Students Performance Analysis with the Python Libraries Pandas, Matplotlib and Seaborn (on Open Data)

Goal

 
  • Analyzing in Detail Students Performance (from open data), from Data Processing and Cleaning to Data Visualization, with the Python libraries Pandas, Matplotlib and Seaborn.

Result

  • Several Visualization Charts (Histogrammes, Pie charts, Boxplots ect) analyzing in detail all students statistics:

           * Number of Students by each Subject Score

           * Students Scores vs Parent Education for all 3 Subjects

           * Pie Charts on several Students Statistics

           * Number of Students by Gender Passing each Subjects

           * Male and Female Scores for all 3 Subjects 

           Ect.

Examples of the work done
Number of Students By each Subject Score
Students Scores vs Parent Education for all 3 Subjects
Pie Charts on several Students Statistics
Number of Students by Gender Passing each Subjects
Male and Female Scores for all 3 Subjects

Details

Data Bring & Data Discovery
  • Student performance Data file downloaded from Kaggle site.
Data Cleaning & Data Analysis
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