What is stack in data structure using c

what is stack in data structure using c

Data Structure Tutorial

Mar 10,  · Stack is a linear data structure which follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). Mainly the following three basic operations are performed in the stack: Push: Adds an item in the stack. If the stack is full, then it is said to be an Overflow condition. What identifies the data structure as a stack, in either case, is not the implementation but the interface: the user is only allowed to pop or push items onto the array or linked list, with few other helper operations. The following will demonstrate both implementations, using pseudocode.

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Question 1. Following whaf C like pseudo code of a function that takes a number as an argument, and uses structurr stack S to do processing. Prints binary representation of n in reverse order. Question 1 Explanation:. Question 2. Which one of the following is an application of Stack Data Structure? Question 2 Explanation:. Question 3. Which of the following is true about linked list implementation of stack? In push operation, if new nodes are inserted at the beginning of linked list, then in pop operation, nodes must be removed from end.

In push operation, if new nodes are inserted at the end, daa in pop operation, nodes stfucture be removed from the beginning. Question 3 Explanation:. To keep the L ast I n F irst O ut order, a stack can be implemented using linked list in two ways: a In push operation, if new nodes are inserted at the beginning of linked list, then in pop operation, nodes must be removed from beginning. Question i. Question 4 Explanation:. Since the stack data structure follows LIFO order. When we pop items from stack, they are popped in reverse order of their insertion or push.

Question 5. Question 5 Explanation:. At the end of while loop, we must check whether the stack is empty or not. For inputthe stack doesn't remain empty after the loop. Question 6. Question 6 Explanation:. The algorithm for evaluating any postfix expression is fairly straightforward: 1.

While there are input tokens left o Read the next sttucture what is stack in data structure using c input.

If there is only one value in the how to keep rabbits warm o That value is the result of the calculation. If there are more values in the stack o Error The user input has too many values. First three tokens are values, so they are what channel is the eagles vs jaguars game pushed. Question 7.

Starting with the empty stack, suppose we push the first n natural numbers in sequence, and then perform n pop operations. Assume that Push and Pop operation take X seconds each, and Y seconds elapse between the end of one such stack operation and the start of the next operation.

The average stack-life of an element of this stack is. Question 7 Explanation:. Question 8. A single array A[ The two stacks grow from opposite ends of the array. Variables top1 and top2 topl A. Question 8 Explanation:. Both stacks will grow from both ends and if any of the stack top reaches near to the other top then stacks are full.

Question 9 Explanation:. Question To evaluate an expression without any embedded function calls:. As many stacks as the height of the expression tree are needed. Question 10 Structurf. Any expression can be converted into Postfix or Prefix form.

Prefix and postfix evaluation can be done using a single stack. PUSH 10 in the stack. PUSH 2 in whay stack. PUSH 8 in the stack. PUSH 3 in the stack. When operator '-' occurs, POP 26 and 3 from the stack. So, 23 is the answer obtained using single what time zone is valparaiso in. Thus, option A is correct.

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Stack operations may involve initializing the stack, using it and then de-initializing it. Apart from these basic stuffs, a stack is used for the following two primary operations ?. push() ? Pushing (storing) an element on the stack. pop() ? Removing (accessing) an element from the stack. When data is PUSHed onto stack. I plan to build a (linear) regression model which predicts a variable (eg y) using a set of input features (e.g. x1, x2, x3) and also use lagged input features (eg x1 at t-1 and t-2, etc). So I try to just prepare the input data in a way which can then be used by different prediction models – . This section contains the data structure tutorial with the most common and most popular topics like Linked List, Stack, Queue, Tree, Graph etc.. Data structure is logical or mathematical organization of data; it describes how to store the data and access data from lovetiktokhere.comly in our programming data stored in main memory(RAM) and To develop efficient software or firmware we need to care.

Join Stack Overflow to learn, share knowledge, and build your career. Connect and share knowledge within a single location that is structured and easy to search. Is there an efficient way to create a series. How can this be done in an efficient way for dataframes with a lot of timeseries which are very long? One solution is to concat shifted Series together to make a DataFrame:. I like to put the lag numbers in the columns by making the columns a MultiIndex. This way, the names of the columns are retained.

Result: a MultiIndex DataFrame with two column labels: the original one "population" and a new one "lag" :. Solution : Like in the accepted solution, we use DataFrame. I wish there were an easy way to append a list of labels to the existing columns. Here's my solution. Assuming you are focusing on a single column in your data frame, saved into s.

This shortcode will generate instances of the column with 7 lags. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. How to create a lagged data structure using pandas dataframe Ask Question. Asked 7 years, 4 months ago. Active 10 months ago. Viewed 50k times. Improve this question. JJJ 6 6 gold badges 16 16 silver badges 28 28 bronze badges. Mannaggia Mannaggia 3, 9 9 gold badges 31 31 silver badges 45 45 bronze badges.

Why would you want this? I plan to build a linear regression model which predicts a variable eg y using a set of input features e. So I try to just prepare the input data in a way which can then be used by different prediction models — Mannaggia Dec 5 '13 at In this case, you would need to order by the continuous descriptive feature and look at where the target feature column changes values, and computer the average of the continuous descriptive feature values between the previous row requiring lag and the current row at that point to determine the thresholds for how to split the dataset on that descriptive feature.

Add a comment. Active Oldest Votes. One solution is to concat shifted Series together to make a DataFrame: In [11]: pd. Improve this answer. Andy Hayden Andy Hayden k 79 79 gold badges silver badges bronze badges.

Do you know how to do this with DataFrames? There is a problem in renaming the columns "Reindexing only valid with uniquely valued Index objects" — Mannaggia Dec 6 '13 at Mannaggia It sounds like you are looking for a Panel I think you should ask this a separate question.

However, I think actually asking about the function you're applying later in another question might avoid the XY problem. Soufiane Chami 2, 16 16 silver badges 31 31 bronze badges. For a dataframe df with the lag to be applied on 'col name', you can use the shift function. Ashutosh Tripathi Ashutosh Tripathi 61 1 1 silver badge 5 5 bronze badges. If you had column names suffixed too e. I would know how to do that. Ask a question, send me a link and I will post the answer.

DataFrame s , [0, 1, 2] Result: a MultiIndex DataFrame with two column labels: the original one "population" and a new one "lag" : Solution : Like in the accepted solution, we use DataFrame. DataFrame s , [0, 1, 2] :. Charlie Brummitt Charlie Brummitt 4 4 silver badges 11 11 bronze badges. Parsi c. Parsi 2 2 gold badges 8 8 silver badges 24 24 bronze badges. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name.

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