An easy to use library to speed up computation (by parallelizing on multi CPUs) with pandas.
| Without parallelization |  |
|---|---|
| With parallelization |  |
Pandaral.lel provides a simple way to parallelize your pandas operations on all your CPUs by changing only one line of code. It also displays progress bars.
pip install pandarallel [--upgrade] [--user]
from pandarallel import pandarallel
pandarallel.initialize(progress_bar=True)
# df.apply(func)
df.parallel_apply(func)
Be sure to check out the documentation.
An example of each available pandas API is available:
FAQs
An easy to use library to speed up computation (by parallelizing on multi CPUs) with pandas.
We found that pandarallel 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
CISOs are racing to adopt AI for cybersecurity, but hurdles in budgets and governance may leave some falling behind in the fight against cyber threats.
Research
Security News
Socket researchers uncovered a backdoored typosquat of BoltDB in the Go ecosystem, exploiting Go Module Proxy caching to persist undetected for years.
Security News
Company News
Socket is joining TC54 to help develop standards for software supply chain security, contributing to the evolution of SBOMs, CycloneDX, and Package URL specifications.