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DIME's Python Training for Stata Users

There are many great Python trainings across the internet, and they all are great in their own niche. The niche of this Python training is to help researchers who are already advanced coders in Stata transition to using Python. This training will therefore not take time to discuss questions like: "What is programming used for?" or "What is an if-condition or a loop/iteration?", but instead simply focus on how such concepts are implemented in Python. One of the main benefits of Python is that it is extremely versatile, and can be used for anything from data science, web servers, or robots; among many other examples. But this training will only focus on what a typical microeconomics researcher needs. If this description fits you, then we think that this training will be great for you. But if this description does not fit you, then there might be a training better suited for you elsewhere on the big internet.

Content

Session 1 - Introduction to Python

Introduces Python variables, data types, and the basic syntax, and applies these concepts in a simple web scraping exercise.

Session 2 - Data processing in Python using Pandas

Introduces the Pandas library, its basic data types, and how to use it to perform the most common data processing operations in Python.

More sessions will be developed soon

Main contact

Luis Eduardo San Martin - [email protected]

Authors

Luis Eduardo San Martin, Kristoffer Bjärkefur

Other contributors

Carla Solis

Last update

May 12, 2021

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DIME's Python Training for advanced R/Stata users

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  • Jupyter Notebook 55.0%
  • TeX 45.0%