On Wed, Feb 19, 2020 at 5:23 PM FilippoM <privacy_ple...@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 > > > -- > https://mail.python.org/mailman/listinfo/python-list 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-le...@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/B27PCY7Z7IPCGN4K5UCKOTISBG7DIJCW/ Code of Conduct: http://python.org/psf/codeofconduct/