Hi I have a list flat which is length 2800, it contains 100 results for each of 28 variables: Below is an example of 4 results for 2 variables
[0,
0,
1,
1,
2,
2,
3,
3]
I would like to reshape the list to an array (2,4) so that the results for each variable are in a single element.
[[0,1,2,3],
[0,1,2,3]]
You can think of reshaping that the new shape is filled row by row (last dimension varies fastest) from the flattened original list/array.
If you want to fill an array by column instead, an easy solution is to shape the list into an array with reversed dimensions and then transpose it:
x = np.reshape(list_data, (100, 28)).T
Above snippet results in a 28x100 array, filled column-wise.
To illustrate, here are the two options of shaping a list into a 2x4 array:
np.reshape([0, 0, 1, 1, 2, 2, 3, 3], (4, 2)).T
# array([[0, 1, 2, 3],
# [0, 1, 2, 3]])
np.reshape([0, 0, 1, 1, 2, 2, 3, 3], (2, 4))
# array([[0, 0, 1, 1],
# [2, 2, 3, 3]])