall at has been more moderate, from 1.8 lakh to 2.1 lakh passengers per day.

This visualization shows the footfall at Rashtreeya Vidyalaya Road station before and after the Yellow Line opening. Each row represents 1,000 people. Before: 15076 people, After: 75366 people.

Daily footfall at RV Road before Yellow Line and after Yellow Line Each row represents 1,000 people
BeforeAfter

The week following the opening of the Yellow Line also coincided with multiple events in the city, including Independence Day celebrations and the Lalbagh Flower Show, which brought additional people to stations like and . The largest unusual spike in ridership was observed on August 16th, coinciding with Krishna Janmashtami, which brought many people to ISKCON, near .

This chart shows daily ridership patterns for three major metro stations during a significant period in August 2025. Key findings:

  • Mahalakshmi station (Orange line) shows consistent high ridership
  • Lalbagh station (Green line) demonstrates steady usage patterns
  • Dr. B. R. Ambedkar Station shows significant variations during special events
  • Yellow Line opening on August 11th created notable ridership changes
  • Independence Day weekend (Aug 15-17) shows distinct usage patterns
Date31017 Daily Ridership0K5K10K15K20K25K ; ; ; MahalakshmiLalbaghVidhana Soudha WeekendWeekendIndependence Day weekend 25K commuters

People in the city’s peripheries tend to have longer metro commutes, and the opening of the Yellow Line has made the average commute even longer, from 10 stations earlier, to 12 stations after the Yellow Line opened. People at have the longest average commute of 18 stations, while people at have the shortest average commute of 7 stations. In terms of time on the metro each day, a commuter spends an average of 73 minutes, while a commuter spends an average of 27 minutes.

Avg. daily metro commute (min, approx)01020304050607080 MadavaraHalasuru scale type mismatch for y (needs band) scale type mismatch for y (needs band) 73 mins27 mins

Many of the most popular commutes are much shorter, like the 2nd most popular commute, from to , a 2 station commute. What is the most popular commute in the entire city? The answer is an indication for what the upcoming Blue Line has in store, as to is the most popular commute with over 2500 daily commuters.

How popular is your usual commute?

Select a pair of stations to see how many people usually travel that route on a given day

Benniganahalli Majestic
2,588
Sri Sathya Sai Hospital Kadugodi Tree Park
1,965
Kadugodi Tree Park Sri Sathya Sai Hospital
1,938
Benniganahalli Indiranagar
1,632
Yeshwantpur Majestic
1,577
Indiranagar Benniganahalli
1,502
Majestic Benniganahalli
1,402
Banashankari Majestic
1,396
Chickpete Majestic
1,379
KR Pura Majestic
1,374
MG Road Indiranagar
1,330
Benniganahalli MG Road
1,305
MG Road Benniganahalli
1,297
Konanakunte Cross Majestic
1,278
MG Road Majestic
1,262
Majestic Yeshwantpur
1,243
Indiranagar MG Road
1,185
Jayanagar Majestic
1,182
Mahalakshmi Majestic
1,178
Halasuru MG Road
1,148
KR Market Majestic
1,130
Vidhana Soudha Majestic
1,120
MG Road Halasuru
1,119
Indiranagar Majestic
1,075
Majestic Chickpete
1,072
Dasarahalli Majestic
1,066
Whitefield (Kadugodi) Sri Sathya Sai Hospital
1,051
JP Nagar Majestic
1,029
Sri Sathya Sai Hospital Whitefield (Kadugodi)
1,027
Majestic Banashankari
1,025
Baiyappanahalli Indiranagar
1,014
Select a route

Ever wonder where do most people at a station come from and go to? More people at have commutes involving than any other station. At , there are more commutes involving than anywhere else. If you want a metro-accessible job near or , you might move to or to find neighbours who make the same commute.

How are trips involving distrbuted each day
0200400600800 0200 Benniganahalli1,514Indiranagar1,628KR Pura1,205Majestic1,112Baiyappanahalli995Halasuru1,010MG Road779KSR Railway Station780Vijayanagara803Hosahalli698Attiguppe652KadugodiTreePark540Whitefield(Kadugodi)451Seetharampalya421Trinity467MagadiRoad453Hoodi398CentralCollege436KengeriBusTerminal397Singayyanapalya424SwamiVivekanandaRoad407Nallurahalli393

The data also allows for an analysis of shared travel patterns beyond a simple ranking of the busiest routes. Since high-traffic stations naturally have high-traffic connections between them, hidden under the surface are connections that are disproportionately important to each other. This “social connectedness” is found by calculating a score for each route that accounts for the overall ridership of both the origin and destination stations. A high score indicates that the passenger flow between the two stations is significantly higher than the average station, like between and .

