Make a pandas dataframe out of Series with numpy ndarrays (or 2d numpy array?)

Question

I have a pandas Series which contains 2d (?) numpy ndarrays of the same length with the shape (1 ,208), what would be the easiest way to make it into pandas dataframe with 208 columns?

how it looks like

When i tried to make a numpy array, it turned out to be 3D, though I expected it to be 2D

x = []
for i in train_rdkit_desc:
    np.reshape(i, 208)
    x.append(i)

x = np.array(x)
x.shape
    
    (908, 1, 208)

stackoverflow.com/questions/32594136/…. pd.DataFrame(series_to_convert.map(lambda x: x[0]).tolist()) — jwzinserl
– jwzinserl, Commented Dec 3, 2021 at 22:27

Volk · Accepted Answer · 2021-12-04 00:39:29Z

1

I think the easiest way:

you can create a list with the name of your numpy arrays. After that use method concatanation by columns (axis = 1):

df3 = pd.concat([numpy1,numpy2,..., numpyn], axis = 1)

Example:

a = np.array([1, 2, 3, 4, 5, 6])
b = np.array([2, 2, 3, 4, 5, 6])
df= pd.concat([pd.DataFrame(a), pd.DataFrame(b)])

edited Dec 4, 2021 at 0:39

answered Dec 3, 2021 at 22:25

Volk

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3 Comments

Diana Over a year ago

this way doesn't work, i get a 1-column dataframe with ndarrays

Volk Over a year ago

Do you need 2D array with same vectors?

Volk Over a year ago

I changed my answer...

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