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Phase 3 · Python for Data Science

Topics

Virtual Environments & Package Management

Part of the Data Science Roadmap.

Summary

Isolating a project's dependencies (via venv, conda, or similar) so different projects' library versions don't conflict — a small habit that prevents a lot of 'it works on my machine' pain.

How to Learn This

  • 1Create a virtual environment for a new project and install packages inside it.
  • 2Learn to export a requirements.txt (or environment.yml) so others can reproduce your setup.
  • 3Practice switching between two environments with different library versions.

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Working With APIs

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Writing Clean, Reusable Code

More topics in Python for Data Science

Python FundamentalsNumPy for Numerical ComputingPandas for Data ManipulationData Cleaning & WranglingMatplotlib & SeabornJupyter Notebooks & Google ColabWorking With APIsWriting Clean, Reusable Code
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