Bixi Bike Sharing Project
This repository contains the code and resources for a project focused on analyzing Bixi bike sharing data. The project aims to explore the dataset, determine relationships between variables, predict the end station of a Bixi ride, and visualize the findings.
Project Overview
The project is structured into four main deliverables:
- Exploratory Research using SQL Objective: Conduct exploratory research on the Bixi bike sharing dataset using SQL. Tasks: Clean and format the data for further analysis. Files: SQL scripts for data cleaning and exploration.
- Relationship Analysis using Python Objective: Utilize Python for determining relationships between various data points in the Bixi dataset. Tasks: Perform statistical analysis, correlation assessments, and identify patterns. Files: Python scripts and notebooks for relationship analysis.
- Prediction of Bixi Ride End Stations Objective: Develop a predictive model to determine the end station of a Bixi ride. Tasks: Machine learning-based prediction using Python. Files: Python scripts or notebooks showcasing the prediction model.
- Data Visualization Objective: Create visual representations of the analyzed data and prediction results. Tasks: Use various visualization libraries to present findings effectively. Files: Python scripts or notebooks generating visualizations. Usage
Each deliverable is organized into separate directories within this repository. Detailed documentation and instructions for each section are provided within the respective directories.
Requirements
SQL database or tool for executing SQL scripts. Python environment with necessary libraries (Pandas, Matplotlib, Seaborn, Scikit-learn, etc.). Contributors
Jacques Sika -