This project is an interactive Streamlit dashboard developed as part of an internship, aimed at analyzing student feedback collected on various aspects of college events such as teaching, course content, examinations, lab work, library facilities, and extracurricular activities.
- 📊 Visualize sentiment distribution for each feedback category
- 📋 Count summary of negative, neutral, and positive responses
- 📂 View the complete dataset in tabular form
- ⚡ Fast, lightweight UI built with Streamlit
The dataset used is finalDataset0.2.xlsx, sourced from Kaggle:
🔗 https://www.kaggle.com/datasets/brarajit18/student-feedback-dataset
It includes both sentiment scores (-1, 0, 1) and written feedback across various categories.
Columns include:
teaching_text,teaching_sentimentcoursecontent_text,coursecontent_sentimentexamination_text,examination_sentimentlabwork_text,labwork_sentimentlibrary_facilities_text,library_facilities_sentimentextracurricular_text,extracurricular_sentiment
Install required dependencies:
pip install streamlit pandas matplotlib seaborn openpyxlgit clone https://github.com/yourusername/college-event-feedback-analysis.git
cd college-event-feedback-analysisstreamlit run app.py- 📌 Sentiment analysis for each category
- 📈 Bar charts & visual insights
- 📄 Full dataset preview
- 🔍 Easy-to-use interactive interface
- Ensure
finalDataset0.2.xlsxis placed in the project root directory - Update file path inside the script if needed
- Works best in a modern browser
- Add NLP-based advanced sentiment analysis
- Deploy on Streamlit Cloud
- Add filtering & search options
- Integrate real-time feedback collection
Contributions are welcome! Feel free to fork this repository and submit a pull request.
Mohd Shami 📧 codexshami@gmial.com 📍 Uttar Pradesh, India
⭐ If you found this project useful, don’t forget to star the repository!