docs.sheetjs.com/docz/docs/03-demos/32-extensions/10-stata.md

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Stata is a statistical software package. It offers a robust C-based extension system.

SheetJS is a JavaScript library for reading and writing data from spreadsheets.

This demo uses SheetJS to pull data from a spreadsheet for further analysis within Stata. We'll create a Stata native extension that loads the Duktape JavaScript engine and uses the SheetJS library to read data from spreadsheets and converts to a Stata-friendly format.

flowchart LR
  ofile[(workbook\nXLSB file)]
  nfile[(clean file\nXLSX)]
  data[[Stata\nVariables]]
  ofile --> |Stata Extension\nSheetJS + Duktape| nfile
  nfile --> |Stata command\nimport excel|data

The demo will read a Numbers workbook and generate variables for each column. A sample Stata session is shown below:

:::info pass

This demo covers Stata extensions. For directly processing Stata DTA files, the "Stata DTA Codec" works in the browser or NodeJS.

:::

:::note Tested Deployments

This demo was last tested by SheetJS users on 2023 November 15.

:::

:::info pass

Stata has limited support for processing spreadsheets through the import excel command¹. At the time of writing, it lacked support for XLSB, NUMBERS, and other common spreadsheet formats.

SheetJS libraries help fill the gap by normalizing spreadsheets to a form that Stata can understand.

:::

Integration Details

The current recommendation involves a native plugin that reads arbitrary files and generates clean XLSX files that Stata can import.

The extension function ultimately pairs the SheetJS read² and write³ methods to read data from the old file and write a new file:

var wb = XLSX.read(original_file_data, {type: "buffer"});
var new_file_data = XLSX.write(wb, {type: "array", bookType: "xlsx"});

The extension function cleanfile will take one or two arguments:

plugin call cleanfile, "pres.numbers" will generate sheetjs.tmp.xlsx from the first argument ("pres.numbers") and print instructions to load the file.

plugin call cleanfile, "pres.numbers" verbose will additionally print CSV contents of each worksheet in the workbook.

flowchart LR
  ofile{{File\nName}}
  subgraph JS Operations
    ojbuf[(Buffer\nFile Bytes)]
    wb(((SheetJS\nWorkbook)))
    njbuf[(Buffer\nXLSX bytes)]
  end
  obuf[(File\nbytes)]
  nbuf[(New file\nbytes)]
  nfile[(XLSX\nFile)]
  ofile --> |C\nRead File| obuf
  obuf --> |Duktape\nBuffer Ops| ojbuf
  ojbuf --> |SheetJS\n`read`| wb
  wb --> |SheetJS\n`write`| njbuf
  njbuf --> |Duktape\nBuffer Ops| nbuf
  nbuf --> |C\nWrite File| nfile

C Extensions

Stata C extensions are shared libraries or DLLs that use special Stata methods for parsing arguments and returning values.

Arguments are passed to the stata_call function in the DLL.

SF_display and SF_error display text and error messages respectively.

Duktape JS Engine

This demo uses the Duktape JavaScript engine. The SheetJS + Duktape demo covers engine integration details in more detail.

The SheetJS Standalone scripts can be loaded in Duktape by reading the source from the filesystem.

Complete Demo

:::info pass

This demo was tested in Windows x64 and macOS x64. The path names and build commands will differ in other platforms and operating systems.

:::

The cleanfile.c extension defines one plugin function. It can be chained with import excel:

program cleanfile, plugin
plugin call cleanfile, "pres.numbers" verbose
program drop cleanfile
import excel "sheetjs.tmp.xlsx", firstrow

Create Plugin

0. Ensure a compatible C compiler (Xcode on macOS) is installed.

1. Open Stata and run the following command:

pwd

The output will be the default data directory. On macOS this is typically ~/Documents/Stata

