4D array numpy into pandas

Question

I'd like to transform my numpy array ( shape=(27, 77, 77) ) :

   [[1., 1., 1., ..., 1., 1., 1.],
    [1., 1., 1., ..., 1., 1., 1.],
    [1., 1., 1., ..., 1., 1., 1.],
    ...,
    [1., 1., 1., ..., 2., 2., 2.],
    [1., 1., 1., ..., 2., 2., 2.],
    [1., 1., 1., ..., 1., 2., 2.]],

   ...,

   [[1., 1., 1., ..., 1., 1., 0.],
    [1., 1., 1., ..., 1., 1., 0.],
    [1., 1., 1., ..., 1., 1., 0.],
    ...,
    [1., 1., 1., ..., 1., 1., 1.],
    [1., 1., 1., ..., 1., 1., 1.],
    [1., 1., 1., ..., 1., 1., 1.]])

into a pandas dataframe with columns 'x' = index 2 (right), 'y' = index 1 (down), 'z' = index 0 ( the 27 "different" arrays) and 'v' = the values in it. df.columns=['x','y','z','v']

I'm relatively new to python, do you know how I should code this?

Thanks !

Answer 1

This does it in a primitive way.

import numpy as np
import pandas as pd

data = np.ones( (27,77,77) )

rows = []
for i,plane in enumerate(data):
    for j,row in enumerate(plane):
        for k,col in enumerate(row):
            rows.append( [k,j,i,col] )

df = pd.DataFrame( rows, columns=['x','y','z','val'])
print(df)

Output:

C:\tmp>python x.py
         x   y   z  val
0        0   0   0  1.0
1        1   0   0  1.0
2        2   0   0  1.0
3        3   0   0  1.0
4        4   0   0  1.0    
...     ..  ..  ..  ...
160078  72  76  26  1.0
160079  73  76  26  1.0
160080  74  76  26  1.0
160081  75  76  26  1.0
160082  76  76  26  1.0

[160083 rows x 4 columns]

C:\tmp>