Note: Please fork the current Udacity repository so that you will have a remote repository in your Github account. Clone the remote repository to your local machine. Later, as a part of the project "Post your Work on Github", you will push your proposed changes to the remote repository in your Github account.

Date created

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Project Title

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Description

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Files used

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Credits

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add bikeshare

First, you'll fork a repository to get your own copy of a template for this project, and then clone it to your local computer. Your first task will then be to add your bikeshare.py file, data file, and a .gitignore file to exclude your data file from version control tracking. This is a common practice to avoid sharing your data publicly, to avoid tracking unnecessarily huge files on GitHub, and because changes in data don't often affect our code.

Project Overview

This project analyzes bikeshare data from three major cities: Washington, New York City, and Chicago. The analysis includes various statistics about bike usage, popular times for biking, and user demographics.

New Updates:

• Improved documentation for better understanding.
• Added line comments and docstrings in bikeshare analysis script.

Recent Updates

• Refactored the function for calculating averages to improve readability and add error handling.
• Optimized loops using list comprehensions for better performance.

add trip_duration_stats function

Displays total travel time in hours and the average trip duration in minutes. The travel times are calculated by summing and averaging the 'Trip Duration' column, which is assumed to be in seconds.

add user_stats function

Displays counts of different user types, such as Subscribers or Customers. For cities other than Washington, it shows the gender distribution and birth year statistics: The earliest, most recent, and most common birth years are calculated. Washington data does not contain gender or birth year information, so it’s skipped for this city.

add display_raw_data function

This function allows users to view the raw data 10 rows at a time by repeatedly asking if they want to see more data.