How to Panel data python – An easy introduction

This tutorial introduces panel data, which tracks the same cross-sectional units, such as countries, firms or individuals, over multiple time points, and shows how to analyze it in Python. It explains that panel data offers advantages over pure cross-sectional or time-series data, including controlling for unobserved characteristics and supporting causal inference. The author demonstrates the approach with the WHO crude birth rates data set from Kaggle, which covers 239 countries and regions and is wide and unbalanced. The walkthrough uses pandas, Matplotlib, and the linearmodels library to run a pooled OLS regression of birth rates.