Student Clustering System using Python + Machine Learning (on CGPA)

Student Clustering System using Python + Machine Learning (on CGPA)

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Student Clustering System

Project Summary

The Student Clustering System is a web app made using Python and Machine Learning. It groups students based on their CGPA and other number-based data. The app is built with Streamlit, which makes it easy to use.Users can upload a CSV file with student info, and the system will use KMeans clustering to group them. The results are shown in tables and charts, and you can also download the output directly. It’s a good project for learning how ML works with real data.

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 Technologies Used

  • Python
  • Streamlit – Web Interface
  • Pandas – Data Manipulation
  • scikit-learn – For KMeans Clustering & Data Scaling
  • Seaborn / Matplotlib – Data Visualizations

Project Flow: Step-by-Step

1. Upload CSV File

  • User uploads a .csv file.
  • The system previews the data and filters only numeric columns for clustering.

2. Configure Clustering

  • A slider allows the user to select the number of clusters (K).
  • Data is standardized using StandardScaler.
  • KMeans algorithm clusters the data.
  • A new column Cluster is added to the dataset showing cluster labels.

3. Show Clustered Data

  • The table with clusters is displayed.
  • Users can download the clustered data as a CSV file.

4. Visualizations (Charts)

The system generates four types of visualizations to interpret the clusters:

  • Bar Chart – Cluster Sizes: Shows the number of students in each cluster.
  • Scatter Plot: Plots the first two numeric features, color-coded by cluster.
  • Pie Chart: Represents the distribution of a selected numeric feature across clusters.

5. Cluster Info (Descriptions)

Interpretations based on CGPA:

  • Cluster 0: Low CGPA (below 6.5)
  • Cluster 1: Average CGPA (6.5 – 8.0)
  • Cluster 2: High CGPA (above 8.0)

Key Features

  • Upload any student-related CSV with numeric features
  • Automatically selects numeric columns
  •  KMeans clustering with customizable number of clusters
  •  Four interactive charts to visualize results
  •  Downloadable clustered data
  •  Works with all types of academic datasets (not limited to CGPA)

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    Screenshot-2025-05-07-112052-1024x496 Student Clustering System using Python + Machine Learning (on CGPA)
    Screenshot-2025-05-07-112100-1024x499 Student Clustering System using Python + Machine Learning (on CGPA)
    Screenshot-2025-05-07-112122-1024x479 Student Clustering System using Python + Machine Learning (on CGPA)
    Screenshot-2025-05-07-112149-1024x470 Student Clustering System using Python + Machine Learning (on CGPA)

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