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Data analysis of 2 electric scooter (rental) mobility companies with a goal to compare the operational metrics of both companies as well as to estimate the number of scooters they are operating

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prakashperiasamy/escooter_rental_rideshare

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escooter_rental_rideshare

Data analysis of 2 electric scooter (rental) mobility companies with a goal to compare the operational metrics of both companies as well as to estimate the number of scooters they are operating. Data source: https://data.louisvilleky.gov/dataset/dockless-vehicles Analysis Description: Performed data cleaning via univariate analysis, metric analysis as part of EDA, data visualization via

  1. temporal analysis (peak ride demand by day of week and time of day) and
  2. spatial analysis (using origin-destination latitude and longitude positions).

● Key Summary:

  1. 1.5x to 2x difference in operations between 2 companies
  2. 12-6 PM on Weekends is when the rental demand peaks for both companies
  3. Casual/recreational is the rider persona
  4. 30 to 120 is the estimated scooter count based on overlapping trip logic

Programming Language: R (tidyverse package ecosystem) Report: R markdown (hyperlinked with table of contents) Decks: A PDF report with key summary is presented here as well

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Data analysis of 2 electric scooter (rental) mobility companies with a goal to compare the operational metrics of both companies as well as to estimate the number of scooters they are operating

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