A package that helps UX researchers quickly analyse data from cardsorting exercises.
More precisely, it helps you to:
- Create dendrograms
- Extract user-generated category-labels
- Using data exports from kardsort.com
$ pip install cardsortcardsort can be used to create dendrograms and extract user-generated category-labels:
from cardsort import analysis
import pandas as pd
path = "example-data.csv" # data with columns: card_id, card_label, category_id, category_label, user_id
df = pd.read_csv(path)
# create a dendrogram that summarized user-generated clusters
analysis.create_dendrogram(df)Output
# learn which category labels users gave to clusters
cards = ['Banana', 'Apple']
analysis.get_cluster_labels(df, cards)Output
['Healthy snacks', 'Snacks', 'Fruits', 'Food']
- This package works with data exports from kardsort.com (Export format 'Casolysis Data (.csv) - Recommended')
- This data equals the following structure:
card_id, card_label, category_id, category_label, user_id
See the documentation for details.
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
cardsort was created by Katharina Kloppenborg and is licensed under the terms of the MIT license.
cardsort was created with cookiecutter and the py-pkgs-cookiecutter template.