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 |
---|---|---|---|---|---|
Trinity | Nagasandra | 44 | 18 | Mon | 2025-08-11 |
Chickpete | Silk Institute | 27 | 17 | Wed | 2025-08-13 |
Lalbagh | Baiyappanahalli | 13 | 13 | Sun | 2025-08-10 |
Hosa Road | Kudlu Gate | 10 | 9 | Sun | 2025-08-17 |
Seetharampalya | Yelachenahalli | 7 | 20 | Fri | 2025-08-01 |
Halasuru | Yelachenahalli | 4 | 15 | Thu | 2025-08-07 |
Majestic | Sri Sathya Sai Hospital | 3 | 6 | Mon | 2025-08-04 |
Whitefield (Kadugodi) | Whitefield (Kadugodi) | 3 | 8 | Wed | 2025-08-06 |
BTM Layout | BTM Layout | 3 | 22 | Sat | 2025-08-16 |
Garudacharpalya | Silk Institute | 2 | 17 | Thu | 2025-08-14 |
KR Market | Manjunathanagara | 2 | 20 | Wed | 2025-08-13 |
Kengeri Bus Terminal | Chickpete | 2 | 7 | Fri | 2025-08-15 |
Cubbon Park | Thalaghattapura | 1 | 10 | Fri | 2025-08-01 |
Sri Sathya Sai Hospital | Singasandra | 1 | 18 | Sat | 2025-08-16 |
Jalahalli | RR Nagar | 1 | 6 | Mon | 2025-08-11 |
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

300 People
Travelled from Benniganahalli to Majestic

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