Pandas array to columns

Question

Given

data= [
    (array([0,0,1]),1),
    (array([0,1,1]),1),
    (array([1,0,1]),0),
    (array([1,1,1]),1)    
]

How can you convert it to a Pandas DataFrame so that each column is separate?

A   B   C   Z
0   0   1   1
0   1   1   1
1   0   1   0
1   1   1   1

Answer 1

I'd use np.append in a list comprehension

pd.DataFrame([np.append(*row) for row in data], columns=list('ABCZ'))

   A  B  C  Z
0  0  0  1  1
1  0  1  1  1
2  1  0  1  0
3  1  1  1  1

Or more efficiently with np.column_stack and zip

pd.DataFrame(np.column_stack(list(zip(*data))), columns=list('ABCZ'))

   A  B  C  Z
0  0  0  1  1
1  0  1  1  1
2  1  0  1  0
3  1  1  1  1

Timing

%timeit pd.DataFrame([np.append(*row) for row in data], columns=list('ABCZ'))
1000 loops, best of 3: 460 µs per loop

%timeit pd.DataFrame(np.column_stack(list(zip(*data))), columns=list('ABCZ'))
10000 loops, best of 3: 130 µs per loop

%timeit pd.DataFrame([e[0].tolist()+[e[1]] for e in data],columns=['A','B','C','Z'])
1000 loops, best of 3: 446 µs per loop

Answer 2

Convert your array to a list of lists and then put it into a Dataframe.

pd.DataFrame([e[0].tolist()+[e[1]] for e in data],columns=['A','B','C','Z'])
Out[265]: 
   A  B  C  Z
0  0  0  1  1
1  0  1  1  1
2  1  0  1  0
3  1  1  1  1