This last is for discussion of changes to the Python language itself, in particular the CPython reference implementation. Python-list or a Pandas forum are appropriate for this question. That said, it sounds like you want df.value_counts(). But if not, follow-up in a more relevant place. On Thu, Feb 20, 2020, 7:39 AM James Lu <jamtlu@gmail.com> wrote:

On Wed, Feb 19, 2020 at 5:23 PM FilippoM <privacy_please@filippo.it> wrote:

...

Hi, I've got a Pandas data frame that looks like this

In [69]: data.head Out[69]: <bound method NDFrame.head of OS and Version Status 0 Android VIDEO_OK 1 Android 4.2.2 VIDEO_OK 2 Android 9 VIDEO_OK 3 iOS 13.3 VIDEO_OK 4 Windows 10 VIDEO_OK 5 Android 9 VIDEO_OK ... ... 24 Windows 10 VIDEO_OK 25 Android 9 VIDEO_OK 26 Android 6.0.1 VIDEO_OK 27 Windows XP VIDEO_OK 28 Android 8.0.0 VIDEO_FAILURE 29 Android 6.0 VIDEO_OK ... ... 2994 iOS 9.1 VIDEO_OK 2995 Android 9 VIDEO_OK 2996 Windows 10 VIDEO_OK 2997 Android 9 VIDEO_OK 2998 Windows 10 VIDEO_OK 2999 iOS 13.3 VIDEO_OK

with 109 possible values of the OS columns and just two possible values ()VIDEO_OK and VIDEO_FAILURE) in the status column.

How can I use Pandas' dataframe magic to calculate, for each of the possible 109 values, how many have VIDEO_OK, and how many have VIDEO_FAILURE I have respectively?

I would like to end up with something like

In[]: num_of_oks{"iOS 13.3"} Out: 15

In[]: num_of_not_oks{"iOS 13.3"} Out: 3

I am trying to do some matplotlib scatter plotting

Thanks

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Have you considered using traditional unix tools, like cut and count? Or traditional SQL. _______________________________________________ Python-ideas mailing list -- python-ideas@python.org To unsubscribe send an email to python-ideas-leave@python.org https://mail.python.org/mailman3/lists/python-ideas.python.org/ Message archived at https://mail.python.org/archives/list/python-ideas@python.org/message/B27PCY... Code of Conduct: http://python.org/psf/codeofconduct/