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Hashing is the procedure of translating a given key into a code. A hash function can be used to substitute the data with a newly generated hash code. Hash algorithms are generally used to offer a digital fingerprint of a file’s contents often used to provide that the file has not been changed by an intruder or virus. Hash functions are also employed by some operating systems to encrypt passwords. Hash functions support a measure of the integrity of a file.Hashing creates use of algorithms that convert blocks of information from a file in a much shorter value or key ... Read More
Public key cryptography is an encryption method that needs a paired public and private key (or asymmetric key) algorithm for secure data communication. Public-key cryptography is also called an asymmetric cryptography. It is a form of cryptography in which a user has a pair of cryptographic keys including public key and a private key.The keys are related numerically, but the private key cannot be changed from the public key. A message encrypted with the public key can be decrypted only with the correlating private key.There are two main branches of public key cryptography are as follows −Public Key Encryption − ... Read More
A spanning tree is a linked and undirected graph subgraph that connects all vertices. Many spanning trees can exist in a graph. The minimum spanning tree (MST) on each graph is the same weight or less than all other spanning trees. Weights are assigned to edges of spanning trees and the sum is the weight assigned to each edge. As V is the number of vertices in the graph, the minimum spanning tree has edges of (V - 1), where V is the number of edges.Finding minimum spanning tree using Kruskal’s algorithmAll of the edges should be arranged in a ... Read More
The pandas series.fillna() method is used to replace missing values with a specified value. This method replaces the Nan or NA values in the entire series object.The parameters of pandas fillna are as follows −Value − it allows us to specify a particular value to replace Nan’s, by default it takes None.Method − it is used to fill the missing values in the reindexed Series. It takes any of these values like ‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, and None(default).Inplace − this parameter takes a boolean value. If it takesTrue, then the modifications are applied to the original series object itself, otherwise, ... Read More
To evaluate a 2D Legendre series at points x, y, use the polynomial.legendre.legval2d() method in Python Numpy. The method returns the values of the two dimensional Legendre series at points formed from pairs of corresponding values from x and y.The 1st parameter is x, y. The two dimensional series is evaluated at the points (x, y), where x and y must have the same shape. If x or y is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged and if it isn’t an ndarray it is treated as a scalar.The 2nd parameter ... Read More
To evaluate a 2D Legendre series at points x, y, use the polynomial.legendre.legval2d() method in Python Numpy. The method returns the values of the two dimensional Legendre series at points formed from pairs of corresponding values from x and y.The 1st parameter is x, y. The two dimensional series is evaluated at the points (x, y), where x and y must have the same shape. If x or y is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged and if it isn’t an ndarray it is treated as a scalar.The 2nd parameter ... Read More
To evaluate a Legendre series at points x, use the polynomial.legendre.legval() method in Python Numpy. The 1st parameter is x. If x is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, x or its elements must support addition and multiplication with themselves and with the elements of c.The 2nd parameter, C, an array of coefficients ordered so that the coefficients for terms of degree n are contained in c[n]. If c is multidimensional the remaining indices enumerate multiple polynomials. In the two dimensional case the ... Read More
To evaluate a 3D Legendre series on the Cartesian product of x, y and z use the polynomial.legendre.leggrid3d() method in Python Numpy. The method returns the values of the three dimensional Chebyshev series at points in the Cartesian product of x, and z. If c has fewer than three 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 + y.shape + z.shape.The 1st parameter is x, y, z. The three dimensional series is evaluated at the points in the Cartesian product of x, y and z. If ... Read More
The pandas Series.factorize() method is used to encode the series object as an enumerated type or categorical variable. This method generates the numeric representation of the series data.The output of this Series.factorize() method is a tuple and it has two elements one is indicating codes and another element indicates uniques.Example 1In the following example, we will see how the series.factorize() method encodes the elements of the series object.# importing pandas package import pandas as pd # create a series s = pd.Series({'A':"aa", 'B':"bb", "C":"cc"}) print(s) result = s.factorize() print(result)ExplanationHere the series object is created by using a python ... Read More
To evaluate a 3D Legendre series on the Cartesian product of x, y and z use the polynomial.legendre.leggrid3d() method in Python Numpy. The method returns the values of the three dimensional Chebyshev series at points in the Cartesian product of x, and z. If c has fewer than three 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 + y.shape + z.shape.The 1st parameter is x, y, z. The three dimensional series is evaluated at the points in the Cartesian product of x, y and z. If ... Read More