https://github.com/priyanka7411/student-performance-tracker

A web application built with Streamlit to track and visualize student performance based on various demographic and academic attributes.
https://github.com/priyanka7411/student-performance-tracker

csv file-upload json matplotlib pandas pickle pip plotly streamlit txt webapplication

Last synced: 5 days ago
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A web application built with Streamlit to track and visualize student performance based on various demographic and academic attributes.

• Host: GitHub
• URL: https://github.com/priyanka7411/student-performance-tracker
• Owner: priyanka7411
• License: mit
• Created: 2024-12-29T08:00:27.000Z (6 days ago)
• Default Branch: main
• Last Pushed: 2024-12-29T08:32:14.000Z (6 days ago)
• Last Synced: 2024-12-29T09:17:09.708Z (6 days ago)
• Topics: csv, file-upload, json, matplotlib, pandas, pickle, pip, plotly, streamlit, txt, webapplication
• Language: Python
• Homepage: https://github.com/priyanka7411/Student-Performance-Tracker
• Size: 905 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Student-Performance-Tracker

## Overview

The Student Performance Tracker is a data-driven web application built with Streamlit, Python, and Pandas to track and visualize the performance of students based on various attributes. It allows users to upload a CSV file containing student data, filter the dataset, perform basic data analysis, and visualize key insights such as the relationship between student performance and demographic factors.

## Features

CSV File Upload: Upload your student dataset in CSV format for analysis.

Data Filtering: Filter data based on gender, race/ethnicity, and other parameters.

Data Visualization: Visualize student performance using bar charts, pie charts, and line plots.

Save Filtered Data: Save the filtered dataset to a CSV file for further use.

Interactive UI: Easy-to-use Streamlit interface to interact with the dataset.

## Technologies Used

Python 3.x: Programming language used for data processing and analysis.

Streamlit: Framework for building the interactive web application.

Pandas: Data manipulation and analysis library.

Matplotlib & Seaborn: Libraries for creating visualizations.

CSV: Data format used for input and output.

## Installation

To run this project on your local machine, follow these steps:

1. Clone the repository: git clone https://github.com/your-username/Student-Performance-Tracker.git

2. Navigate to the project directory:cd Student-Performance-Tracker

3. Install the required dependencies:pip install -r requirements.txt

4. Run the Streamlit application:streamlit run src/streamlit_app.py

## Usage

Upload your student dataset: Click on the "Choose a CSV file" button to upload the student data.

Filter the data: Select filters like gender, race/ethnicity, etc., to see the data based on those filters.

Visualize the data: View visualizations like bar charts and pie charts to analyze student performance.

Save filtered data: Click the "Save Filtered Data" button to save the modified dataset.

## Dataset

(https://www.kaggle.com/datasets/spscientist/students-performance-in-exams)

## Contributing

Fork the repository.

Create a new branch for your feature or bug fix.

Make the necessary changes.

Commit your changes and push to your forked repository.

Submit a pull request with a detailed explanation of your changes.

## License

This project is open-source and available under the MIT License.

## Acknowledgements

Streamlit: Framework used to build the web application interface.

Pandas: Library used for data manipulation and analysis.

Matplotlib & Seaborn: Libraries used for data visualization.