This repository contains my solutions to the five mandatory projects required for the freeCodeCamp Data Analysis with Python Certification.
These projects showcase my ability to manipulate data, perform statistical analysis, and create meaningful visualizations using Python and its core data analysis libraries.
View My Official Certification
- Language: Python
- Libraries: NumPy, Pandas, Matplotlib, Seaborn, SciPy
- Concepts Covered:
- Data Cleaning & Filtering
- Statistical Analysis (mean, variance, std dev, correlations)
- Data Visualization (box plots, scatter plots, line charts, heatmaps)
- Time Series Analysis
- Linear Regression & Prediction
| Project | Challenge Focus | Key Achievement |
|---|---|---|
| 1. Mean-Variance-Std Dev Calculator | NumPy | Calculated and structured seven statistical measures on a 3x3 matrix using efficient NumPy operations. |
| 2. Demographic Data Analyzer | Pandas | Explored U.S. census data with Pandas, calculating statistics on race, education, work hours, and income. |
| 3. Medical Data Visualizer | Pandas & Seaborn | Created a categorical plot and correlation heatmap to analyze patient medical records and lifestyle factors. |
| 4. Page View Time Series Visualizer | Pandas & Matplotlib | Cleaned time series data, then visualized long-term trends and seasonality with line plots and box plots. |
| 5. Sea Level Predictor | Pandas & SciPy | Applied linear regression (scipy.stats.linregress) to model sea level rise and predict values through the year 2050. |
Here are a few example outputs from the projects:
Medical Data Visualizer – Correlation Heatmap
Page View Time Series Visualizer – Box/Bar Plot
Sea Level Predictor – Linear Regression Projection
