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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