surveypie 0.0.1

Polarization indices in Python

Ordinal-Scale-Stats-py

Python package that helps you analyze ordinal data.

Introduction

Ordinal scale data is common. Companies and governments can quickly perform large-scale research with surveys. Usually, a survey output is placed on the Likert scale, where answers are ordered to describe a person's feelings about the survey's topic. A typical example of a survey is when a person is asked to agree with a statement with answers on a five-level scale:

Should the law protect your personal data?

1. Strongly disagree.
2. Rather disagree.
3. I don't know.
4. Rather agree.
5. Strongly agree.

The order between categories makes analysis complex, and the fact that answers are polarized between opposing states. Moreover, a border between categories is subjective and depends on the person's experiences, feelings, and knowledge about a surveying topic.

Classical measurements of central tendency do not fit well with ordinal data [ADD BIBLIOGRAPHY]. We encourage you to use the ordinal-scale-stats package to analyze survey responses. With ordinal-scale-stats, you can:

• visualize differences between surveyed groups,
• measure polarization within a group,
• measure polarization between groups,
• measure ...

Example use case

Setup

Requirements

API

Vignettes

Tests and Contribution

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