delete last item in all rows and columns numpy.ndarray

Question

I am trying to delete the last item in both the rows and columns in my numpy.ndarray ( type = class numpy.ndarray ). My array has 30 rows and 180 columns (ie 180 values per row). I have tried numpy.delete but this simply removes the whole row/column.

To illustrate what I want to achieve I created the following example in Python using and array and nested for loops:

a = np.array([[[1,2,3,4,5,6],[1,2,3,4],[1,2,3,4]],[[1,2,3,4,5,6],[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4]],[[1,2,3,4],[1,2,3,4]]])
for list in a:
    for sublist in list:
        del sublist[-1]

Using

print(a) 

Gives the following array:

 [[[1, 2, 3, 4, 5, 6], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4, 5, 6], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4]] [[1, 2, 3, 4], [1, 2, 3, 4]]] 

Using

print(list)

after the for loops gives:

[[1, 2, 3, 4, 5], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3, 4, 5], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3]]
[[1, 2, 3], [1, 2, 3]]

Unfortunately using this on my array gives the following error:

TypeError: 'numpy.float64' object does not support item deletion

Thanks

---

Update: I am extracting my information from a grid NetCDF file. I have changed the word list to l since list is a Python keyword. This didn't change it for me.

This provides a good example of my array:

c = np.arange(5400).reshape(30,180)
for l in c:
    for i in l:
        del i[-1]

When I run this code I get the following error:

Traceback (most recent call last):   File "main.py", line 18, in <module>
    del i[-1] 
 TypeError: 'numpy.int64' object does not support item deletion

Answer 1

del i[-1] is a list operation. np.array does not support that.

Count the occurrences of a specific value and remove them at the same time demonstrates the differences between lists and arrays when it comes to deletion.

Your example a is object dtype, containing lists

In [111]: a.shape
Out[111]: (11,)
In [112]: [len(i) for i in a]
Out[112]: [3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2]
In [113]: a[0]
Out[113]: [[1, 2, 3, 4, 5, 6], [1, 2, 3, 4], [1, 2, 3, 4]]

a[0] is a 3 element list, with sublists of different length.

It's not clear what you want to delete. Delete elements from a , or elements from each element of a , or elements from the sublists of those elements.

Furthermore, if the real data is from NetCDF it might actually a multidimensional array. Or if object dtype, the elements might themselves be (2d) arrays.

In case, slicing is the right way to remove rows/columns from an array:

In [114]: a = np.arange(12).reshape(3,4)
In [115]: a
Out[115]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
In [116]: a[:-1, :-1]
Out[116]: 
array([[0, 1, 2],
       [4, 5, 6]])

The result is a view ; it does not change a itself. a = a[:-1, :-1].copy() is the cleanest way to creates a reduced size array without leaving the any of the original around.