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Sensitive information is the classified information that should be protected and is inaccessible to external parties unless specifically granted permission. The data can be in physical or electronic form, but sensitive information is regarded as private information or data. An ethical or legal reason can warrant the need to have complex restrictions on person who can access personal or an organization sensitive information, particularly when it pertains to individual privacy and property rights.For example, a data breach in a government commission can expose government secrets to foreign powers. The same can be used to individual or organisation data, which can ... Read More
To get the position of minimum value of a pandas series object we can use a function called argmin().The argmin() is the method of the pandas series constructor, which is used to get the row position of the smallest value from the series. The output of the argmin() method is an integer value. If the pandas series object having the Nan values, then the argmin() method will identify the smallest number by neglecting those Nan values.If the minimum value is located in multiple index positions, then the first occurrence value position is taken as output.Example 1# import pandas package import ... Read More
Transporter data flows are digitally encoded units of data in which the transfer, storage, or processing takes place in more than one union state. The information can be moved physically by magnetic media, such as tapes, disks, or transmitted electronically over a terrestrial line, submarine cable, or satellite connection.The significant fact is that the information transported or transmitted by these two modes either undergoes some type of information processing, or is accessed across an international frontier.Transporter data flow supports business process streamlining, enhance market access, and keep business relevance in a fast-evolving business landscape. The maturing business and technological landscape, ... Read More
To generate a pseudo Vandermonde matrix of the Legendre polynomial with x, y, z sample points, use the legendre.legvander3d() method in Python Numpy. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z).The parameters, x, y ,z are arrays of point coordinates, all of the same shape. The dtypes will be converted to either float64 or complex128 depending on whether any of the elements are complex. Scalars are converted to 1-D arrays. The parameter, deg is a list of maximum degrees of the form [x_deg, y_deg, z_deg].StepsAt first, import the required library −import numpy as np from ... Read More
To generate a pseudo Vandermonde matrix of the Legendre polynomial, use the legendre.legvander2d() method in Python Numpy. The method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where The last index is the degree of the corresponding Legendre polynomial. The dtype will be the same as the converted x.The parameter, x, y is an array of point coordinates, all of the same shape. The dtypes will be converted to either float64 or complex128 depending on whether any of the elements are complex. Scalars are converted to 1-D arrays.The parameter, deg is ... Read More
To evaluate a 2D Legendre series on the Cartesian product of x and y, use the polynomial.legendre.leggrid2d() method in Python Numpy. The method returns the values of the two dimensional Chebyshev series at points in the Cartesian product of x and y. If c has fewer than two dimensions, ones are implicitly appended to its shape to make it 2-D. The shape of the result will be c.shape[2:] + x.shape + y.shape.The 1st parameter is x, y. The two dimensional series is evaluated at the points in the Cartesian product of x and y. If x or y is a ... Read More
To evaluate a 3D Legendre series at points x, y, z use the polynomial.legendre.legval3d() method in Python Numpy. The method returns the values of the multidimensional polynomial on points formed with triples of corresponding values from x, y, and z.If c has fewer than 3 dimensions, ones are implicitly appended to its shape to make it 3-D. The shape of the result will be c.shape[3:] + x.shape. The 1st parameter is x, y, z. The three dimensional series is evaluated at the points (x, y, z), where x, y, and z must have the same shape. If any of x, ... Read More
To generate a pseudo Vandermonde matrix of the Hermite_e polynomial and x, y, z sample points, use the hermite_e.hermevander3d() in Python Numpy. The method returns the pseudoVandermonde matrix. The parameter, x, y, z are arrays of point coordinates, all of the same shape. The dtypes will be converted to either float64 or complex128 depending on whether any of the elements are complex. Scalars are converted to 1-D arrays. The parameter, deg is the list of maximum degrees of the form [x_deg, y_deg, z_deg].StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate arrays of ... Read More
To generate a pseudo Vandermonde matrix of the Legendre polynomial, use the legendre.legvander2d() method in Python Numpy. The method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where The last index is the degree of the corresponding Legendre polynomial. The dtype will be the same as the converted x.The parameter, x, y is an array of point coordinates, all of the same shape. The dtypes will be converted to either float64 or complex128 depending on whether any of the elements are complex. Scalars are converted to 1-D arrays. The parameter, deg ... Read More
In the pandas series constructor, there is a method called argmax() which is used to get the position of maximum value over the series data.The pandas series is a single-dimensional data structure object with row index values. By using row index values we can access the data.The argmax() method in the pandas series is used to get the positional index of the maximum value of the series object. The output of the argmax method is an integer value, which refers to the position where the largest value exists.Example 1# import pandas package import pandas as pd import numpy as np ... Read More