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Phase 3 · Python for Data Science

Topics

Pandas for Data Manipulation

Part of the Data Science Roadmap.

Summary

The standard tool for loading, exploring, filtering and transforming tabular data in Python — DataFrames, Series, groupby, merge — used in nearly every data science workflow.

How to Learn This

  • 1Load a CSV into a DataFrame and explore it with .head(), .info(), .describe().
  • 2Practice filtering, grouping, and merging DataFrames on a sample dataset.
  • 3Learn .loc versus .iloc for label-based versus position-based selection.

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NumPy for Numerical Computing

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Data Cleaning & Wrangling

More topics in Python for Data Science

Python FundamentalsNumPy for Numerical ComputingData Cleaning & WranglingMatplotlib & SeabornJupyter Notebooks & Google ColabWorking With APIsVirtual Environments & Package ManagementWriting Clean, Reusable Code
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