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My goal is to make a numpy array out of dataframes. There are 2 dataframes, which have 2 rows and 5 columns for each(If they were numpy array, their shapes are (2,5) for each). Is there a way to make numpy array which has shape (2, 2, 5) out of these dataframes?(There are 2 datataframe which has (2,5) shape, so (2,2,5) it is.)

import pandas as pd
import numpy as np

A1 = pd.DataFrame({'O':[2,4],'H':[4,8],'L':[1,2],'V':[100, 120],'C':[3,7]})  # shape (2,5) Table
A2 = pd.DataFrame({'O':[20,40],'H':[40,80],'L':[10,20],'V':[1000, 1200],'C':[30,70]})  # shape (2,5) Table

# Is there a way to make (2, 2, 5) numpy array from dataframe A1, A2?

2 Answers 2

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Just concat then reshape

pd.concat([A1,A2]).values.reshape(2,2,5)
Out[398]: 
array([[[   2,    4,    1,  100,    3],
        [   4,    8,    2,  120,    7]],
       [[  20,   40,   10, 1000,   30],
        [  40,   80,   20, 1200,   70]]])
pd.concat([A1,A2]).values.reshape(2,2,5).shape
Out[399]: (2, 2, 5)
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1

One way is to stack them using np.stack([])

import numpy as np

np.stack([A1.values, A2.values])

np.stack([A1.values, A2.values]).shape

Output : (2, 2, 5)

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