28th of December 2021
Bikeshare Data Analysis Project
The program would take user input for the city (e.g. Chicago), month for which the user wants to view data (e.g. January; also includes an 'all' option), and day for which the user wants to view data (e.g. Monday; also includes an 'all' option).
Upon receiving the user input, it goes ahead and asks the user if they want to view the raw data (5 rows of data initially) or not. Following the input received, the program prints the following details:
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 (if available) The youngest user (if available) The most common birth year amongst users (if available) Finally, the user is prompted with the choice of restarting the program or not.
chicago.csv - Stored in the data folder, the chicago.csv file is the dataset containing all bikeshare information for the city of Chicago provided by Udacity.
new_york_city.csv - Dataset containing all bikeshare information for the city of New York provided by Udacity.
washington.csv - Dataset containing all bikeshare information for the city of Washington provided by Udacity. Note: This does not include the 'Gender' or 'Birth Year' data.
Language: Python 3.6 or above Libraries: pandas, numpy, time
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