Lesser-Known Python Data Analysis Libraries

Natsort is a lifesaver when working with filenames numbered by humans (like file1, file2 ... file11), those will be sorted correctly. Beats asking people to "Please add leading 0's oh and when you suspect you will pass 100, add 2 leading 0's."

Re: Lesser-Known Python Data Analysis Libraries

#5

Post by aub3bhat » Tue, Apr 19, 2016, 1:18 PM UTC

melor wrote: post #2

I use histogram.py from https://github.com/bitly/data_hacks all the time...

Its really cool, I wish it handled missing values (empty string), will submit a PR soon. until then here is the issue https://github.com/bitly/data_hacks/issues/34

Re: Lesser-Known Python Data Analysis Libraries

#6

Post by philovivero » Tue, Apr 19, 2016, 1:58 PM UTC

melor wrote: post #2

I use histogram.py from https://github.com/bitly/data_hacks all the time...

Interesting. Looks similar to my version, albeit with a bit fewer features.

https://github.com/philovivero/distribution

Re: Lesser-Known Python Data Analysis Libraries

#7

Post by forgetsusername » Tue, Apr 19, 2016, 1:59 PM UTC

This is a great list.

I'm equally excited for all the suggestions sure to appear in the comments (hinthint). I got a ton from this thread last time, even though they weren't data analysis specific:

https://news.ycombinator.com/item?id=10782969

Re: Lesser-Known Python Data Analysis Libraries

#8

Post by ZenoArrow » Tue, Apr 19, 2016, 2:01 PM UTC

tinydb looks like it could be useful, thanks for this.

Whilst this isn't a data analysis library per se, PyOpenCL may be of interest for people doing data analysis work in Python:

https://mathema.tician.de/software/pyopencl/

Re: Lesser-Known Python Data Analysis Libraries

#9

Post by herge » Tue, Apr 19, 2016, 2:02 PM UTC

teekert wrote: post #4

Natsort is a lifesaver when working with filenames numbered by humans (like file1, file2 ... file11), those will be sorted correctly. Beats asking people to "Please add leading 0's oh and when you suspect you will pass 100, add 2 leading 0's."

FWIW, the sort method (and sorted keyword) take a 'key' keyword, where you can pass a function to use to calculate the key to sort the sequence with. So in your file11 case, you can do:

sorted(files, key=lambda x: int(x[4:])

, and it will do the right thing.

Although with natsort, you don't have to parse the actual strings yourself.

Re: Lesser-Known Python Data Analysis Libraries

#10

Post by metaobject » Tue, Apr 19, 2016, 2:27 PM UTC

I've used PrettyTable on a few projects and found it to be very easy to use. Highly recommended!