CODEWITHSUNDEEP
pythonnumpy
Ferguzz
Ferguzz

Reputation: 6107

find row or column containing maximum value in numpy array

How do I find the row or column which contains the array-wide maximum value in a 2d numpy array?

Upvotes: 20

Views: 48594

Answers (5)

jared
jared

Reputation: 550

You can use np.argmax() directly.

The example is copied from the official documentation.

>>> a = np.arange(6).reshape(2,3) + 10
>>> a
array([[10, 11, 12],
       [13, 14, 15]])
>>> np.argmax(a)
5
>>> np.argmax(a, axis=0)
array([1, 1, 1])
>>> np.argmax(a, axis=1)
array([2, 2])

axis = 0 is to find the max in each column while axis = 1 is to find the max in each row. The returns is the column/row indices.

Upvotes: 0

Deverp
Deverp

Reputation: 141

np.argmax just returns the index of the (first) largest element in the flattened array. So if you know the shape of your array (which you do), you can easily find the row / column indices:

A = np.array([5, 6, 1], [2, 0, 8], [4, 9, 3])
am = A.argmax()
c_idx = am % A.shape[1]
r_idx = am // A.shape[1]

Upvotes: 4

ecatmur
ecatmur

Reputation: 157484

If you only need one or the other:

np.argmax(np.max(x, axis=1))

for the column, and

np.argmax(np.max(x, axis=0))

for the row.

Upvotes: 24

Geoff Reedy
Geoff Reedy

Reputation: 36071

You can use np.argmax along with np.unravel_index as in

x = np.random.random((5,5))
print np.unravel_index(np.argmax(x), x.shape)

Upvotes: 27

Akavall
Akavall

Reputation: 86326

You can use np.where(x == np.max(x)).

For example:

>>> x = np.array([[1,2,3],[2,3,4],[1,3,1]])
>>> x
array([[1, 2, 3],
       [2, 3, 4],
       [1, 3, 1]])
>>> np.where(x == np.max(x))
(array([1]), array([2]))

The first value is the row number, the second number is the column number.

Upvotes: 21

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