How to get element-wise true division of an array using Numpy? Last Updated : 13 Mar, 2023 Summarize Comments Improve Suggest changes Share Like Article Like Report True Division in Python3 returns a floating result containing the remainder of the division. To get the true division of an array, NumPy library has a function numpy.true_divide(x1, x2). This function gives us the value of true division done on the arrays passed in the function. To get the element-wise division we need to enter the first parameter as an array and the second parameter as a single element. Syntax: np.true_divide(x1,x2) Parameters: x1: The dividend arrayx2: divisor (can be an array or an element) Return: If inputs are scalar then scalar; otherwise array with arr1 / arr2(element- wise) i.e. true division Now, let's see an example: Example 1: Python3 # import library import numpy as np # create 1d-array x = np.arange(5) print("Original array:", x) # apply true division # on each array element rslt = np.true_divide(x, 4) print("After the element-wise division:", rslt) Output : Original array: [0 1 2 3 4] After the element-wise division: [0. 0.25 0.5 0.75 1. ] The time complexity of applying true division on each array element using NumPy's true_divide() function is also O(n), since we're applying a single operation to each element in the array. In this case, since the size of the array is 5, the time complexity of this operation is O(5) = O(1). The auxiliary space complexity of this code is O(n), since we're creating a new array rslt with the same number of elements as the original array x. However, since the size of the array is fixed at 5, the space complexity of this code is O(5) = O(1). Example 2: Python3 # import library import numpy as np # create a 1d-array x = np.arange(10) print("Original array:", x) # apply true division # on each array element rslt = np.true_divide(x, 3) print("After the element-wise division:", rslt) Output: Original array: [0 1 2 3 4 5 6 7 8 9] After the element-wise division: [0. 0.33333333 0.66666667 1. 1.33333333 1.66666667 2. 2.33333333 2.66666667 3. ] Time complexity: O(n), where n is the length of the array x. Auxiliary space: O(n), as a new array of size n is created to store the result of the element-wise division. Comment More infoAdvertise with us Next Article How to get element-wise true division of an array using Numpy? 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