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In the pandas series constructor, there is a method called ge() which is used to apply Greater Than or Equal to comparison operation between elements of two pandas series objects.The output of this method is a new series object with boolean values(True Or False). If True, the element which is Greater than or Equal to the corresponding element in other series objects. It gives False for remaining values.There are 3 parameters for this ge() method, which is fill_value, other, and level. The other parameter takes the 2nd input (series or a scalar), fill_value parameter takes None or float value, used ... Read More

By using the series.ge() method we can apply the Greater Than or Equal to comparison operation on elements of the series with a python list. The functionality of this ge() method in pandas series class is to check Greater Than or Equal to compare operation between elements of a series with another.Here another is one of the parameters of this ge() method, by using this we can give our second input (series or a scalar) and also we can apply this ge() Greater Than or Equal to comparison operation between series and a python list.Example 1In the following example, we ... Read More

The series.rfloordiv() function is used to apply the integer division operation to a pandas series objective by others, and it performs an element-wise division operation. The method rfloordiv is called reverse floordiv and is similar to the floordiv() method, but instead of calculating series // other it calculates other // series.The method supports the substitution of missing values in any of the inputs by using one of its parameter called fill_value. And the method has two more parameters called other, and level. Another is a 2nd input object (series or scalar), and the level is broadcast across a level.Example 1In ... Read More

The Integer division operation can also be applied to the elements of pandas Series by another Python sequence like a list or a tuple.To perform integer division operations we can use the floordiv() method In the pandas series class. Which is used to apply an element-wise integer division operation between a pandas series object by the corresponding element of another Series or a scalar or list-like object.Here we will discuss some examples to understand how the floordiv() method performs the integer division operation to the elements of a pandas Series by the elements of a Python list.Example 1Below is an ... Read More

In this problem, we must build C++ code to determine whether or not an array may be divided into two equal subarrays. Also, we have to check the condition if the sum of all the elements in both subarrays is exactly the same or not. The partitioning problem is a variant of the Subset Sum Problem, which is in turn a variant of the Knapsack Problem. We'll use the C++ programming language to tackle the partition problem. We must return a string with a Yes or No depending on whether the specified condition is fulfilled or not.Inputarr[] = {6, 4, ... Read More

The operation integer division is also called floor division, which is equivalent to // in python. And it is a binary operation nothing but an element-wise division operation that returns a new value.In the pandas series class, there is a method called floordiv() which performs the element-wise integer division operation between a series object and a scalar. And this method can also be used to perform floor division between two series objects.The output of this method is a new series with the result of the operation. And it has 3 parameters, which are fill_value, other, and level. The other parameter ... Read More

The floordiv() method in the pandas series constructor is used to perform integer division of two series objects (an element-wise division operation) and the Floor Division operation is also called Integer Division, which is equivalent to // in python. The method supports the substitution of missing values in any of the inputs.The method returns a series with resultant values, and the method has 3 parameters, which are fill_value, other, and level. The other parameter is nothing but the 2nd input object either series or a scalar.The fill_value parameter is used to replace a specific value in the place of missing ... Read More

The pandas series.last() method is used to return final periods based on the date offset. By applying this series.last() method we can get the final periods of the time series object. The last method is very similar to the pandas series.first() method, here we can get the final periods instead of the initial periods.The series.last() method has a parameter called offset which is used to mention the length of the offset data to select the rows within the given limit.The last() method will return a now Series object with resultant rows and it will raise the TypeError if the index ... Read More

The parallel array is also called the structure array.Definition − A parallel array can be defined as multiple arrays in which the ith elements are closely related, and together, they constitute an entity. An array is a fundamental feature in the C++ language. Making parallel arrays helps us in comparing two or more arrays.For instance, first_name = ['John', 'Dexter', 'Fredd', 'Hank', 'james'] last_name = ['Jocab', 'Jonas', 'smith', 'lee', 'banner'] height = [160, 148, 231, 153, 162]Approach for Making a Parallel ArraySearching and sorting are some of the essential features required to form a parallel array.SearchingSearching is based on specific values ... Read More

The pandas series.last_valid_index() method is used to get the index of the last valid element from the given series object. This means the last_valid_index() method returns the index of the last non_null element of the series.It will return a single scalar based on the type of series index, and it will return None if the given series has all null/NA values or if it is empty. The method doesn’t have any parameters.Example 1Let’s create a pandas series object and retrieve the last valid index by using the last_valid_index() method.# importing packages import pandas as pd import numpy as np ... Read More