# nbstata

**Repository Path**: econometric/nbstata

## Basic Information

- **Project Name**: nbstata
- **Description**: https://github.com/hugetim/nbstata
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-05-12
- **Last Updated**: 2026-05-12

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# nbstata: a new Stata kernel


<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

 

*nbstata* is a [Jupyter
kernel](https://docs.jupyter.org/en/latest/projects/kernels.html) for
[Stata](https://www.stata.com/why-use-stata/) built on top of
[pystata](https://www.stata.com/python/pystata18/index.html).

**[*For the User Guide, click
here.*](https://hugetim.github.io/nbstata/user_guide.html)**

 

## What is Jupyter?

A Jupyter notebook allows you to combine interactive code and results
with [Markdown](https://daringfireball.net/projects/markdown/basics) in
a single document. 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](https://www.stata.com/python/pystata18/notebook/Example2.html),
which is needlessly clunky if you are working primarily with Stata).

### Key *nbstata* features

- [x] [Easy
  setup](https://hugetim.github.io/nbstata/user_guide.html#install)
- [x] Works with Stata 17+ (only).
- [x] DataGrid widget with `browse`-like capabilities (e.g., interactive
  filtering)
- [x] Variable and data properties available in a ‘contextual help’ side
  panel
- [x] Quarto [inline
  code](https://quarto.org/docs/computations/inline-code.html) support

Users of Stata 17 or 18.0 also get these features only built-in natively
to Stata 18.5+:

- Displays Stata output without the redundant ‘echo’ of (multi-line)
  commands
- Autocompletion for variables, macros, matrices, and file paths
- Interactive/richtext help files accessible within notebook
- `#delimit ;` interactive support (along with all types of comments)

The video below demonstrates using Stata in a Jupyter notebook. In
addition to the
[NBClassic](https://nbclassic.readthedocs.io/en/stable/notebook.html)
application shown there, *nbstata* can also be used with
[JupyterLab](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html),
[VS
Code](https://code.visualstudio.com/docs/datascience/jupyter-notebooks),
or [Quarto](https://quarto.org/).

<img align="center" width="650" src="https://github.com/kylebarron/stata_kernel/raw/master/docs/src/img/jupyter_notebook_example.gif" alt="Animated GIF demoing major Stata kernel features">

### What can you do with Stata notebooks…

…that you can’t do with the [official Stata
interface](https://www.stata.com/features/overview/graphical-user-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.  <img align="left" width="54" height="18.6" src="https://raw.githubusercontent.com/hugetim/nbstata/master/index_files/figure-commonmark/226326ec-1-image-2.png" alt="WordArt of the word 'images'">
    4.  [links](https://hugetim.github.io/nbstata/)
    5.  math: $y_{it}=\beta_0+\varepsilon_{it}$

## Contributing

*nbstata* is being developed using
[nbdev](https://nbdev.fast.ai/blog/posts/2022-07-28-nbdev2/#whats-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.)

For more, see
[CONTRIBUTING.md](https://github.com/hugetim/nbstata/blob/master/CONTRIBUTING.md).

## Acknowledgements

Kyle Barron authored the original *stata_kernel*, which works for older
versions of Stata. Vinci Chow created a Stata kernel that instead uses
[pystata](https://www.stata.com/python/pystata18/), which first became
available with Stata 17. *nbstata* was originally derived from his
[*pystata-kernel*](https://github.com/ticoneva/pystata-kernel), but much
of the docs and newer features are derived from *stata_kernel*.

[^1]: Stata [dynamic
    documents](https://www.stata.com/manuals/rptdynamicdocumentsintro.pdf)
    can do this part, though with a less interactive workflow. (See
    also: [markstat](https://grodri.github.io/markstat/),
    [stmd](https://www.ssc.wisc.edu/~hemken/Stataworkshops/stmd/Usage/stmdusage.html),
    and
    [Statamarkdown](https://ssc.wisc.edu/~hemken/Stataworkshops/Statamarkdown/stata-and-r-markdown.html))
    Using *nbstata* with
    [Quarto](https://www.statalist.org/forums/forum/general-stata-discussion/general/1703835-ado-files-and-literate-programming)
    instead gives you a similar workflow, with greater flexibility of
    output.