A set of Data analysis tools in pYTHON 3.x.
Dython was designed with analysis usage in mind - meaning ease-of-use, functionality and readability are the core values of this library.
Dython can be installed directly using pip:
pip install dython
or, via the conda package manager:
conda install -c conda-forge dython
Modules documentation can be found on shakedzy.xyz/dython. You can also learn more and see examples of the main methods of this library on these blogposts.
Contributions are always welcomed - if you found something you can fix, or have an idea for a new feature, feel free to write it and open a pull request. Please make sure to go over the contributions guidelines.
Use this reference to cite if you use Dython in a paper:
@software{Zychlinski_dython_2018,
author = {Zychlinski, Shaked},
title = {{dython}},
year = {2018},
url = {https://github.com/shakedzy/dython},
doi = {10.5281/zenodo.12698421}
}
FAQs
A set of data tools in Python
We found that dython demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.