Can I create a dataframe from few 1d arrays as columns?

Question

Is it possible to create a dataframe from few 1d arrays and place them as columns? If I create a dataframe from 1 1d array everything is ok:

arr1 = np.array([11, 12, 13, 14, 15])
arr1_arr2_df = pd.DataFrame(data=arr1, index=None, columns=None) 
arr1_arr2_df
Out: 
    0
0  11
1  12
2  13
3  14
4  15

But If make a datafreme form 2 arrays they are placed is rows:

arr1 = np.array([11, 12, 13, 14, 15])
arr2 = np.array([21, 22, 23, 24, 25])
arr1_arr2_df = pd.DataFrame(data=(arr1,arr2), index=None, columns=None)
arr1_arr2_df
Out: 
    0   1   2   3   4
0  11  12  13  14  15
1  21  22  23  24  25

I know that I can achieve it by using transpose:

arr1_arr2_df = arr1_arr2_df.transpose()
arr1_arr2_df
Out: 
    0   1
0  11  21
1  12  22
2  13  23
3  14  24
4  15  25

But is it possible to get it from the start?

what about zip? arr1_arr2_df = pd.DataFrame(data=(zip(arr1,arr2)), index=None, columns=None) — Chris Doyle
– Chris Doyle, Commented Jun 2, 2020 at 16:44
since we r in the mood : pd.DataFrame(dict(enumerate((arr1,arr2)))) . But really, zip does the job succinctly — sammywemmy
– sammywemmy, Commented Jun 2, 2020 at 16:54

Tom · Accepted Answer · 2020-06-02 16:51:23Z

3

You can use a dictionary:

arr1_arr2_df = pd.DataFrame(data={0:arr1,1:arr2})

answered Jun 2, 2020 at 16:51

Tom

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