Where people tend to go when they board at

Loading metro network...

Same-line trips are consistently more likely than cross-line trips. The hassle of switching at an interchange means that for most stations, the strongest links are usually to stations on the same line. The few cross-line connections that do rank highly represent notable cross-line travel patterns, many of these being work commutes that disappear over the weekend, such as the commute between and . The rhythm of the metro changes in additional ways between weekdays and weekends. Weekdays show two peaks: one at 9 AM as the city gets to work, and one at 6 PM as it heads home. Weekends replace this bimodal rhythm with a single, broad wave of travel that builds from noon through evening.

Average ridership flow every hour, throughout the day on weekdays vs the weekend

This chart compares metro ridership patterns between weekdays and weekends across 24 hours. Key findings:

  • Weekday peak at 9 AM with 950+ riders (morning commute)
  • Evening weekday peak at 6 PM with 950+ riders (evening commute)
  • Weekend ridership peaks between 1-4 PM, exceeding weekday levels
  • Lowest ridership occurs overnight on both weekdays and weekends
12AM3AM6AM9AM12PM3PM6PM9PM 12AM3AM6AM9AM12PM3PM6PM9PM 05001K ; ; Weekday commutersheading to work Brown areas show whenweekdays have higherridership than weekends Weekday commutersheading back home Weekend usage peaks aboveweekdays from noon through evening
Area chart showing metro ridership by hour. Grey areas indicate where weekday ridership exceeds weekend ridership. Red areas show where weekend ridership is higher. The chart reveals typical commuter patterns with morning and evening weekday peaks, and steady weekend afternoon activity.

The hourly granularity in ridership shows that there are stations whose weekday rhythm doesn’t closely match the network-wide weekday rhythm. has consistently high ridership throughout the day. On weekdays, and wake up the earliest, while Yellow Line stations sleep the latest. On weekends, is busiest at 9PM.

How many people board at each station at each hour on

This chart shows a heatmap of ridership over time for each station for weekdays.

5AM9AM1PM5PM 5AM9AM1PM5PM Weekday Peak Hours Weekend Activity scale type mismatch for x (needs band)
Ridership share at
:00
Weekdays 0.0%
Weekends NaN%

This chart shows a heatmap of ridership over time for each station for weekends.

5AM9AM1PM5PM 5AM9AM1PM5PM Weekday Activity Weekend Peak Hours scale type mismatch for x (needs band)
Ridership share at
:00
Weekdays 0.0%
Weekends NaN%

Even the network-wide pattern of weekdays being busier than weekends has its outliers. , and might be particularly busier on weekdays, but others like and have remarkably consistent patterns between weekdays and weekends. At the other extreme, and are more popular on weekends than on weekdays. to is disproportionately popular on weekdays, while to is disproportionately popular on weekends.

Similar ridership More ← weekday ridership Moreweekend →ridership
Daily ridership on
Weekday 0
Weekend 0

All the above analysis stems from a single dataset. For organizations such as BMRCL, the takeaway should be obvious, which is to release this data regularly. When data is available and covers a long period of time, it can be used to answer a much wider range of questions, more accurately and with greater detail. You can’t beat the cost of getting analysis and insights from the public, for free. If you are from BMRCL (or another government agency), please consider releasing data like this regularly.

METHODOLOGY


The source data was acquired through a Right to Information (RTI) request to BMRCL. It covers the period from August 1st to August 18th, 2025. While this includes a week after the Yellow Line opened, patterns observed from a single week cannot be used to conclusively establish the long-term impact of the line on ridership. Longer periods of data are needed to draw definitive conclusions. The week from 11th August to 18th August also coincides with other events such as Independence Day and the Lalbagh Flower Show, which may have affected ridership patterns in different ways.

The term “ridership” in this analysis refers to the number of people who passed through the fare gates at a station, or a pair of stations. Individuals who go to a station, without entering or exiting the ticketed area of the station by going through the fare gates, do not count towards ridership. As a result, interchange stations like Majestic and RV Road, where many commuters transfer without exiting the ticketed area of the station, may count towards high in-station footfall, but such commuters do not translate to ridership counts in the data.

The data analysis was largely done in R, explore the analysis notebook for more details. Mapping of station names to station locations and additional metadata was done using spatial data from OpenStreetMap. Notebook is available under the MIT License.

The frontend was built with SvelteKit, explore the frontend code for more details. The basemap was made using OpenStreetMap data. The landuse map was made using data from GHS built-up volume (R2023). Code is available under the MIT License.

Illustrations of the travellers by Reechik Bannerjee.

Claude AI was used for assistance developing certain interactive components of this project. No text was generated with an LLM.

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