Searching in a NumPy array
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
