Convert two numpy array to dataframe

Question

I want to convert two numpy array to one DataFrame containing two columns. The first numpy array 'images' is of shape 102, 1024. The second numpy array 'label' is of shape (1020, )

My core code is:

images=np.array(images)
label=np.array(label)
l=np.array([images,label])
dataset=pd.DataFrame(l)

But it turns out to be an error saying that:

ValueError: could not broadcast input array from shape (1020,1024) into shape (1020)

What should I do to convert these two numpy array into two columns in one dataframe?

Possible duplicate of Combining NumPy arrays

Grigory
– Grigory

2017-09-23 11:32:07 +00:00
Commented Sep 23, 2017 at 11:32 — Grigory
– Grigory, Commented Sep 23, 2017 at 11:32

MSeifert · Accepted Answer · 2017-09-23 14:45:56Z

31

You can't stack them easily, especially if you want them as different columns, because you can't insert a 2D array in one column of a DataFrame, so you need to convert it to something else, for example a list.

So something like this would work:

import pandas as pd
import numpy as np
images = np.array(images)
label = np.array(label)
dataset = pd.DataFrame({'label': label, 'images': list(images)}, columns=['label', 'images'])

This will create a DataFrame with 1020 rows and 2 columns, where each item in the second column contains 1D arrays of length 1024.

answered Sep 23, 2017 at 14:45

MSeifert

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Comments

MCL · Accepted Answer · 2021-10-14 09:40:55Z

2

Coming from engineering, I like the visual side of creating matrices.

matrix_aux = np.vstack([label,images])
matrix     = np.transpose(matrix_aux)
df_lab_img = pd.DataFrame(matrix)

Takes a little bit more of code but leaves you with the Numpy array too.

answered Oct 14, 2021 at 9:40

MCL

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Comments

Erwin · Accepted Answer · 2022-01-13 09:49:56Z

0

You can also use hstack

import pandas as pd
import numpy as np

dataset = pd.DataFrame(np.hstack((images, label.reshape(-1, 1))))

answered Jan 13, 2022 at 9:49

Erwin

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