https://github.com/lverweijen/piargus
Python wrapper for TauArgus
https://github.com/lverweijen/piargus
disclosure statistical-disclosure-control statistics tauargus
Last synced: 5 months ago
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Python wrapper for TauArgus
- Host: GitHub
- URL: https://github.com/lverweijen/piargus
- Owner: lverweijen
- License: apache-2.0
- Created: 2022-12-14T13:55:05.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-01-24T10:14:17.000Z (over 1 year ago)
- Last Synced: 2025-10-27T22:41:43.704Z (8 months ago)
- Topics: disclosure, statistical-disclosure-control, statistics, tauargus
- Language: Python
- Homepage: https://lverweijen.github.io/piargus/
- Size: 5.36 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# PiArgus
This package provides a python wrapper around [τ-ARGUS](https://research.cbs.nl/casc/tau.htm), a program to protect statistical tables.
This package takes care of generating all the required metadata and runs τ-ARGUS in the background to do the heavy work.
For this package to work, it is required to install τ-ARGUS locally first.
It's also recommended to read the [TauArgus manual](https://research.cbs.nl/casc/Software/TauManualV4.1.pdf) to understand how it should be used.
## Features
- Generate output tables from microdata or tabledata. It is recommended to generate from microdata.
- Metadata can be generated automatically, although using an existing rda-file is also possible.
- It's possible to create hierarchies, codelists, apriori files, recode files all from code or from existing files.
- Basic error checking of input is done before input is supplied to argus.
Feel free to [contribute](https://github.com/lverweijen/piargus) for other TauArgus-features.
[Feedback](https://github.com/lverweijen/piargus/issues) is welcome too.
## Installing
- Download and install the latest version of [τ-ARGUS](https://github.com/sdcTools/tauargus/releases).
- Then use [pip](https://pip.pypa.io/en/stable/getting-started/) to install piargus:
```sh
$ pip install --upgrade piargus
```
## Example
```python
import pandas as pd
import piargus as pa
tau = pa.TauArgus(r'C:\Users\User\Programs\TauArgus4.2.0b5\TauArgus.exe')
input_df = pd.read_csv('data/microdata.csv')
input_data = pa.MicroData(input_df)
output_table = pa.Table(['sbi', 'regio'], 'income', safety_rule="P(10)")
job = pa.Job(input_data, [output_table], directory='tau')
report = tau.run(job)
table_result = output_table.load_result()
print(report)
print(table_result)
```
Change `C:\Users\User\Programs\TauArgus4.2.0b5\TauArgus.exe` to the location where argus is installed.
See [tutorial](https://lverweijen.github.io/piargus/tutorial.html) for a general introduction.
See [Examples](https://github.com/lverweijen/tree/main/examples) for more examples.
## See also
The following packages in R offer similar functionality:
- https://github.com/sdcTools/sdcTable
- https://github.com/InseeFrLab/rtauargus