Guided Notes

Python & pandas for Healthcare Data

Why analysts add Python, loading and inspecting data with pandas, cleaning, groupby summaries, merging tables, and reproducible notebooks.

Why Python

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Excel and SQL handle most daily work, but Python (with pandas) adds: • repeatable data pipelines and reports (no copy-paste), • handling files too big for Excel, • advanced statistics and machine learning (scikit-learn, statsmodels), • automation (pull data, clean, chart, email a report), • working with APIs (e.g. FHIR) and unstructured text. R is a common alternative, especially in research and biostatistics.

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