Explore US Bikeshare Data

This project aims to use Python programming language to explore data related to bike share systems for three major cities in the United States - Chicago, New York City, and Washington. The project will require the user to write code that imports the data and answers interesting questions about it by computing descriptive statistics. Additionally, a script will be written to create an interactive experience in the terminal to present these statistics.

Software Requirements

To complete this project, the following software requirements apply:

• Python 3
• NumPy
• pandas, installed using Anaconda
• A text editor, like Sublime or Atom.
• A terminal application (Terminal on Mac and Linux or Cygwin on Windows).

Files used in the Project

The following files will be used in the project:

• 'chicago.csv'
• 'new_york_city.csv'
• 'washington.csv'
• 'bikeshare.py'

How to Run the Script

To run the script, open a terminal window and navigate to the project directory. Run the following command:

'python bikeshare.py'

The Code

The code is written in Python 3 and contains the following functions:

• 'get_filters()': Asks the user to specify a city, month, and day to analyze and returns the selected data.
• 'load_data(city, month, day)': Loads data for the specified city and filters by month and day if applicable. Returns a Pandas DataFrame containing city data filtered by month and day.
• 'time_stats(df)': Displays statistics on the most frequent times of travel, such as the most common month, day, and start hour.
• 'station_stats(df)': Displays statistics on the most popular stations and trips.
• 'trip_duration_stats(df)': Displays statistics on the total and average trip duration.
• 'user_stats(df)': Displays statistics on bikeshare users, such as user type, gender, and birth year.

The functions above are called in the main function 'main()', which presents an interactive experience to the user by asking questions and presenting the results based on the user's choices.