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data science HW - 1 week Load the BART demand data for years 2017 and 2018 from http://64.111.127.166/origin-destination/ This data represents hourly demand for BART public transport for each Origin-Destination pair. Using any resources you can find, answer these questions with a jupyter notebook: A) Plot the average daily (from 0 to 24h) rideship pattern, averaging all O-D pairs. Comment the peaks. B) Plot the hourly rideship for 2 years (hour by hour for 2 years) for the 5 highest average rideship O-D pairs. C) Plot the distribution of the trains travelled between disctricts (NOT O-D pairs). We'd like to see yearly rideship or average per hour. The district map can be found here: https://www.bart.gov/about/bod/districts . Additional points for a Chord plot usage. D) BONUS: try to create a demand prediction model. Feel free to google any missing information, plot any interesting / intermediate findings. Use any library you like. When you're finished, send us your jupyter notebook with code and analysis results.
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Applied Data Scientist

Interviewed at Hyperloop One

3.2★
Apr 13, 2020

data science HW - 1 week Load the BART demand data for years 2017 and 2018 from http://64.111.127.166/origin-destination/ This data represents hourly demand for BART public transport for each Origin-Destination pair. Using any resources you can find, answer these questions with a jupyter notebook: A) Plot the average daily (from 0 to 24h) rideship pattern, averaging all O-D pairs. Comment the peaks. B) Plot the hourly rideship for 2 years (hour by hour for 2 years) for the 5 highest average rideship O-D pairs. C) Plot the distribution of the trains travelled between disctricts (NOT O-D pairs). We'd like to see yearly rideship or average per hour. The district map can be found here: https://www.bart.gov/about/bod/districts . Additional points for a Chord plot usage. D) BONUS: try to create a demand prediction model. Feel free to google any missing information, plot any interesting / intermediate findings. Use any library you like. When you're finished, send us your jupyter notebook with code and analysis results.

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