GeoDevelopment Observatory of Bolivia / Tools
expdpy: explore and model panel data
A companion package for panel data: within/between variation, trajectories and transitions, then pooled, fixed and random effects, Hausman tests and clustered standard errors, each with a plain-language reading.
expdpy (a Python port of ExPanDaR) turns the everyday steps of panel-data research into single functions. Explore functions describe a panel’s structure, decompose variation into between and within components (xtsum), and chart trajectories, distributions, transitions, missing values and correlations. Analyze functions estimate pooled, between, fixed-effects, random-effects and correlated-random-effects models, run Hausman and joint tests, fit fixest-style regressions with fixed effects and clustered or Driscoll–Kraay standard errors, and cover IV, event studies and β-, σ- and club convergence. Learn functions simulate each concept from a known truth. Every result has an interactive figure or table and an interpret() method. The observatory’s datasets are exactly the long panels expdpy expects: geo.for_expdpy() hands them over, labeled, in one line.