To integrate a Legendre series, use the polynomial.legendre.legint() method in Python. The method returns the Legendre series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, is added. The scaling factor is for use in a linear change of variable. The 1st parameter, c is an array of Legendre series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.The 2nd parameter, m is an order of integration, must be positive. (Default: ... Read More

To generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermvander() 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 Hermite polynomial. The dtype will be the same as the converted x.The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the resulting ... Read More

To generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermvander() 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 Hermite polynomial. The dtype will be the same as the converted x.The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the resulting ... Read More

To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned.The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None. The "nuc" set as a parameter is the Nuclear norm. Both the Frobenius and nuclear norm orders are only defined for matricesStepsAt first, import the required ... Read More

The “axes” is an attribute of the pandas series object, this attribute is used to access the group of index labels in the given Series. It will return a python list of index labels.The axes attribute collects all the index labels and returns a list object with all index labels in it.Example 1import pandas as pd # create a sample series s = pd.Series({'A':123, 'B':458, "C":556, "D": 238}) print(s) print("Output: ") print(s.axes)ExplanationIn the following example, we initialized a Series with some data. Then we called the axes property on the series object.OutputA   123 B   458 ... Read More

To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned.The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None. The "fro" set as a parameter is the Frobenius norm. Both the Frobenius and nuclear norm orders are only defined for matricesStepsAt first, import the required ... Read More

The pandas.Series.at attribute is used to access the single labeled element from a Series object and It is very similar to the loc in pandas. The “at” attribute takes label data to get or set the series value in that particular label position.It will return a single value based on the index label, and it also uploads the data at that particular label position.Example 1import pandas as pd # create a sample series s = pd.Series({'A':12, 'B':78, "C":56}) print(s) print(s.at['A'])ExplanationIn this following example, we have created a series using a python dictionary and the index will be ... Read More

To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned. The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None.The 3rd parameter axis, if an integer, specifies the axis of x along which to compute the vector norms. If axis is a 2-tuple, it specifies ... Read More

To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned.The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None. The 3rd parameter axis, if an integer, specifies the axis of x along which to compute the vector norms. If axis is a 2-tuple, it specifies ... Read More

To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned. The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None.The 3rd parameter axis, if an integer, specifies the axis of x along which to compute the vector norms. If axis is a 2-tuple, it specifies ... Read More