import numpy as np
a=np.array([ [1,2,3],[4,5,6],[7,8,9]])
How can I get zeroth index column? Expecting output [[1],[2],[3]] a[...,0] gives 1D array. Maybe next question answers this question.
How to get last 2 columns of a? a[...,1:2] gives second column only, a[...,2:3] gives last 2 columns, but a[...,3] is invalid dimension. So, how does it work?
By the way, operator ... and : have same meaning? a[...,0] and a[:,0] give same output. Can someone comment here?
numpy indexing is built on python list conventions, but extended to multi-dimensions and multi-element indexing. It is powerful, but complex, but sooner or later you should read a full indexing documentation, one that distinguishes between 'basic' and 'advanced' indexing.
Like range and arange, slice index has a 'open' stop value
In [111]: a = np.arange(1,10).reshape(3,3)
In [112]: a
Out[112]:
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
Indexing with a scalar reduces the dimension, regardless of where:
In [113]: a[1,:]
Out[113]: array([4, 5, 6])
In [114]: a[:,1]
Out[114]: array([2, 5, 8])
That also means a[1,1] returns 5, not np.array([[5]]).
Indexing with a slice preserves the dimension:
In [115]: a[1:2,:]
Out[115]: array([[4, 5, 6]])
so does indexing with a list or array (though this makes a copy, not a view):
In [116]: a[[1],:]
Out[116]: array([[4, 5, 6]])
... is a generalized : - use as many as needed.
In [117]: a[...,[1]]
Out[117]:
array([[2],
[5],
[8]])
You can adjust dimensions with newaxis or reshape:
In [118]: a[:,1,np.newaxis]
Out[118]:
array([[2],
[5],
[8]])
Note that trailing : are automatic. a[1] is the same as a[1,:]. But leading ones must be explicit.
List indexing also removes a 'dimension/nesting layer'
In [119]: alist = [[1,2,3],[4,5,6]]
In [120]: alist[0]
Out[120]: [1, 2, 3]
In [121]: alist[0][0]
Out[121]: 1
In [122]: [l[0] for l in alist] # a column equivalent
Out[122]: [1, 4]
import numpy as np
a=np.array([ [1,2,3],[4,5,6],[7,8,9]])
a[:,0] # first colomn
>>> array([1, 4, 7])
a[0,:] # first row
>>> array([1, 2, 3])
a[:,0:2] # first two columns
>>> array([[1, 2],
[4, 5],
[7, 8]])
a[0:2,:] # first two rows
>>> array([[1, 2, 3],
[4, 5, 6]])
a[:,0] # first colomn doesn't column start with zero-index (as in cpython objects)?
a[:,0].Tto get there. NBprint(a)to see what's column, what's rowa[:,0]is 1d, so.Tdoes nothing.