31st August 2020
Bikeshare Data Exploration using Pandas library
This program enables users explore bikeshare data from three US cities - Washington, New York City and Chicago.
The program takes user's input for the city name, month and day for which the user wants to view data. There's an option to select 'all' instead of specifiying month and day to skip the filter.
Following user input, the user gets presented with the following data -
Most popular month Most popular day Most popular hour Most popular start station Most popular end station Most popular combination of start and end stations Total trip duration Average trip duration Types of users by number Types of users by gender (if available) The oldest user's birth year (if available) The youngest user's birth year (if available) The most common birth year amongst users (if available)
The user is prompted with the choice of displaying the raw data 5 lines at a time, and finally given a choice to restart the program.
washington.csv chicago.csv new_york_city.csv
I consulted this repo for help with writing this https://github.com/Aritra96/bikeshare-project/blob/master/bikeshare.py