To evaluate a 3D Laguerre series at points x, use the polynomial.laguerre.lagval3d() 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, y, or ... Read More

To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, 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 coefficients ... Read More

To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, 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 coefficients ... Read More

To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, 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 coefficients ... Read More

To differentiate a Legendre series, use the polynomial.laguerre.legder() method in Python. Returns the Legendre series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl. 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 the number of derivatives taken, must be non-negative. (Default: 1). The 3rd parameter, scl is a scalar. Each differentiation is multiplied by scl. The end result is multiplication by scl**m. This is ... 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

To evaluate a 3-D Hermite_e series on the Cartesian product of x, y and z, use the hermite_e.hermegrid3d(x, y, z, c) method in Python. The method returns the values of the two dimensional polynomial at points in the Cartesian product of x, y and z. The parameters are x, y, z. The three dimensional series is evaluated at the points in the Cartesian product of x, y, and z. If x, `y`, or z 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 ... Read More

The idxmax() method of the pandas series constructor is used to get the index label of maximum value over the series data.As we know, the pandas series is a single-dimensional data structure object with axis labels. And we can access the label of a maximum value of the series object by applying the idxmax() method to that series object.The output of the idxmax method is an index value, which refers to the label name or row indices where the largest value exists. The data type of the idxmax() method has the same type of series index labels.If the maximum value ... Read More

The series.gt() method in the pandas constructor performs the Greater Than condition operation between the elements of a series object with another (example: with series, or with scalar, or with list-like object). And it is equal to “series > Other”.Here we will see how the series.gt() method applies the Greater Than conditional operation on two input objects if their elements have string type data. In this case, the comparison is done with their ASCII values.We only need to compare a string element with a corresponding element with the same data type. Otherwise, it will raise the TypeError. We cannot compare ... Read More

By using pandas series.gt() function, we can apply the Greater Than condition to the elements of a series with list elements. The series.gt() method is used to apply the element-wise Greater Than comparison operation between two objects. The two objects are series and other (series, scalar of sequence).Example 1Given below is an example of how the gt() method will apply Greater Than condition between series and list. Here, we will see how the series.gt() method works for series and a list.import pandas as pd import numpy as np # create pandas Series s = pd.Series([9, 103, 18, 31, 92]) ... Read More