I have a Pandas Dataframe and wish to reverse the binary encoding (i.e. get_dummies()) of three columns. The encoding is left-to-right:
a b c
0 0 1 1
1 0 0 1
2 1 1 1
3 1 0 0
would result in a new categories column C taking values 0-7:
C
1 6
2 4
3 7
4 1
I am not sure why this line is giving me a syntax error, near axis=1:
df['C'] = df.apply(lambda x: (x['a']==1 ? 1:0)+(x['b']==1 ? 2:0)+(x['c']==1 ? 4:0), axis=1)
Use numpy if performance is important - first convert DataFrame to numpy array and then use bitwise shift:
a = df.values
#pandas 0.24+
#a = df.to_numpy()
df['C'] = a.dot(1 << np.arange(a.shape[-1]))
print (df)
a b c C
0 0 1 1 6
1 0 0 1 4
2 1 1 1 7
3 1 0 0 1
What you are doing is right. (just need some modifications in syntax)
I have modified you code,
>>> df['C'] = df.apply(lambda x: (1 if x['a']==1 else 0)+(2 if x['b']==1 else 0)+(4 if x['c']==1 else 0), axis=1)
