Python | Find elements within range in numpy Last Updated : 12 Mar, 2019 Comments Improve Suggest changes Like Article Like Report Given numpy array, the task is to find elements within some specific range. Let's discuss some ways to do the task. Method #1: Using np.where() Python3 1== # python code to demonstrate # finding elements in range # in numpy array import numpy as np ini_array = np.array([1, 2, 3, 45, 4, 7, 810, 9, 6]) # printing initial array print("initial_array : ", str(ini_array)); # find elements in range 6 to 10 result = np.where(np.logical_and(ini_array>= 6, ini_array<= 10)) # printing result print("resultant_array : ", result) Output: initial_array : [ 1 2 3 45 4 7 810 9 6] resultant_array : (array([5, 7, 8]),) Method #2: Using numpy.searchsorted() Python3 1== # Python code to demonstrate # finding elements in range # in numpy array import numpy as np ini_array = np.array([1, 2, 3, 45, 4, 7, 9, 6]) # printing initial array print("initial_array : ", str(ini_array)); # find elements in range 6 to 10 start = np.searchsorted(ini_array, 6, 'left') end = np.searchsorted(ini_array, 10, 'right') result = np.arange(start, end) # printing result print("resultant_array : ", result) Output: initial_array : [ 1 2 3 45 4 7 9 6] resultant_array : [5 6 7] Method #3: Using * Python3 1== # Python code to demonstrate # finding elements in range # in numpy array import numpy as np ini_array = np.array([1, 2, 3, 45, 4, 7, 9, 6]) # printing initial array print("initial_array : ", str(ini_array)); # find elements in range 6 to 10 result = ini_array[(ini_array>6)*(ini_array<10)] # printing result print("resultant_array : ", result) Output: initial_array : [ 1 2 3 45 4 7 9 6] resultant_array : [7 9] Comment More infoAdvertise with us Next Article Python | Find elements within range in numpy garg_ak0109 Follow Improve Article Tags : Python Python numpy-program Practice Tags : python Similar Reads Python - Numbers in a list within a given range We are given a list and we are given a range we need to count how many number lies in the given range. For example, we are having a list n = [5, 15, 25, 35, 45, 55, 65, 75] and we are having range lower=20, upper=60 so we need to count how many element lies between this range so that the output shou 4 min read Python | Find smallest element greater than K This problem involves searching through a list to identify the smallest number that is still larger than K. We will explore different methods to achieve this in Python In this article, we'll look at simple ways to find the smallest element greater than k in a list using Python.Using Binary SearchBin 3 min read numpy.find() in Python numpy.core.defchararray.find(arr, substring, start=0, end=None): Finds the lowest index of the sub-string in the specified range. Parameters: arr : array-like or string to be searched. substring : substring to search for. start, end : [int, optional] Range to search in. Returns : An integer array wi 1 min read numpy.fmin() in Python numpy.fmin() function is used to compute element-wise minimum of array elements. This function compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first 2 min read Numpy recarray.min() function | Python In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']. Record array 4 min read Index of Non-Zero Elements in Python list We are given a list we need to find all indexes of Non-Zero elements. For example, a = [0, 3, 0, 5, 8, 0, 2] we need to return all indexes of non-zero elements so that output should be [1, 3, 4, 6].Using List ComprehensionList comprehension can be used to find the indices of non-zero elements by ite 2 min read How to use NumPy where() with multiple conditions in Python ? In Python, NumPy has a number of library functions to create the array and where is one of them to create an array from the satisfied conditions of another array. The numpy.where() function returns the indices of elements in an input array where the given condition is satisfied. Syntax: numpy.where( 3 min read numpy.clip() in Python numpy.clip() function is used to Clip (limit) the values in an array. Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Syntax : numpy.clip(a, a_min, 2 min read Numpy recarray.argmin() function | Python In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']. Record array 3 min read Numpy recarray.any() function | Python In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']. Record array 3 min read Like