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For our Data Analyst final project, we analyzed taxi and public transport data in New York for Worten. We used Python for data prep, SQL Server and Navicat for management, R and Excel for analysis, and Power BI for the dashboard. This approach provided valuable insights and answered the client’s questions effectively.

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Anacatarinapinheiro/Worten_Project-NYC_Taxi_Limousine_Commission

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Worten - Taxi & Limousine Commission Project

Welcome to our final project for the Data Analyst course! Our client, Worten, commissioned us to perform a comprehensive analysis of taxi and other transportation distribution across New York State. This included services like Uber, Lyft, Bolt, and others.

Project Overview

Our goal was to understand the distribution patterns of these services and deliver actionable insights. Here's a breakdown of the tools and methodologies we used to achieve this:

Tools and Technologies

  • Python: For initial data conversion and preliminary analysis.
  • SQL Server & Navicat: For querying and managing the data.
  • R & Excel: For in-depth data analysis and visualization.
  • Power BI: To create an interactive and detailed dashboard.

Approach

  1. Data Collection and Conversion: We used Python to prepare the data for analysis.
  2. Data Management: SQL Server and Navicat helped us efficiently manage and query the data.
  3. Analysis and Visualization: R and Excel provided powerful tools for analyzing and visualizing the data.
  4. Dashboard Creation: Power BI allowed us to build a user-friendly and comprehensive dashboard to present our findings.

Results

Our methodical approach enabled us to answer the client's questions effectively and deliver valuable insights through a well-designed dashboard. We hope this project provides a clear understanding of transportation patterns and aids in strategic decision-making.

SQL Queries and Data Analysis for NYC Taxi & Limousine Commission Project

Open the Project Report PDF

Interactive Dashboard

Interactive Dashboard

Feel free to explore the repository and reach out if you have any questions or feedback!

About

For our Data Analyst final project, we analyzed taxi and public transport data in New York for Worten. We used Python for data prep, SQL Server and Navicat for management, R and Excel for analysis, and Power BI for the dashboard. This approach provided valuable insights and answered the client’s questions effectively.

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