/EDA-and-DataVisualization

This app allows you to select a dataset, view its contents, explore data statistics, and generate various types of plots. It's built with Streamlit, a Python library for creating web applications with ease.

Primary LanguagePython

ML DataSet Explorer & Data Visualization with Streamlit

Link : https://edavisual.streamlit.app/

Table of Contents

Streamlit Logo

Explore and visualize your datasets interactively with this Streamlit application. This app allows you to select a dataset, view its contents, explore data statistics, and generate various types of plots. It's built with Streamlit, a Python library for creating web applications with ease.

Features

  • Dataset Selection: Choose a dataset file from a directory.
  • Data Exploration:
    • View the first few rows of the dataset.
    • Display the dataset's shape (number of rows and columns).
    • Select specific columns to display.
    • Check the value counts of the target/class variable.
    • Check for missing (null) values in the dataset.
    • View the data types of each column.
    • Explore summary statistics of the dataset.
  • Data Visualization:
    • Generate a correlation heatmap (Seaborn).
    • Create a pie chart to visualize target variable distribution.
    • Generate bar plots based on selected columns.
    • Customize and generate various types of plots (area, bar, line, etc.).
  • Fun Interaction: Click the "Thanks" button to display balloons.

Usage

  1. Clone Repository: Clone this repository to your local machine or download the code.

    git clone https://github.com/adityab24840/EDA-and-DataVisualization

  2. Install Dependencies: Install the required Python packages listed in the requirements.txt file:

    pip install -r requirements.txt

  3. Run the App: Start the Streamlit app using the following command:

    streamlit run app.py

  4. Interact with the App: The app will open in your default web browser, allowing you to explore and visualize your datasets interactively.

Author

  • Author: Aditya N Bhatt
  • Student ID: 231057017
  • Program: AI & ML, MSIS

GitHub Repository

You can find the source code for this project on GitHub.

Built With

  • Streamlit: The app is built with Streamlit, a Python library for creating web applications.