Unable to convert 3d array to data frame python

Question

I have a 3d list

l=[ [ [1,"ab",119.0] ] ,  [ [2,"cd",129.0] ] ,  [ [ 3,"ef",139.0] ] ]

Code

 import pandas as pd , numpy as np
 l=[ [ [1,"ab",119.0] ] , [ [2,"cd",129.0] ] , [ [ 3,"ef",139.0] ] ]
 b=np.array(l)
 print(pd.DataFrame(l))
 print(pd.DataFrame(b))

Conversion of this list to data frame is possible . But when I convert this list to array and then convert the array to data frame I'm getting value Error -Must pass 2d input . Why is this error is generated in case of numpy array and not in list ???

Edgar Ramírez Mondragón · Accepted Answer · 2018-08-31 05:49:21Z

2

When you pass l to the pd.DataFrame constructor, it reads l as a list of objects, and thus returns a dataframe with one column consisting of the lists inside l:

                0
 0  [1, ab, 119.0]
 1  [2, cd, 129.0]
 2  [3, ef, 139.0]

When you convert l to a np.array, you get a 3d array (3, 1, 1):

[
  [
    ['1' 'ab' '119.0']
  ],
  [
    ['2' 'cd' '129.0']
  ],
  [
    ['3' 'ef' '139.0']
  ]
]

pandas cannot convert this 3d array into a 2d dataframe, thus the error.

If you actually type in your list like this

l = [[1, "ab", 119.0], [2, "cd", 129.0], [3, "ef", 139.0]]

you should have no problem passing in either the list or the array. You would get this dataframe:

   0   1      2
0  1  ab  119.0
1  2  cd  129.0
2  3  ef  139.0

answered Aug 31, 2018 at 5:49

Edgar Ramírez Mondragón

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