Data Visualization App

Overview

This Streamlit app lets you pick a statistical distribution, plot it, and change the parameters to see how the shape moves. I built it with Streamlit, Plotly, and NumPy as a way to learn the distributions by playing with them instead of reading about them.

DataVisOverview

App Screenshot

Why Use This App?

  • Learn by Doing: Experimenting with different data distributions helps build an intuitive understanding of statistical concepts.
  • Enhance Data Literacy: Visualizing data in various forms allows users to recognize patterns and anomalies quickly.
  • Bridge Theory and Application: Students and professionals can use this tool to reinforce theoretical knowledge with real-time visualization.
  • Quick Prototyping: Analysts and data scientists can generate and visualize distributions instantly without writing complex scripts.

DataVisWhy

How It Works

  1. Select a Data Type: Choose from a range of statistical distributions.
  2. Adjust Data Size: Use the slider to set the number of data points.
  3. Choose a Visualization: Pick from various chart types.
  4. Explore the Data: View a brief summary and interactive visualization.
  5. Refresh Data: Generate a new dataset at any time.

Try It Yourself

Open Live Demo

Features

  • Dynamic Sidebar Controls
    • Toggle sidebar state for better user experience
    • Select different data types including Normal, Non-Normal, Random, Linear, Exponential, Poisson, Gamma, and Skewed
    • Adjust the sample size with an interactive slider
    • Choose from multiple visualization types: Histogram, Line Chart, Scatterplot, Heatmap, Box and Whisker Plot, and Bar Chart
  • Data Generation
    • Uses NumPy to generate various types of distributions
    • Provides a brief summary of each distribution type to enhance learning
  • Data Visualization
    • Uses Plotly to create interactive charts
    • Automatically updates charts based on user input
  • Additional Features
    • Refresh data functionality to generate new samples
    • GitHub link to source code
    • Footer crediting ChatGPT for assistance in development

Technologies Used

  • Streamlit: For building the interactive web-based application
  • Plotly: For creating dynamic visualizations
  • NumPy: For generating statistical data distributions
  • Pandas: For handling data transformations
  • Streamlit Components: For embedding custom HTML elements

Live Demo & Source Code

Check out the source code on GitHub: beautifulcharts

Screenshots

App Screenshot_1

App Screenshot_2

Note: See the details on GitHub, beautifulcharts.