Learning how to Visualize CSV Data

This project started as a school assignment, where the task was to visualize public data from two CSV files (Comma Separated Values) in a meaningful way. Initially, I was focused on creating some basic visualizations that would help users understand trends and patterns in the data. It seemed like a straightforward assignment to practice using standard web technologies.

However, as I dove into the project, I realized I wanted to go beyond the basics. Why stop at 2 datasets? I tried my hand at 3. Instead of just producing static charts, I created an interactive web application that would allow users to truly engage with the data. I decided to push again and incorporate dynamic maps to show how data is distributed across Chicago, and I used D3.js to build charts that users could interact with and filter in real-time.

What started as a simple school project quickly grew into something much more. I ended up creating a tool that not only visualizes data but also helped me to discover some insights on Chicago for my own. (don’t bike near district 42) This project became a way for me to bring data to life, transforming an interesting assignment into a powerful, enjoyable experience that I’m proud of.

Try me out

Features:

Interactive Map Visualization:

  • CSV Data on Map: Display public data from Chicago on a map, allowing users to visualize and explore the geographical distribution of the data.

  • Dynamic Interaction: Users can interact with the map to view detailed information about specific data points.

D3.js Charts:

  • Dynamic Charts: Generate dynamic, interactive charts using D3.js to represent various datasets, providing clear and insightful visualizations.

  • Data Filtering: Users can filter data directly on the charts to explore specific subsets of information.

Technologies Used:

  • D3.js: A powerful JavaScript library used for creating dynamic and interactive data visualizations in the form of charts and graphs.

  • Leaflet.js: A JavaScript library used for creating mobile-friendly interactive maps, enabling the visualization of CSV data on a map.

  • CSV & JSON: Data is stored and managed in CSV and JSON formats, ensuring compatibility and ease of use for data visualization.

Check it out in Github
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