#################################################### SPSS Converter ####################################################

Simple format converter utility for SPSS data files

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The SPSS Converter is a simple utility that facilitates the easy conversion of SPSS data to / from a variety of formats, including:

• CSV
• JSON
• YAML
• Excel
• Pandas DataFrame

COMPLETE DOCUMENTATION: http://spss-converter.readthedocs.org/en/latest/index.html

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Installation

To install the SPSS Converter via Pip just execute:

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$ pip install spss-converter

Dependencies

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• • Python 3.x
• • | Pandas v0.24 <https://pandas.pydata.org/docs/>_ or higher | Pyreadstat v1.0 <https://github.com/Roche/pyreadstat> or higher | * OpenPyXL v.3.0.7 <https://openpyxl.readthedocs.io/en/stable/> or higher | PyYAML v3.10 <https://github.com/yaml/pyyaml>_ or higher | simplejson v3.0 <https://simplejson.readthedocs.io/en/latest/> or higher | * Validator-Collection v1.5.0 <https://github.com/insightindustry/validator-collection> or higher

Why the SPSS Converter?

If you work with SPSS data in the Python ecosystem, you probably use a combination of two or three key libraries: Pandas <https://pandas.pydata.org>, Pyreadstat <https://github.com/Roche/pyreadstat>, and savReaderWriter <https://pythonhosted.org/savReaderWriter/>_. All three libraries are vital tools, incredibly well-constructed, designed, and managed. But over the years, I have found that converting from SPSS to other file formats using these libraries requires some fairly repetitive boilerplate code. So why not make it easier?

The SPSS Converter library is a simple wrapper around the Pyreadstat <https://github.com/Roche/pyreadstat> and Pandas <https://pandas.pydata.org> libraries that provides a clean and simple API for reading data files in a variety of formats and converting them to a variety of formats. The semantics are super simple, and should be as simple as: spss_converter.to_csv('my-spss-file.sav') or spss_converter.from_json('my-json-file.json').

Key SPSS Converter Features

• With one function call, convert an SPSS file into:

  • a Pandas <https://pandas.pydata.org>_ DataFrame
  • CSV
  • JSON
  • YAML
  • Excel
  • a dict

• With one function call, create an SPSS data file from data in:

  • a Pandas <https://pandas.pydata.org>_ DataFrame
  • CSV
  • JSON
  • YAML
  • Excel
  • a dict

• With one function call, generate a Pythonic data map or meta-data collection from your SPSS data file.

• Decide which variables (columns) you want to include / exclude when doing your conversion.

SPSS Converter vs Alternatives

For a comparison of the SPSS Converter to various alternative conversion approaches, please see full documentation: https://spss-converter.readthedocs.io/en/latest/index.html#spss-converter-vs-alternatives

Complete Documentation

The SPSS Converter is a simple library, but its functions are comprehensively documented at:

https://spss-converter.readthedocs.org/en/latest/index.html

Questions and Issues

You can ask questions and report issues on the project's Github Issues Page <https://github.com/insightindustry/spss-converter/issues>_

Contributing

We welcome contributions and pull requests! For more information, please see the Contributor Guide <http://spss-converter.readthedocs.org/en/latest/contributing.html>_

Testing

We use TravisCI <http://travisci.org> for our build automation, Codecov.io <http://codecov.io> for our test coverage, and ReadTheDocs <https://readthedocs.org>_ for our documentation.

Detailed information about our test suite and how to run tests locally can be found in our Testing Reference <http://spss-converter.readthedocs.org/en/latest/testing.html>_.

License

The SPSS Converter is made available under an MIT License <http://spss-converter.readthedocs.org/en/latest/license.html>_.