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Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect, withe examples in packages:

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

• Using Python for Introductory Econometrics by Florian Heiss and Daniel Brunner.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.

Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect, with examples in packages:

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

• Using Python for Introductory Econometrics by Florian Heiss and Daniel Brunner.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.

Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect, withe examples in packages:

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.

Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect, withe examples in packages:

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

• Using Python for Introductory Econometrics by Florian Heiss and Daniel Brunner.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.

Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect by Nick Huntington-Klein

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.

Here are a few good websites/books that I am fond of that use DAGs, and have code examples in R, Python, and Stata on github or packaged up.

• Causal Inference: The Mixtape and its github

• Data Analysis for Business, Economics, and Policy and its github.

• The Effect, withe examples in packages:

  • install.packages('causaldata') in R
  • ssc install causaldata in Stata
  • pip install causaldata in Python.

This is not exactly the cutting-edge stuff, but the foundation you need to get started.

I am an economist at a tech company who uses and teaches these methods.