Convert multidimensional array to pandas dataframe

Question

I got an numpy array looking like this:

0.716524    0.76476     0.734421    0.699913
0.708502    0.659577    0.646064    0.693093
0.749121    0.695317    0.675748    0.72938
0.68869     0.711581    0.614649    0.654494
0.651646    0.67847     0.655275    0.63885
0.765029    0.685263    0.646114    0.743514
0.7615      0.76907     0.728695    0.746114
0.682806    0.671888    0.6394      0.677168
...

and want to convert it to a pandas dataframe. I know you can convert one-dimensional arrays with

pd.Dataframe(array, columns=["name"])

But how would I do this in my case? And is it possible to name the columns dynamically if the size varies?

jezrael · Accepted Answer · 2020-12-09 09:50:44Z

2

You can use DataFrame constructor and for new columns names if dont know number of them is possible use DataFrame.add_prefix:

pd.Dataframe(array).add_prefix('Name')

edited Dec 9, 2020 at 9:50

answered Dec 9, 2020 at 9:20

jezrael

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