nbstata 0.4.0

Jupyter kernel for Stata based on pystata

Welcome to nbstata

Click here for the nbstata User Guide

What is Jupyter?

JupyterLab is a browser-based editor that allows you to combine interactive code and results with Markdown in a single document (called a Jupyter notebook). It is open source and widely used. Though it is named after the three core programming languages it supports (Julia, Python, and R), it can be used with with a wide variety of languages.

nbstata allows you to create Stata notebooks (as opposed to using Stata within a Python notebook, which is a nice way to embed Stata commands within Python code but is needlessly clunky if you are working primarily with Stata).

nbstata features

• Works with Stata 17 (only).
• Can display output from Stata code without an ‘echo’ of multi-line commands
• Autocompletion for variables, macros, matrices, and file paths.
• DataGrid widget with browse-like capabilities (e.g., interactive filtering).
• Variable and data properties (describe and e/return list) available in a ‘contextual help’ side panel.
• Interactive help files available within notebook.
• #delimit ; interactive support (along with all types of comments).

What can you do with Stata notebooks…

…that you can’t do with the official Stata interface?

• Exploratory analysis that is both:
  • interactive
  • preserved for future reference/editing
• Present results in a way that interweaves:[1]
  • code
  • results (including graphs)
  • rich text:
    1. lists
    2. Headings
    3. 
    4. links
    5. math: $y_{it}=\beta_0+\varepsilon_{it}$

[1] Stata dynamic documents can do something similar, but with a very different workflow.

Contributing

nbstata is being developed using nbdev. The /nbs directory is where edits to the source code should be made. (The python code is then exported to the /nbdev library folder.) The one exception is install.py.

The @patch_to decorator is occasionally used to break up class definitions into separate cells.

For more, see CONTRIBUTING.md.

Acknowledgements

Kyle Barron authored the original stata_kernel and Vinci Chow carried that work forward for Stata 17, converting the backend to use pystata. nbstata is directly derived from his pystata-kernel.