Bikeshare Data Analysis Project

Date Created

26/09/2023

Overview

This Python Bikeshare Data Analysis project is designed to explore and analyze bikeshare data from three major cities: Chicago, New York City, and Washington. The project includes a Python script that allows users to interactively explore various aspects of the bikeshare data, such as popular stations, trip duration statistics, and user demographics.

Table of Contents

• Requirements
• Installation
• Usage
• Project Structure

Requirements

To run this project, you will need the following software and libraries:

• Python 3.x
• Pandas

Installation

1. Clone the repository to your local machine using the following command:

   git clone git@github.com:Ravencodess/pdsnd_github.git
   

2. Navigate to the project directory:

   cd /path/to/project/directory
   

3. Install the required Python libraries using pip:

   pip install pandas 
   

Usage

1. Run the bikeshare.py script to start the bikeshare data analysis tool:

   python bikeshare.py
   

2. Follow the on-screen prompts to select a city and specify filtering options (by month, day, or both).

3. Explore the bikeshare data by viewing statistics on popular stations, trip durations, user types, and more.

4. Optionally, view raw data in chunks of 5 lines at a time.

5. When you're done, you can restart the program or exit.

Project Structure

The project directory structure is organized as follows:

        bikeshare-analysis/
    │
    ├── bikeshare.py         # Main Python script for data analysis
    ├── bikeshare.jpg        # Project image
    ├── README.md            # Project README file
    │
    └── (other project files and directories)

For becoming well versed in Git commands I read the official VsCode Git docs https://code.visualstudio.com/docs/sourcecontrol/intro-to-git For Documentation for basic pandas DataFrame creation and indexing I used the official docs: https://pandas.pydata.org/pandas-docs/stable/user_guide/ For Linting and Formatting I used the pep8 extension on Vscode For Doc string reviewing and corrections I referred to ChatGPT : https://chat.openai.com For setting up my Linux environment on vscode I used the official docs: https://code.visualstudio.com/docs/remote/wsl