Python Pandas Ditches NumPy for Speedier PyArrow (thenewstack.io) 18 points by blacktulip 1y ago ↗ HN
[–] constantcrying 1y ago ↗ This is an insane article, I do not think the author has any idea what is going on.The comparison of numpy reading CSV to arrow reading parquet is completely bizarre and totally misses the point of switching out the underlying data format. [–] kbrkbr 1y ago ↗ Or maybe you did not read it properly?> Reading in that CSV file into memory would take Python 55.8 seconds, but PyArrow did the work in 11.8 seconds.It's later clarified that Pyarrow does load csv here, though the numbers don't fully add up. Also the format change is explained.
[–] kbrkbr 1y ago ↗ Or maybe you did not read it properly?> Reading in that CSV file into memory would take Python 55.8 seconds, but PyArrow did the work in 11.8 seconds.It's later clarified that Pyarrow does load csv here, though the numbers don't fully add up. Also the format change is explained.
[–] joshlk 1y ago ↗ > [numpy] stores everything in rowsThis isn't true. Pandas uses Numpy to store columns of data. Theres quite a few technical errors in the article.
[–] agons 1y ago ↗ It gets worse the further you go, this was where I had to bail:> the format is much favored by AI frameworks such as TensorFlow and PyCharm.
5 comments
[ 3.7 ms ] story [ 21.0 ms ] threadThe comparison of numpy reading CSV to arrow reading parquet is completely bizarre and totally misses the point of switching out the underlying data format.
> Reading in that CSV file into memory would take Python 55.8 seconds, but PyArrow did the work in 11.8 seconds.
It's later clarified that Pyarrow does load csv here, though the numbers don't fully add up. Also the format change is explained.
This isn't true. Pandas uses Numpy to store columns of data. Theres quite a few technical errors in the article.
> the format is much favored by AI frameworks such as TensorFlow and PyCharm.