🚲 Washington DC Bike Dataset Analysis and Prediction Application

This is a Streamlit application that allows users to explore the Washington DC Bike Dataset and showcases the modeling process for predicting the number of users per hour on a given day. The app includes two main sections: exploratory data analysis (EDA) and predictive modeling.

Access the App here

Installation

To run the app, you need to have Python 3.7 or higher installed. You also need to install the required packages listed in the requirements.txt file. You can do this by running the following command in your terminal:

pip install -r requirements.txt

Usage

To start the app, run the following command in your terminal:

streamlit run MainApp.py

This will open a new tab in your web browser, where you can interact with the app. The main sections of the app are:

• Data Exploration: this section allows you to explore the Washington DC Bike Dataset and get insights into its features and distributions.

• Predictive Model Building: this section showcases the modeling process for predicting the number of users per hour on a given day.

• Live Prediction: this tab allows you to input feature values and get a real-time prediction of the number of users per hour.

License

This project is licensed under the MIT License - see the LICENSE file for details.