Exploration, cleaning, visualization, and statistical inference with Pandas, Seaborn, and Matplotlib.
Compatible files: .csv, .xlsx, .parquet, .ipynb, .py
Exploratory analysis of PM2.5, CO, and NO₂ levels using public datasets from the World Air Quality Index.
Correlation analysis of search terms like “depression” and “anxiety” using Google Trends data.
Monthly price evolution of rice, potatoes, and eggs using Google Finance and public datasets.