An easy to use library to speed up computation (by parallelizing on multi CPUs) with pandas.
Readme
| 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.
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