A data analysis project exploring students’ performance in Math, Reading, and Writing using Python.
This project aims to:
Understand score patterns
Identify performance trends
Explore correlations
Visualize gender-wise and course-wise differences
Analyze factors affecting students’ scores
Rows: 1000
Columns: 8
Contains students’ demographic and academic information.
Python
Pandas
NumPy
Matplotlib
Seaborn
Jupyter Notebook
✔ Data Cleaning ✔ Handling Missing Values ✔ Duplicate Removal ✔ Statistical Summary ✔ Visual Explorations ✔ Correlation Analysis ✔ Final Insights
Gender Distribution
Average Scores by Gender
Effect of Test Preparation Course
Correlation Heatmap
Maths Score Histogram
(Graphs are available inside notebook)
Math, reading, and writing scores are highly correlated.
Students who completed test preparation courses perform better.
Female students perform slightly better in reading and writing.
Parental education has a positive impact on performance.