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Tag Archives: Python-numpy

numpy.dtype.base() function returns dtype for the base element of the subarrays, regardless of their dimension or shape. Syntax : numpy.dtype.base() Return : Returns data type… Read More
numpy.imag() function return the imaginary part of the complex argument. Syntax : numpy.imag(arr) Parameters : arr : [array_like] Input array. Return : [ndarray or scalar]… Read More
In this numpy.real_if_close()function, if complex input returns a real array then complex parts are close to zero. Syntax : numpy.real_if_close(arr, tol = 100) Parameters :… Read More
numpy.interp() function returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Syntax : numpy.interp(x, xp,… Read More
numpy.indices() function return an array representing the indices of a grid. Compute an array where the subarrays contain index values 0, 1, … varying only… Read More
numpy.ndarray.dtype() function return the data-type of the array’s elements. Syntax : numpy.ndarray.dtype() Parameters : None Return : [numpy dtype object] Return the data-type of the… Read More
numpy.ndarray.resize() function change shape and size of array in-place. Syntax : numpy.ndarray.resize(new_shape, refcheck = True) Parameters : new_shape :[tuple of ints, or n ints] Shape… Read More
numpy.real() function return the real part of the complex argument. Syntax : numpy.real(arr) Parameters : arr : [array_like] Input array. Return : [ndarray or scalar]… Read More
numpy.roots() function return the roots of a polynomial with coefficients given in p. The values in the rank-1 array p are coefficients of a polynomial.… Read More
numpy.nanstd() function compute the standard deviation along the specified axis, while ignoring NaNs. Syntax : numpy.nanstd(arr, axis = None, dtype = None, out = None,… Read More
numpy.correlate() function defines the cross-correlation of two 1-dimensional sequences. This function computes the correlation as generally defined in signal processing texts: c_{av}[k] = sum_n a[n+k]… Read More
All of us are familiar with Fibonacci Series. Each number in the sequence is the sum of the two numbers that precede it. So, the… Read More
Julia is a very new and fast high-level programming language and has the power to compete with python. Like python, Julia is also compatible to… Read More
Array splitting can be vertical, horizontal, or depth-wise. We can use functions hsplit(), vsplit() and dsplit() respectively for the same . We can split arrays… Read More
numpy.intersect1d() function find the intersection of two arrays and return the sorted, unique values that are in both of the input arrays. Syntax: numpy.intersect1d(arr1, arr2,… Read More