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To divide one Hermite_e series by another, use the polynomial.hermite.hermediv() method in Python Numpy. The method returns an array of Hermite_e series coefficients representing the quotient and remainder.Returns the quotient-with-remainder of two Hermite_e series c1 / c2. The arguments are sequences of coefficients from lowest order “term” to highest, e.g., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters, c1 and c2 are 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite as HCreate 1-D arrays of Hermite_e series coefficients −c1 ... Read More

To multiply one Hermite_e series to another, use the polynomial.hermite.hermemul() method in Python Numpy. The method returns an array representing the Hermite_e series of their product. Returns the product of two Hermite_e series c1 * c2. The arguments are sequences of coefficients, from lowest order “term” to highest, e.g., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate 1-D arrays of Hermite_e series coefficients −c1 = np.array([1, 2, 3]) c2 ... Read More

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 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 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 for ... Read More

To multiply the Hermite_e series by x, where x is the independent variable, use the polynomial.hermite.hermemulx() method in Python Numpy. The method returns an array representing the result of the multiplication. The parameter, c is a 1-D array of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate an array −c = np.array([1, 2, 3])Display the array −print("Our Array...", c)Check the Dimensions −print("Dimensions of our Array...", c.ndim)Get the Datatype −print("Datatype of our Array object...", c.dtype)Get the Shape −print("Shape of our Array object...", c.shape)To multiply the Hermite_e ... Read More

To subtract one Hermite_e series to another, use the polynomial.hermite.hermesub() method in Python Numpy. The method returns an array representing the Hermite_e series of their difference. Returns the difference of two Hermite_e series c1 - c2. The sequences of coefficients are from lowest order term to highest, i.e., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters c1 and c2 are 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate 1-D arrays of Hermite_e series coefficients −c1 = np.array([1, ... Read More

To add one Hermite_e series to another, use the polynomial.hermite.heremadd() method in Python Numpy. The method returns an array representing the Hermite_e series of their sum. Returns the sum of two Hermite_e series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters c1 and c2 are 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate 1-D arrays of Hermite_e series coefficients −c1 ... Read More

To convert a polynomial to a Legendre series, use the legendre.poly2lag() method in Python Numpy. Convert an array representing the coefficients of a polynomial ordered from lowest degree to highest, to an array of the coefficients of the equivalent Legendre series, ordered from lowest to highest degree. The method returns a 1-D array containing the coefficients of the equivalent Legendre series. The parameter pol, is a 1-D array containing the polynomial coefficientsStepsAt first, import the required library −import numpy as np from numpy.polynomial import legendre as LCreate an array using the numpy.array() method −c = np.array([1, 2, 3, 4, 5])Display ... Read More

In the pandas series constructor, the method called dropna() is used to remove missing values from a series object. And it does not update the original series object with removed NaN values instead of updating the original series object, it will return another series object with updated values.The parameters of the dropna() method are axis, inplace, and how.Example 1# importing packages import pandas as pd import numpy as np # Creating Series objects sr = pd.Series([42, np.nan, 55, 42, np.nan, 73, np.nan, 55, 76, 87], index=list("ABCDEFGHIJ")) print('Series object:', sr) # Remove missing elements result = sr.dropna() ... Read More