Data Download: Metrorail Ridership by Station by Month, 2010-2015
See how seasons, land use, and service drive trends in rail ridership at the station level, in this new data download.
This latest data download shows Metrorail ridership by station, by month, for the last five years or so. It hints at the complex factors driving rail ridership – from short-term effects like weather or service changes, to long-term trends like real estate development and office relocations.
We see a few tidbits in this data:
- Seasonal trends: rail ridership follows a predictable pattern each year – peaking in the summer and around Cherry Blossoms, and reaching lows around the holidays. Compare the high seasonality of Arlington Cemetery to a more commuter-oriented station, for example. Ridership in the summer at that station can quintuple over its winter base.
- Weather impacts: see how the blizzard this past January lowered the average for the month as service was shut down.
- Service changes: See how the opening of the Silver Line shifted riders from Orange to Silver in July-August 2014.
- Land Use is key! Look at the recent growth rates at stations like Navy Yard and NoMa (formerly New York Ave.), reflecting the new jobs and residences near those stations.
Metrorail Ridership, by Station by Month, 2010-2015, Average Weekday (.xlsx, 120kb)
Metrorail Ridership, by Station by Month by Period, 2010-2015, Average Weekday (.xlsx, 630kb) (Added 3/30/2016)
Notes: these numbers are raw entries for an average weekday in the month, including snow days, excluding holidays when we did not run a weekday schedule. The numbers are for trend analysis and will differ slightly from those we report in financial statements, which undergo additional data scrubbing and normalization.
What do trends you see?
Is station parking lot usage available over the same time frame?
With cash no longer accepted, the current parking pricing policy needs to change and be based on usage. Every station should be at 90% usage at 10AM and pricing such be adjusted every three months.
Examples(FY15):
Wheaton – 29%, Landover – 39% – Prince George Plaza – 46%, Addison Road – 50%, College Park – 55%, West Falls Church 66% lots should be priced cheaper.
East Falls Church – 117% should be be priced higher.
Any chance to get this broken down by time period (am peak, mid-day, pm peak, evening)? That would enable more interesting comparisons with past data.
I processed the data in a similar way to the last time I found a data dump here. I looked at this in as many ways as I could think.
1. Total average weekday ridership from 2010-2016
2. Average ridership at each station across years, month and month*year
3. Average ridership at each station for each year.
The plots are located here: http://imgur.com/a/DuEwF
If there is some other way to look at this, I would love to hear it.
@Ben Ross
Sure thing – link added above to the same data, broken out into the five time periods.
Great stuff!
Also, want the background on why Foggy Bottom is such a crowding problem? As many passengers entering/exiting as L’Enfant, Dupont, Farragut West, etc. but only one exit!
It would be useful if this data can be converted into the same type of data as below. This would permit comparisons
May 2013 and 2014 Metrorail ridership data is available: what patterns do you see?
Following up on our last data download of rail ridership from May 2012, 2013 and 2014 are now available. These data now represent three “snapshots” in time of rail ridership, at a very fine level of detail. This data can help answer questions, such as: where is ridership growth the strongest? Which destinations are becoming more or less popular? How has off-peak vs. peak ridership changed?
May 2013 Metrorail Ridership by Origin, Destination, TimePeriod, DayOfWeek (.xlsx, 3.3 MB)
May 2014 Metrorail Ridership by Origin, Destination, TimePeriod, DayOfWeek (.xlsx, 3.4 MB)
We invite you to tell us what you see, in the comments.
Technical notes on the data are the same as the last post. This time, Saturdays and Sundays are shown in the same worksheet as weekdays.