-
Overview
The purpose of this analysis is to show how the data differs by city type and how those differences can be used by decision-makers at PyBer.
-
Results
We created a summary DataFrame of the ride-sharing data by city type as well as a multiple-line graph that shows the total weekly fares for each city type. By looking at the results we can tell that there is a big difference in ride-sharing amount in diffrerent city types. The average number of rides in the rural cities is much lower than urban and suburban cities, respectively, as well as the total fare.
-
Summary
Based on the results we should look into lowering prices for rural city types to potentially increase the number of rides.
lubib / pyber_analysis Goto Github PK
View Code? Open in Web Editor NEWMatplotlib charts