Student Performance Dataset

Student Grade Prediction
Dataset

A student performance dataset from the UCI Machine Learning Repository, containing student data for mathematics and Portuguese courses in Portuguese secondary schools, covering 33 demographic, social, and school-related features, suitable for educational data mining research.

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1,044 samples 33 features CC BY 4.0 license P. Cortez (2014)
Student Performance Dataset
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1,044
Total Samples
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33
Feature Dimensions
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2
Subject Data
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CC BY 4.0
Open License Agreement

Dataset Highlights

Rich educational datasets suitable for social science and educational data mining

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Real Educational Data

Data comes from real student records of two high schools in Portugal, including three exam scores (G1, G2, G3).

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Social Factors

Includes rich social background information such as family size, parents' occupations, parents' education levels, and family relationships.

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Behavioral Characteristics

Includes students' behavioral characteristics such as drinking frequency on weekdays and weekends, frequency of going out, and health status.

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Dual Subject Data

Provides independent datasets for mathematics and Portuguese courses, allowing for cross-disciplinary comparative analysis.

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Regression and Classification

Scores G3 can be used as continuous values for regression or grouped for classification (pass/fail).

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UCI Authoritative Source

Originates from the UCI Machine Learning Repository, published in an academic paper by P. Cortez et al.

Applicable Scenarios

Rich application scenarios from grade prediction to social factor analysis

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Grade Prediction

Predict students' final grades based on social and behavioral characteristics, practicing regression and classification algorithms

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Factor Analysis

Analyze which family and social factors most affect student performance, discovering educational patterns

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Comparative Study

Compare the differences in factors affecting grades in mathematics and Portuguese courses

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Exploratory Analysis

Visualize the relationship between social factors and academic performance, suitable for educational data EDA

Educational Data Regression Prediction Social Science Behavior Analysis Multi-Feature

Data Preview

The following are examples of the first few rows of the student math scores dataset

CSV
school,sex,age,address,famsize,Pstatus,Medu,Fedu,Mjob,Fjob,...,G1,G2,G3
GP,F,18,U,GT3,A,4,4,at_home,teacher,...,5,6,6
GP,F,17,U,GT3,T,1,1,at_home,other,...,5,5,6
GP,F,15,U,LE3,T,1,1,at_home,other,...,7,8,10
GP,F,15,U,GT3,T,4,2,health,services,...,15,14,15
GP,F,16,U,GT3,T,3,3,other,other,...,6,10,10

3 Steps to Get Started

From browsing to analysis, you can start your data science project in just a few minutes

01

Browse the Dataset

View dataset details on the Ace Data Cloud platform, understand field descriptions, sample size, and licensing agreements.

02

Download Data

Download the two CSV files for math (42 KB) and Portuguese (69 KB).

03

Load and Analyze

Use pandas.read_csv() to load the data and start exploring the relationship between social factors and scores.

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Start Exploring Student Score Data

A classic educational dataset with open licensing, available for immediate download. 33 social and behavioral features make it an ideal choice for educational data mining and social science analysis.

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