2. Open a terminal window and create a project folder sheetjs-stata within the Stata data directory:

# `cd` to the Stata data directory
cd ~/Documents/Stata
mkdir sheetjs-stata
cd sheetjs-stata

0. Ensure "Windows Subsystem for Linux" (WSL) and Visual Studio are installed.

1. Open a new "x64 Native Tools Command Prompt" window and create a project folder c:\sheetjs-stata:

cd c:\
mkdir sheetjs-stata
cd sheetjs-stata

2. Enter WSL:

bash

3. Download stplugin.c and stplugin.h from the Stata website:

curl -LO https://www.stata.com/plugins/stplugin.c
curl -LO https://www.stata.com/plugins/stplugin.h

4. Download Duktape. In Windows, the following commands should be run in WSL. In macOS, the commands should be run in the same Terminal session.

curl -LO https://duktape.org/duktape-2.7.0.tar.xz
tar -xJf duktape-2.7.0.tar.xz
mv duktape-2.7.0/src/*.{c,h} .

5. Download cleanfile.c.

In Windows, the following commands should be run in WSL. In macOS, the commands should be run in the same Terminal session.

curl -LO https://docs.sheetjs.com/stata/cleanfile.c

6. Observe that macOS does not need a "Linux Subsystem" and move to Step 7.

7. Build the plugin:

gcc -shared -fPIC -DSYSTEM=APPLEMAC stplugin.c duktape.c cleanfile.c -lm -std=c99 -Wall -ocleanfile.plugin

6. Exit WSL:

exit

The window will return to the command prompt.

7. Build the DLL:

cl /LD cleanfile.c stplugin.c duktape.c

Install Plugin

8. Copy the plugin to the Stata data directory:

cp cleanfile.plugin ../

8. Copy the DLL to cleanfile.plugin in the Stata data directory. For example, with a shared data directory c:\data:

mkdir c:\data
copy cleanfile.dll c:\data\cleanfile.plugin

Download SheetJS Scripts

9. Move to the Stata data directory:

cd ..

10. Observe that macOS does not need a "Linux Subsystem" and move to Step 11.

9. Move to the c:\data directory:

cd c:\data

10. Enter WSL

bash

11. Download SheetJS scripts and the test file.

In Windows, the following commands should be run in WSL. In macOS, the commands should be run in the same Terminal session.

{\ curl -LO https://cdn.sheetjs.com/xlsx-${current}/package/dist/shim.min.js curl -LO https://cdn.sheetjs.com/xlsx-${current}/package/dist/xlsx.full.min.js curl -LO https://sheetjs.com/pres.numbers}

Stata Test

:::note pass

The screenshot in the introduction shows the result of steps 13 - 19

:::

12. If it is not currently running, start the Stata application.

13. Run the following command in Stata:

dir

Inspect the output and confirm that cleanfile.plugin is listed.

13. Move to the c:\data directory in Stata:

cd c:\data

14. Load the cleanfile plugin:

program cleanfile, plugin

16. Read the pres.numbers test file:

plugin call cleanfile, "pres.numbers" verbose

The result will show the data from pres.numbers:

. plugin call cleanfile, "pres.numbers" verbose{'\n'}
Worksheet 0 Name: Sheet1{'\n'}
Name,Index{'\n'}
Bill Clinton,42{'\n'}
GeorgeW Bush,43{'\n'}
Barack Obama,44{'\n'}
Donald Trump,45{'\n'}
Joseph Biden,46{'\n'}
{'\n'}
Saved to `sheetjs.tmp.xlsx`{'\n'}
import excel "sheetjs.tmp.xlsx", firstrow will read the first sheet and use headers{'\n'}
for more help, see import excel

17. Close the plugin:

program drop cleanfile

18. Clear the current session:

clear

19) In the result of Step 16, click the link on import excel "sheetjs.tmp.xlsx", firstrow

Alternatively, manually type the command:

import excel "sheetjs.tmp.xlsx", firstrow

The output will show the import result:

. import excel "sheetjs.tmp.xlsx", firstrow{'\n'}
(2 vars, 5 obs)

20. Open the Data Editor (in Browse or Edit mode) and compare to the screenshot:

browse Name Index

---

1. Run help import excel in Stata or see "import excel" in the Stata documentation. ↩︎

2. See read in "Reading Files" ↩︎

3. See write in "Writing Files" ↩︎