Add Possible Values From List To Groupby Result
I have a list of possible results:
list(TEST_RESULT_PRIORITY.keys()) ['Failed', 'Inconclusive', 'Passed', 'Error', 'NotImplemented', 'NonTestable', 'None']
and I do a groupby of a dataframe and get:
df.groupby(['Result']).size() Result Failed 144 Inconclusive 29 NonTestable 15 None 4820 Passed 45
I would like to add to the result of the groupby the options from the first list (or dictionary keys, whatever is easier) that don't show because don't exist in the data frame. So I would get something like this (order alphabetically would be easier):
Result Error 0 Failed 144 Inconclusive 29 NotImplemented 0 NonTestable 15 None 4820 Passed 0 Passed 45
Any ideas? Thanks!
s = (df.groupby(['Result']) .size() .reindex(list(TEST_RESULT_PRIORITY.keys()), fill_value=0) .sort_index()) print (s) Result Error 0 Failed 144 Inconclusive 29 NonTestable 15 None 4820 NotImplemented 0 Passed 45 dtype: int64
s = (df.groupby(['Result']) .size() .reindex(sorted(list(TEST_RESULT_PRIORITY.keys())), fill_value=0)) print (s) Result Error 0 Failed 144 Inconclusive 29 NonTestable 15 None 4820 NotImplemented 0 Passed 45 dtype: int64
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