Programming Articles - Page 939 of 3363

A 2-3 Tree is a type of tree in data structures in which every node of the tree is either a 2 nodeor 3 nodes. It is a special type of B-Tree with order 3.A 2 node in the tree is one which has one data part and two child nodes.A 3 node in the tree is one which has two data parts and three child nodes.Fig:- A 2-3 treeProperties of a 2-3 Tree:-Every internal node is either a 2 node or a 3 node.A node containing one data part can be a 2 node with exactly 2 children or ... Read More

We are given an array Arr[] containing integer values. The goal is to find the maximum number of subarrays with XOR as 0. The bits of any subarray can be swapped any number of times.Note:- 1

We are given an array Arr[] containing integers and 2D array Q containing queries. Each query contains 3 values that are lpos, rpos and K. One can move from index i to next index i+1 in a single step or remain in that index. One can move from lpos to rpos in a maximum of K steps only. Add all numbers at each step including the leftmost number. The goal is to maximize the sum in maximum K moves. If no movement is possible from lpos to rpos in K steps then print “No”. Let us understand more.Let us see ... Read More

We are given a cube which can be formed using a 3-D array as cube[length][breadth][height]. The task is to calculate the minimum sum path which will be achieved by traversing the cube and hence print the result.Let us see various input output scenarios for this -In − int cube[length][breadth][height] = { { {2, 4, 1}, {3, 4, 5}, {9, 8, 7}}, { {5, 3, 2}, {7, 6, 5}, {8, 7, 6}}, { {3, 2, 1}, {4, 3, 2}, {5, 4, 3}}}Out  − Minimum Sum Path In 3-D Array are: 15Explanation − we are given a cube having length, breadth and height. Now, we ... Read More

We are given integer values as a_num that will store the numerator and p_den that will store the denominator which should be a prime number. The task is to check whether the operations performed on a_num after dividing with p_den proves the midy’s theorem or not.Steps to prove Midy’s theorem are-Input numerator as a_num and denominator as p_den which should always be a prime value.Divide the numbers. Check for the repeating decimal values.Store the decimal values until they are not repeating.Check whether the digits are even, if yes, then break them into halvesAdd both the numbers. If the output is ... Read More

We are given with an array of integer elements of any given size. The task is to find the maximum sum which will be calculated by forming the subarrays from the given array within the given range which can be started from any possible index value in an array.Let us see various input output scenarios for this -In − int arr[] = { 3, 2, -1, 6, 7, 2 }, int first = 0, int last = 5Out − Maximum Subarray Sum in a given Range is: 19Explanation − we are given with an array containing both positive and negative values and a ... Read More

To check if the given timestamp is on offset or not, use the CustomBusinessHour.is_on_offset() in Pandas. Pass the timestamp as an argument to check.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-11-14 05:20:30') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass −cbhOffset = pd.tseries.offsets.CustomBusinessHour(start="09:30", end = "18:30")Add the offset to the Timestamp and display the Updated Timestampprint("Updated Timestamp...", timestamp + cbhOffset) Check if the given timestamp is on offset or not −offset = cbhOffset.is_on_offset(pd.Timestamp('2021-11-20 05:20:30'))Display the result −print("Check if the given timestamp is on offset or not...", offset) ExampleFollowing is ... Read More

To check if the given CustomBusinessHour is Anchored, use the CustomBusinessHour.is_anchored() method in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-11-14 05:20:30') Create the CustomBusinessHour Offset. CustomBusinessHour is the DateOffset subclass −cbhOffset = pd.tseries.offsets.CustomBusinessHour(start="09:30", end = "18:30")Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Check whether the CustomBusinessHour is anchored −print("Check whether the CustomBusinessHour is anchored...", cbhOffset.is_anchored())ExampleFollowing is the code −import pandas as pd # Set the timestamp object in Pandas timestamp = pd.Timestamp('2021-11-14 05:20:30') # Display the Timestamp print("Timestamp...", ... Read More

To display the end time of the custom business hour in 24h format from the CustomBusinessHour offset object, use the CustomBusinessHour.end property in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-11-14 05:20:30') Create the CustomBusinessHour Offset. Here, "start" is the start time of your custom business hour in 24h format. The "end" is the end time of your custom business hour in 24h format −cbhOffset = pd.tseries.offsets.CustomBusinessHour(start="09:30", end = "18:30", n = 5)Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Display the ... Read More

To display the start time of the custom business hour in 24h format from the CustomBusinessHour offset object, use the CustomBusinessHour.start property in Pandas.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandas −timestamp = pd.Timestamp('2021-11-14 05:20:30') Create the CustomBusinessHour Offset. Here, "start" is the start time of your custom business hour in 24h format. The "end" is the end time of your custom business hour in 24h format −cbhOffset = pd.tseries.offsets.CustomBusinessHour(start="09:30", end = "18:00", n = 8)Add the offset to the Timestamp and display the Updated Timestamp −print("Updated Timestamp...", timestamp + cbhOffset) Display the ... Read More