问题
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 (i.e. 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
回答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.
来源:https://stackoverflow.com/questions/43371757/delete-last-item-in-all-rows-and-columns-numpy-ndarray