Pandas to_numpy() results in an array of lists. How do I get a 2D numpy array from this?

user_3259896 0
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I have a column of lists, and each list contains the same number of values.

If I do 

df['column'].to_numpy()

I get an array of lists:

array([list([0, 4688, 11, 43486, 40508, 13, 5,...
       list([0, 40928, 17707, 22705, 9, 38312, 2..
       list([0, 6766, 368, 3551, 28837,..
      dtype=object)

How do I get a 2D array instead?

pandas numpy python
3 Answers

You can do this:

np.array(df['column'].tolist())

Or you can simply stack them:

np.stack(df['column'].to_numpy())

This will stack your lists on top of each other and output is a 2-D array. You have to make sure lists are of the same length. Numpy arrays are rectangular.

user_49759810

You can use list list comprehension

>>> df
                 A
0  [0, 1, 2, 3, 4]
1  [0, 1, 2, 3, 4]
2  [0, 1, 2, 3, 4]

>>> np.array([x for x in df['A']])
array([[0, 1, 2, 3, 4],
       [0, 1, 2, 3, 4],
       [0, 1, 2, 3, 4]])
user_60756990 
data=np.array(df['column']).reshape(2,2)
  • It will convert your desire columns into array

for 2d array you can use reshape function on numpy But you should have proper value in data to corvert eg (2,2) is used if you have 4 numbers of data it indicate (row,columns)

user_125597350
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