average number passengers a day using the Yamanote Line

  • Last Update:October,29,2019 Created:October,29,2019
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Title of the dataset average number passengers a day using the Yamanote Line
Provenance of the dataset JR East, and any purchasers
How were the data collected/created? What was the cost? The data is collected by tracking the number of entrances, whether by paper ticket or IC card, through the fare gates.
Data sharing policy Shareable for research purpose
Data sharing policy perhaps this data can be shared for research purposes regarding traffic and how to create better public transportation

About data analysis and simulation

Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. graph number series
Variable labels of dataset (the names of the variables) month | year | avg number of passengers
Outline of data This data contains the monthly average number of passengers entering a station on the Yamanote Line in one day. There is a data point for each month (January, February, etc.) for the past 10 years (1999 - 2019), organized by each station on the line.
Simulation process We may want to use some simulation to estimate how many people will be using the Yamanote Line during big events such as the Olympics. We want to analyze why certain times of the year may have more or less passengers. We may also want to see how population change in Tokyo has affected the usage of the Yamanote Line.
Expected outcome of the process (obtained knowledge, analysis results, output of tools) If there are past events we can correlate with more or less traffic in the Yamanote Line, it may be possible to predict how certain events will affect the traffic in the future.
Anticipation for analyses/simulations other than the typical ones provided above Predicting which stations will have more traffic may also allow for analysis concerning when and where to place advertisements in train stations.

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What kind of data/tools do you wish to have? an easy way to input a station and see its past history of average ridership, using the data from my dataset
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Sample data

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