numpy.vander() function | Python Last Updated : 22 Apr, 2020 Comments Improve Suggest changes Like Article Like Report numpy.vander() function is used to generate a Vandermonde matrix. Syntax : numpy.vander(arr, N = None, increasing = False) Parameters : arr : [ array_like] 1-D input array. N : [int, optional] Number of columns in the output. If N is not specified, a square array is returned (N = len(x)). increasing : [bool, optional] Order of the powers of the columns. If True, the powers increase from left to right, if False (the default) they are reversed. Return : [ndarray] dVandermonde matrix. If increasing is False, the first column is x^(N-1), the second x^(N-2) and so forth. If increasing is True, the columns are x^0, x^1, ..., x^(N-1). Code #1 : Python3 # Python program explaining # numpy.vander() function # importing numpy as geek import numpy as geek arr = geek.array([1, 2, 3, 4, 5]) gfg = geek.vander(arr) print (gfg) Output : [[ 1 1 1 1 1] [ 16 8 4 2 1] [ 81 27 9 3 1] [256 64 16 4 1] [625 125 25 5 1]] Code #2 : Python3 # Python program explaining # numpy.vander() function # importing numpy as geek import numpy as geek arr = geek.array([1, 2, 3, 4, 5]) N = 3 gfg = geek.vander(arr, N) print (gfg) Output : [[ 1 1 1] [ 4 2 1] [ 9 3 1] [16 4 1] [25 5 1]] Code #3 : Python3 # Python program explaining # numpy.vander() function # importing numpy as geek import numpy as geek arr = geek.array([1, 2, 3, 4, 5]) gfg = geek.vander(arr, increasing = True) print (gfg) Output : [[ 1 1 1 1 1] [ 1 2 4 8 16] [ 1 3 9 27 81] [ 1 4 16 64 256] [ 1 5 25 125 625]] Comment More infoAdvertise with us Next Article Introduction to Machine Learning S sanjoy_62 Follow Improve Article Tags : Machine Learning Python-numpy Python numpy-arrayManipulation python Practice Tags : Machine Learningpython Similar Reads Machine Learning Tutorial Machine learning is a branch of Artificial Intelligence that focuses on developing models and algorithms that let computers learn from data without being explicitly programmed for every task. 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