numpy.where condition to select specific vertical columns in 2D array

Question

say we have

a = numpy.arange(25).reshape(5,5)

> array([[ 0,  1,  2,  3,  4],
         [ 5,  6,  7,  8,  9],
         [10, 11, 12, 13, 14],
         [15, 16, 17, 18, 19],
         [20, 21, 22, 23, 24]])

By going

numpy.where(a[1])

> array([0, 1, 2, 3, 4])

and then something like

a[1][numpy.where(a[1])]

> array([5, 6, 7, 8, 9])

I can select the horizontal rows of an array and the respective values, However how can I have a similar where condition to select only specific vertical columns

ie.

numpy.where(condition)

> array([1, 6, 11, 16, 21])

sacuL · Accepted Answer · 2018-10-09 22:00:32Z

1

I'm not sure exactly if this is what you mean, but you can index columns using [:,column_number], where : stands for "all rows":

a[:,1][numpy.where(a[1])]

# array([ 1,  6, 11, 16, 21])

The above, however, is equivalent to simply a[:,1]:

>>> a[:,1]
array([ 1,  6, 11, 16, 21])

answered Oct 9, 2018 at 22:00

sacuL

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2 Comments

TheMagicalMuffinMan Over a year ago

perfect thanks, although whats does the comma , stand for?

sacuL Over a year ago

Thats how you separate the "row" index and the "column" index. So [2,3] would select row 2, column 3

Paolo Irrera · Accepted Answer · 2018-10-09 22:01:43Z

1

Have a look at this tutorial to learn how to apply slicing on numpy arrays (https://docs.scipy.org/doc/numpy-1.15.1/reference/arrays.indexing.html). As for your question, the answer is:

a[:,1]

answered Oct 9, 2018 at 22:01

Paolo Irrera

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