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Searching in a NumPy array

  • Last Updated : 01 Oct, 2020

Numpy provides various methods for searching different kinds of numerical values, in this article, we will cover two important ones.

  • numpy.where()
  • numpy.searchsorted()

1. numpy.where:() It returns the indices of elements in an input array where the given condition is satisfied.

Syntax: numpy.where(condition[, x, y]) 

Parameters:

  • condition : When True, yield x, otherwise yield y.
  • x, y : Values from which to choose. x, y and condition need to be broadcastable to some shape.

Returns:
out : [ndarray or tuple of ndarrays] If both x and y are specified, the output array contains elements of x where condition is True, and elements from y elsewhere.

If only condition is given, return the tuple condition.nonzero(), the indices where condition is True.

The following example demonstrates how to search using where().

Python3






# importing the module
import numpy as np
  
# creating the array
arr = np.array([10, 32, 30, 50, 20, 82, 91, 45])
  
#  printing arr
print("arr = {}".format(arr))
  
#  looking for value 30 in arr and storing its index in i
i = np.where(arr == 30)
print("i = {}".format(i))

Output:

arr = [10 32 30 50 20 82 91 45]
i = (array([2], dtype=int64),)

As you can see variable i is an iterable with the index of our searched value as the first element.  We can make it look better by replacing the last print statement with

print("i = {}".format(i[0]))

This will change the final output to

arr = [10 32 30 50 20 82 91 45]
i = [2]

2. numpy.searchsorted(): The function is used to find the indices into a sorted array arr such that, if elements are inserted before the indices, the order of arr would be still preserved. Here, a binary search is used to find the required insertion indices.

Syntax : numpy.searchsorted(arr, num, side=’left’, sorter=None)

Parameters :

  • arr : [array_like] Input array. If sorter is None, then it must be sorted in ascending order, otherwise sorter must be an array of indices that sort it.
  • num : [array_like]The Values which we want to insert into arr.
  • side : [‘left’, ‘right’], optional.If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of a).
  • num : [array_like, Optional] array of integer indices that sort array a into ascending order. They are typically the result of argsort.

Return : [indices], Array of insertion points with the same shape as num.

The following example explains the use of searchsorted().

Python3




# importing the module
import numpy as np
  
# creating the array
arr = [1, 2, 2, 3, 3, 3, 4, 5, 6, 6]
print("arr = {}".format(arr))
  
# left-most 3
print("left-most index = {}".format(np.searchsorted(arr, 3, side="left")))
  
# right-most 3
print("right-most index = {}".format(np.searchsorted(arr, 3, side="right")))

Output:

arr = [1, 2, 2, 3, 3, 3, 4, 5, 6, 6]
left-most index = 3
right-most index = 6

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