The pyzipf package tallies the occurrences of words in text
files and plots each word's rank versus its frequency together
with a line for the theoretical distribution for Zipf's Law.
Zipf's Law is often stated as an observational pattern seen in the relationship between the frequency and rank of words in a text:
"…the most frequent word will occur approximately twice as often as the second most frequent word, three times as often as the third most frequent word, etc." — wikipedia
Many books are available to download in plain text format from sites such as Project Gutenberg, so we created this package to qualitatively explore how well different books align with the word frequencies predicted by Zipf's Law.
pip install pyzipf
After installing this package, the following three commands will be available from the command line
countwordsfor counting the occurrences of words in a text.collatefor collating multiple word count files together.plotcountsfor visualizing the word counts.
A typical usage scenario would include running the following from your terminal:
countwords dracula.txt > dracula.csv countwords moby_dick.txt > moby_dick.csv collate dracula.csv moby_dick.csv > collated.csv plotcounts collated.csv --outfile zipf-drac-moby.jpg
Additional information on each function
can be found in their docstrings and appending the -h flag,
e.g. countwords -h.
- Amira Khan <amira@zipf.org> @amira-khan
- Sami Virtanen <sami@zipf.org> @sami-virtanen
Interested in contributing? Check out the CONTRIBUTING.md file for guidelines on how to contribute. Please note that this project is released with a Contributor Code of Conduct (CONDUCT.md). By contributing to this project, you agree to abide by its terms. Both of these files can be found in our GitHub repository.