/PyBer_Analysis

Primary LanguageJupyter Notebook

PyBer_Analysis

Project Overview

This project we will be creating visualizations of rideshare data for PyBer to help improve access to ride-sharing services and determine affordability for underserved neighborhoods.

Results

Urban city rides dominates in terms of total fares (63%), total rides (68%) and total drivers (81%). Suburban city rides came in second with total fares (31%), total rides (26%) and total drivers (17%). Coming in last is rural city rides with total fares (7%), total rides (5%) and total drivers (3%). Surprising even with lower driver counts and total rides in rural rides, the average fare is $5 higher than suburban city rides and $11 more than urban city rides.

For additional findings please refer to the following figures:

Summary

Our recommendations for our CEO, V. Isualize, for addressing any disparities among the city types are:

  • The averae number of rides in rural cities is 4 times lower than urban cities and 3.5 times lower than suburban city.
  • The average fare for rides in rural cities is $5 more than suburban cities and $11 more than urban cities.
  • The average number of driver for rural cities is 32 less than urban cities and 22 less than suburban cities. This is the biggest contributer for higher average fare in rural cities.