numpy.atleast_1d() in Python Last Updated : 28 Nov, 2018 Summarize Comments Improve Suggest changes Share Like Article Like Report numpy.atleast_1d()function is used when we want to Convert inputs to arrays with at least one dimension. Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved. Syntax : numpy.atleast_1d(*arrays) Parameters : arrays1, arrays2, ... : [array_like] One or more input arrays. Return : [ndarray] An array, or list of arrays, each with a.ndim >= 1. Copies are made only if necessary. Code #1 : Working Python # Python program explaining # numpy.atleast_1d() function import numpy as geek in_num = 10 print ("Input number : ", in_num) out_arr = geek.atleast_1d(in_num) print ("output 1d array from input number : ", out_arr) Output : Input number : 10 output 1d array from input number : [10] Code #2 : Working Python # Python program explaining # numpy.atleast_1d() function import numpy as geek my_list = [[2, 6, 10], [8, 12, 16]] print ("Input list : ", my_list) out_arr = geek.atleast_1d(my_list) print ("output array : ", out_arr) Output : Input list : [[2, 6, 10], [8, 12, 16]] output array : [[ 2 6 10] [ 8 12 16]] Code #3 : Working Python # Python program explaining # numpy.atleast_1d() function # when inputs are in high dimension import numpy as geek in_arr = geek.arange(9).reshape(3, 3) print ("Input array :\n ", in_arr) out_arr = geek.atleast_1d(in_arr) print ("output array :\n ", out_arr) print(in_arr is out_arr) Output : IInput array : [[0 1 2] [3 4 5] [6 7 8]] output array : [[0 1 2] [3 4 5] [6 7 8]] True' Comment More infoAdvertise with us Next Article Numpy MaskedArray.atleast_1d() function | Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads numpy.atleast_2d() in Python numpy.atleast_2d() function is used when we want to Convert inputs to arrays with at least two dimension. Scalar and 1-dimensional inputs are converted to 2-dimensional arrays, whilst higher-dimensional inputs are preserved. Syntax : numpy.atleast_2d(*arrays) Parameters : arrays1, arrays2, ... : [ar 2 min read numpy.atleast_3d() in Python numpy.atleast_3d() function is used when we want to Convert inputs to arrays with at least three dimension. Scalar, 1 and 2 dimensional inputs are converted to 3-dimensional arrays, whilst higher-dimensional inputs are preserved. Input includes scalar, lists, lists of tuples, tuples, tuples of tuple 2 min read numpy.alen() in Python numpy.alen() function is used to return the length of the first dimension of the input array. Syntax : numpy.alen(arr) Parameters : arr : [array_like] Input array. Return : [int]Length of the first dimension of arr. Code #1 : Python3 # Python program explaining # alen() function import numpy as geek 1 min read numpy.any() in Python The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax :Â numpy.any(a, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters :Â array :[array_like]Input array or object whose elements, we need to test. axis : 3 min read Numpy MaskedArray.atleast_1d() function | Python numpy.MaskedArray.atleast_1d() function is used to convert inputs to masked arrays with at least one dimension.Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved. Syntax : numpy.ma.atleast_1d(*arys) Parameters: arys:[ array_like] One or more input arr 2 min read numpy.floor() in Python The numpy.floor() function returns the largest integer less than or equal to each element in the input array. It effectively rounds numbers down to the nearest whole number. Let's understand with an example:Pythonimport numpy as np a = [0.5, 1.5, 2.5, 3, 4.5, 10.1] res = np.floor(a) print("Floored:" 1 min read Like