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in Data Science by (50.2k points)

I've written a bunch of code on the assumption that I was going to use Numpy arrays. Turns out the data I am getting is loaded through Pandas. I remember now that I loaded it in Pandas because I was having some problems loading it in Numpy. I believe the data was just too large.

Therefore I was wondering, is there a difference in computational ability when using Numpy vs Pandas?

If Pandas is more efficient then I would rather rewrite all my code for Pandas but if there is no more efficiency then I'll just use a numpy array...

1 Answer

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by (108k points)

There can be a notable performance difference, of an order of magnitude for multiplications and multiple orders of magnitude for indexing a few random values.

I was actually wondering about the same thing and came across this interesting comparison in the following link:

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