CODEWITHSUNDEEP
pythonpython-3.xnumpy-ndarray
Pritam Deka
Pritam Deka

Reputation: 33

Counting number of elements greater than a certain value in a numy.ndarray

I want to calculate the count of number of elements in a numpy.ndarry which is greater than a certain value. How do I get the required results?

For example:

[[0.25656927 0.31030828 0.23430803 0.25999823 0.20450112 0.19383106
  0.35779405 0.36355627 0.16837767 0.1933686  0.20630316 0.17804974
  0.06902786 0.26209944 0.21310201 0.12016498 0.14213449 0.16639964
  0.33461425 0.15897344 0.20293266 0.14630634 0.2509769  0.17211646
  0.3922994  0.14036047 0.12571093 0.25565785 0.18216616 0.0728473
  0.25328827 0.1476636  0.1873344  0.12253726 0.16082433 0.20678088
  0.33296013 0.03104548 0.14949016 0.05495472 0.1494042  0.32033417
  0.05361898 0.14325878 0.16196126 0.15796155 0.10990247 0.14499696]]

is the array and I want the count of number of elements greater than 0.19214945092486838. Here the value will be 21. How to calculate it?

Upvotes: 1

Views: 4792

Answers (9)

Jasar Orion
Jasar Orion

Reputation: 686

you can use len to count results like this example:

import numpy as np

matrix = np.array([[0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686, 0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646,
  0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417,
  0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696]])

n = len(matrix[matrix > 0.18])
print(n)

Upvotes: 0

Johnson Francis
Johnson Francis

Reputation: 271

arr=np.array([0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634 ,0.2509769 , 0.17211646,
  0.3922994 , 0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636 , 0.1873344 , 0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042 , 0.32033417,
  0.05361898, 0.14325878 ,0.16196126, 0.15796155, 0.10990247, 0.14499696])

Count:

arr[np.where(arr>0.19214945092486838)].shape[0]

Upvotes: 0

Jussi Nurminen
Jussi Nurminen

Reputation: 2408

Cleanest way (IMHO):

x > 1 will transform your array x into a boolean one, where elements larger than 1 are True. Then you can count the True values by np.count_nonzero()

Thus, np.count_nonzero(x > 1)

Upvotes: 0

rodvictor
rodvictor

Reputation: 339

The following snippet of code will achieve what you desire :)

import numpy as np
arrayToCheck=np.array([0.25656927, 0.31030828, 0.23430803, 0.25999823, 0.20450112, 0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646,
  0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417,
  0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696])
print ("The number of float numbers above your threshold is " + str(np.sum(a>0.19214945092486838)))

Upvotes: 0

Ray
Ray

Reputation: 321

To get an array of which the item is greater than / less than:

>>> import numpy as np
>>> data = np.arange(12)
>>> data > 5
array([False, False, False, False, False, False,  True,  True,  True,
        True,  True,  True])

Then you just have to find the sum of the array:

>>> (data > 5).sum()
6

Now substitude data with your values, and use (data > 0.19214945092486838) instead.

Upvotes: 0

Renaud
Renaud

Reputation: 2819

With numpy you can try:

Myarray= [ [ your array]]
Value_to_search=0.19214945092486838

Array_greater_than=Myarray>Value_to_search
Nb_Val_greater_than=Array_greater_than.sum()
print(Nb_Val_greater_than)

Upvotes: 0

Edward Cullen
Edward Cullen

Reputation: 66

ar[ar>0.19214945092486838] will provide you list of elements which are higher than the current values. You can take len to get the length

>>> import numpy as np
>>> ar = np.array([0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,0.35779405,0.36355627,0.16837767,0.1933686,0.20630316,0.17804974    ,0.06902786,0.26209944,0.21310201,0.12016498,0.14213449,0.16639964,0.33461425,0.15897344,0.20293266,0.14630634,0.2509769,0.17211646    ,0.3922994,0.14036047,0.12571093,0.25565785,0.18216616,0.0728473,0.25328827,0.1476636,0.1873344,0.12253726,0.16082433,0.20678088    ,0.33296013,0.03104548,0.14949016,0.05495472,0.1494042,0.32033417,0.05361898,0.14325878,0.16196126,0.15796155,0.10990247,0.14499696])

>>> print(len(ar[ar>0.19214945092486838]))
>>> 21

Upvotes: 1

Tom Barron
Tom Barron

Reputation: 1594

Here's one way

my_array = ... the target array ...
result = sum(0.19214945092486838 < x for x in my_array)

Upvotes: 0

lorenzozane
lorenzozane

Reputation: 1279

You can simply do:

import numpy

arr = numpy.asarray([0.25656927, 0.31030828, 0.23430803, 0.25999823, 0.20450112, 0.19383106, 0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974, 0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964, 0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646, 0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473, 0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088, 0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417, 0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696])

print((arr > 0.19214945092486838).sum())

The output is: 21

Upvotes: 2

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