numpy.take() in Python Last Updated : 08 Mar, 2024 Comments Improve Suggest changes Like Article Like Report The numpy.take() function returns elements from array along the mentioned axis and indices. Syntax: numpy.take(array, indices, axis = None, out = None, mode ='raise') Parameters : array : array_like, input array indices : index of the values to be fetched axis : [int, optional] axis over which we need to fetch the elements; By Default[axis = None], flattened input is used mode : [{‘raise’, ‘wrap’, ‘clip’}, optional] mentions how out-of-bound indices will behave raise : [default]raise an error wrap : wrap around clip : clip to the range out : [ndarray, optional]to place result within array Returns : ndarray; array has the same type Python # Python Program illustrating # numpy.take method import numpy as geek #array = geek.arange(10).reshape(2, 5) array = [[5, 6, 2, 7, 1], [4, 9, 2, 9, 3]] print("Original array : \n", array) # indices = [0, 4] print("\nTaking Indices\n", geek.take(array, [0, 4])) # indices = [0, 4] with axis = 1 print("\nTaking Indices\n", geek.take(array, [0, 4], axis = 1)) Output : Original array : [[5, 6, 2, 7, 1], [4, 9, 2, 9, 3]] Taking Indices [5 1] Taking Indices [[5 1] [4 3]] Note : These codes won't run on online IDE's. So please, run them on your systems to explore the working. Comment More infoAdvertise with us Next Article numpy.take() in Python M Mohit Gupta_OMG Improve Article Tags : Python Python-numpy Python numpy-Indexing Practice Tags : python Similar Reads numpy.subtract() in Python numpy.subtract() function is used when we want to compute the difference of two array.It returns the difference of arr1 and arr2, element-wise.Syntax : numpy.subtract(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj], ufunc 'subtract' 3 min read numpy.trim_zeros() in Python numpy.trim_zeros function is used to trim the leading and/or trailing zeros from a 1-D array or sequence. Syntax: numpy.trim_zeros(arr, trim) Parameters: arr : 1-D array or sequence trim : trim is an optional parameter with default value to be 'fb'(front and back) we can either select 'f'(front) and 2 min read Taking input in Python Developers often have a need to interact with users, either to get data or to provide some sort of result. Most programs today use a dialog box as a way of asking the user to provide some type of input. While Python provides us with two inbuilt functions to read the input from the keyboard. input () 3 min read Python NumPy Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.Besides its obvious scientific uses, Numpy can also be used as an efficient m 6 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.reciprocal() in Python The numpy.reciprocal() is a mathematical function that is used to calculate reciprocal of all the elements in the input array. Syntax :numpy.reciprocal(x, /, out=None, *, where=True) Parameters : x[array_like]: Input array or object whose elements needed to test. out [ndarray, optional]: A location 2 min read numpy.select() function - Python The numpy.select() function is used to construct an array by selecting elements from a list of choices based on multiple conditions. It is particularly useful when dealing with conditional replacements or transformations in NumPy arrays. Example:Pythonimport numpy as np arr = np.array([10, 20, 30, 4 3 min read numpy.who function - Python numpy.who() function print the NumPy arrays in the given dictionary. Syntax : numpy.who(vardict = None) Parameters : vardict : [dict, optional] A dictionary possibly containing ndarrays. Return : Returns âNoneâ. If there is no dictionary passed in or vardict is None then returns NumPy arrays in the 1 min read numpy.asarray() in Python numpy.asarray()function is used when we want to convert input to an array. Input can be lists, lists of tuples, tuples, tuples of tuples, tuples of lists and arrays. Syntax : numpy.asarray(arr, dtype=None, order=None) Parameters : arr : [array_like] Input data, in any form that can be converted to a 2 min read NumPy Tutorial - Python Library NumPy (short for Numerical Python ) is one of the most fundamental libraries in Python for scientific computing. It provides support for large, multi-dimensional arrays and matrices along with a collection of mathematical functions to operate on arrays.At its core it introduces the ndarray (n-dimens 3 min read Like