How to create a pandas DataFrame with several numpy 1d arrays?

Question

I've created some np.arrays to do some calculation with them. (All have the same size [100,1]) Now I want to create a pandas Dataframe and each array shoud be one column of that DF. The Names of the arrays should be the header of the DataFrame.

In Matlab I would easily do it like that:

Table = table(array1, array2, array3, ... );

How can I do this in Python?

thanks in advance!

Answer 1

Let's say these are your arrays:

arr1, arr2, arr3 = np.zeros((3, 100, 1))

arr1.shape
Out: (100, 1)

You can use hstack to stack them and pass the resulting 2D array to the DataFrame constructor:

df = pd.DataFrame(np.hstack((arr1, arr2, arr3)))

df.head()
Out: 
     0    1    2
0  0.0  0.0  0.0
1  0.0  0.0  0.0
2  0.0  0.0  0.0
3  0.0  0.0  0.0
4  0.0  0.0  0.0

Or name the columns as arr1, arr2, ...:

df = pd.DataFrame(np.hstack((arr1, arr2, arr3)), 
                  columns=['arr{}'.format(i+1) for i in range(3)])

which gives

df.head()
Out: 
   arr1  arr2  arr3
0   0.0   0.0   0.0
1   0.0   0.0   0.0
2   0.0   0.0   0.0
3   0.0   0.0   0.0
4   0.0   0.0   0.0

Answer 2

Solution with numpy.concatenate for 2d array and DataFrame constructor:

df = pd.DataFrame(np.concatenate([arr1, arr2, arr3], axis=1), columns= ['a','b','c'])