Consider the following data block
df = pd.DataFrame({'name' : [['one two','three four'], ['one'],[], [],['one two'],['three']],
'col' : ['A','B','A','B','A','B']})
df.sort_values(by='col',inplace=True)
df
Out[62]:
col name
0 A [one two, three four]
2 A []
4 A [one two]
1 B [one]
3 B []
5 B [three]
I would like to get a column that keeps track of all the unique rows included in namefor each combination col.
That is the expected result
df
Out[62]:
col name unique_list
0 A [one two, three four] [one two, three four]
2 A [] [one two, three four]
4 A [one two] [one two, three four]
1 B [one] [one, three]
3 B [] [one, three]
5 B [three] [one, three]
Indeed, let's say, for group A you can see that the unique set of lines included in [one two, three four], []and [one two], is[one two]
I can get the corresponding number of unique values using Pandas: how to get a unique number of values in cells when the cells contain lists? :
df['count_unique']=df.groupby('col')['name'].transform(lambda x: list(pd.Series(x.apply(pd.Series).stack().reset_index(drop=True, level=1).nunique())))
df
Out[65]:
col name count_unique
0 A [one two, three four] 2
2 A [] 2
4 A [one two] 2
1 B [one] 2
3 B [] 2
5 B [three] 2
but the replacement nuniquefor the uniqueabove is not performed.
Any ideas? Thank!