Merging two data frames into a new one with unique items marked with 1 or 0

Using concat+ get_dummies

u = pd.concat([df1, df2], axis=0, keys=['DF1', 'DF2'])

pd.get_dummies(u.Feature).sum(level=0).T

   DF1  DF2
a    1    1
b    1    1
c    1    0
d    1    0
x    0    1
y    0    1

You can use merge with series.str.get_dummies() together to achieve this:

m=df1[['Feature']].merge(df2[['Feature']],how='outer',indicator=True)

d={'both':'DF1,DF2','left_only':'DF1','right_only':'DF2'}
m=m.assign(_merge=m._merge.map(d))
m[['Feature']].join(m._merge.str.get_dummies(','))

  Feature  DF1  DF2
0       a    1    1
1       b    1    1
2       c    1    0
3       d    1    0
4       y    0    1
5       x    0    1

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