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The given series is 2, 12, 36, 80, 150...If you clearly observe the series, you will find that the n-th number is n2 + n3.AlgorithmInitialise the number N.Use the series formula to compute the n-th term.Print the result.ImplementationFollowing is the implementation of the above algorithm in C++#include using namespace std; int getNthTerm(int n) { return (n * n) + (n * n * n); } int main() { int n = 7; cout
To return frequency applied on the given CustomBusinessHour Offset object as a string, use the CustomBusinessHour.freqstr property in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-10-25 08:35:10') Create the CustomBusinessHour Offset −cbhOffset = pd.tseries.offsets.CustomBusinessHour(n = 3, weekmask = 'Mon Tue Wed Fri')Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Return frequency applied on the given CustomBusinessHour Offset object as a string −print("Frequency applied on the given CustomBusinessHour Offset object...", cbhOffset.freqstr)ExampleFollowing is the code −import pandas as pd # Set the timestamp ... Read More
We are given with an integer array and an integer variable i.e. ‘X’. The task is to firstly form the subarray from the given array and then multiply all the elements of a subarray with an integer X. At last find out the elements that will contribute the maximum sum.Let us see various input output scenarios for this -In − int arr[] = {2, 4, 1, -5, -2}, X = 3Out − Maximize the subarray sum after multiplying all elements of any subarray with X are: 21Explanation − we are given with an array and an integer variable as X. Firstly, ... Read More
To roll provided date backward, use the CustomBusinessHour.rollback() method in Pandas. At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-12-20 08:35:10') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass −cbhOffset = pd.tseries.offsets.CustomBusinessHour(n = 5, weekmask = 'Mon Tue Wed Fri')Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Roll backward if not on offset −roll_back = cbhOffset.rollback(pd.Timestamp('2021-12-18 08:35:10'))Display the result −print("Roll Backward Result...", roll_back) ExampleFollowing is the code −import pandas as pd # Set the timestamp object in Pandas timestamp = pd.Timestamp('2021-12-20 ... Read More
To move to the next business day, use the CustomBusinessHour.next_bday property in Pandas. At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-12-20 08:35:10') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass −cbhOffset = pd.tseries.offsets.CustomBusinessHour(start ='09:30', end ='18:00', n = 5, weekmask = 'Mon Tue Wed Fri')Display the CustomBusinessHour Offset −print("CustomBusinessHour Offset...", cbhOffset) Display the next business day −print("The next business day...", timestamp + cbhOffset.next_bday)ExampleFollowing is the code −import pandas as pd # Set the timestamp object in Pandas timestamp = pd.Timestamp('2021-12-20 08:35:10') # Display the Timestamp print("Timestamp...", timestamp) ... Read More
To roll provided date forward to next offset only if not on offset, use the CustomBusinessHour.rollforward() method in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-12-20 08:35:10') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass. Weekmask of valid business days −cbhOffset = pd.tseries.offsets.CustomBusinessHour(n = 5, weekmask = 'Mon Tue Wed Fri')Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Roll forward if not on offset −roll = cbhOffset.rollforward(pd.Timestamp('2021-12-30 08:35:10'))Display the result −print("Roll forward Result...", roll) ExampleFollowing is the code −import pandas as ... Read More
You are given the N-th root and the result of it. You need to find the number such that numberN = result.Let's see some examples.Input result = 25 N = 2Output 5The 52 = 25. Hence the output in the above example is 5.Inputresult = 64 N = 3Output4 The 43 = 64. Hence the output in the above example is 4.AlgorithmImplementationFollowing is the implementation of the above algorithm in C++#include using namespace std; int getNthRoot(int result, int n) { int i = 1; while (true) { if (pow(i, n) == result) { return i; } i += 1; } } int main() { int result = 64, N = 6; cout
To create a CustomBusinessHour object, use the pandas.tseries.offsets.CustomBusinessHour() method in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-12-31 08:35:10') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass. Weekmask of valid business days −cbhOffset = pd.tseries.offsets.CustomBusinessHour(n = 5, weekmask = 'Mon Tue Wed Fri')Display the CustomBusinessHour Offset −print("CustomBusinessHour Offset...", cbhOffset) Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset)ExampleFollowing is the code −import pandas as pd # Set the timestamp object in Pandas timestamp = pd.Timestamp('2021-12-31 08:35:10') # Display the Timestamp ... Read More
To get the weekmask applied on the CustomBusinessDay offset, use the CustomBusinessDay.weekmask property in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-10-22 03:10:35') Create the CustomBusinessDay Offset. CustomBusinessDay is the DateOffset subclass representing custom business days excluding holidays. Weekmask of valid business days −cbdOffset = pd.tseries.offsets.CustomBusinessDay(n = 4, weekmask = 'Mon Tue Wed Fri')Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbdOffset) Display the weekmask −print("The weekmask on the CustomBusinessDay object..", cbdOffset.weekmask)ExampleFollowing is the code −import pandas as pd # Set the ... Read More
To return the count of increments applied on the CustomBusinessDay offset, use the CustomBusinessDay.n property in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-10-22 03:10:35') Create the CustomBusinessDay Offset −cbdOffset = pd.tseries.offsets.CustomBusinessDay(n = 4, weekmask = 'Mon Tue Wed Fri')Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbdOffset) Return the count of increments on the given CustomBusinessDay object −print("The count of increments on the CustomBusinessDay object..", cbdOffset.n)ExampleFollowing is the code −import pandas as pd # Set the timestamp object in Pandas timestamp ... Read More