In [46]: s = Series(list(‘aaabbbccddefgh’)).astype(‘category’)
In [47]: s
Out[47]:
0 a
1 a
2 a
3 b
4 b
5 b
6 c
7 c
8 d
9 d
10 e
11 f
12 g
13 h
dtype: category
Categories (8, object): [a < b < c < d < e < f < g < h]
In [48]: df = pd.get_dummies(s)
In [49]: df
Out[49]:
a b c d e f g h
0 1 0 0 0 0 0 0 0
1 1 0 0 0 0 0 0 0
2 1 0 0 0 0 0 0 0
3 0 1 0 0 0 0 0 0
4 0 1 0 0 0 0 0 0
5 0 1 0 0 0 0 0 0
6 0 0 1 0 0 0 0 0
7 0 0 1 0 0 0 0 0
8 0 0 0 1 0 0 0 0
9 0 0 0 1 0 0 0 0
10 0 0 0 0 1 0 0 0
11 0 0 0 0 0 1 0 0
12 0 0 0 0 0 0 1 0
13 0 0 0 0 0 0 0 1
In [50]: x = df.stack()
# I don't think you actually need to specify ALL of the categories here, as by deFinition
# they are in the dummy matrix to start (and hence the column index)
In [51]: Series(pd.Categorical(x[x!=0].index.get_level_values(1)))
Out[51]:
0 a
1 a
2 a
3 b
4 b
5 b
6 c
7 c
8 d
9 d
10 e
11 f
12 g
13 h
Name: level_1, dtype: category
Categories (8, object): [a < b < c < d < e < f < g < h]
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