How does grouping compared to sorting

Shortest Routes I 2. Shortest Routes Ii 2. Teleporters Path 2. Introductory 2. Apple Division 2. Bit Strings 2. Chessboard And Queens 2. Coin Piles 2. Creating Strings 2. Digit Queries 2. Gray Code 2. Increasing Array 2. Missing Number 2. Number Spiral 2. Palindrome Reorder 2. Permutations 2. Repetitions 2.

Tower Of Hanoi 2. Trailing Zeros 2. Two Knights 2. Two Sets 2. Weird Algorithm 2. Mathematics 2. Another Game 2. Binomial Coefficients 2. Bracket Sequences I 2. Bracket Sequences Ii 2. Candy Lottery 2. Christmas Party 2. Common Divisors 2. Counting Coprime Pairs 2. Counting Divisors 2. Counting Grids 2. Counting Necklaces 2. Creating Strings Ii 2. Dice Probability 2. Distributing Apples 2. Divisor Analysis 2. Exponentiation Ii 2. Exponentiation 2. Fibonacci Numbers 2.

Graph Paths I 2. Graph Paths Ii 2. Grundys Game 2. Inversion Probability 2. Josephus Queries 2. Moving Robots 2. Nim Game I 2. Nim Game Ii 2. Prime Multiples 2. Stair Game 2. Stick Game 2. Sum Of Divisors 2. Throwing Dice 2. Range Queries 2. Distinct Values Queries 2. Dynamic Range Minimum Queries 2. Dynamic Range Sum Queries 2. Forest Queries Ii 2. Forest Queries 2. Hotel Queries 2. Increasing Array Queries 2. List Removals 2. Pizzeria Queries 2. Polynomial Queries 2. Prefix Sum Queries 2.

Range Queries And Copies 2. Range Update Queries 2. Range Updates And Sums 2. Range Xor Queries 2. Salary Queries 2. Static Range Minimum Queries 2. Static Range Sum Queries 2. Subarray Sum Queries 2.

Sorting And Searching 2. Apartments 2. Array Division 2. Collecting Numbers Ii 2. Collecting Numbers 2. Concert Tickets 2. Distinct Numbers 2. Factory Machines 2. Ferris Wheel 2. Josephus Problem I 2. Josephus Problem Ii 2.

Maximum Subarray Sum Ii 2. Maximum Subarray Sum 2. Missing Coin Sum 2. Movie Festival Ii 2. Movie Festival 2. Nearest Smaller Values 2. Nested Ranges Check 2. Nested Ranges Count 2. Playlist 2. Reading Books 2. Restaurant Customers 2. Room Allocation 2. Sliding Cost 2. Sliding Median 2. Stick Lengths 2. Subarray Distinct Values 2. Subarray Divisibility 2. Subarray Sums I 2. Subarray Sums Ii 2. Sum Of Four Values 2.

Sum Of Three Values 2. Sum Of Two Values 2. Tasks And Deadlines 2. Towers 2. Traffic Lights 2. String Algorithms 2. Counting Patterns 2. Distinct Substrings 2. Finding Borders 2. Finding Patterns 2. Finding Periods 2. Longest Palindrome 2. Minimal Rotation 2. Palindrome Queries 2. Pattern Positions 2. Repeating Substring 2. Required Substring 2. String Functions 2. String Matching 2. Substring Distribution 2.

Substring Order I 2. Substring Order Ii 2. Word Combinations 2. Tree Algorithms 2. Company Queries I 2. Company Queries Ii 2. Counting Paths 2. Distance Queries 2. Distinct Colors 2. Finding A Centroid 2. Fixed Length Paths I 2. Fixed Length Paths Ii 2. Path Queries Ii 2. Path Queries 2.

Subordinates 2. Subtree Queries 2. Tree Diameter 2. Tree Distances I 2. Tree Distances Ii 2. Tree Matching 2. Ctci 2. Ctci Cpp 2. Ctci Cpp Arrays 2. Ctci Rust 2. Ctci Rust Arrays 2. Interview Questions 2. Bfs 2. Calculate Best Discount 2. Insert Interval 2. Shortest Path In Binary Matrix 2. Leetcode 2. Explanations 2. Leetcode Rust 2. Binary Tree Inorder Traversal Rs 2. Two Sum Rs 2. Valid Parentheses Rs 3. Artificial Intelligence 4.

The Bitter Lesson 5. Books 6. Atomic Habits 7. Between The World And Me 8. Black Swan 9. Born A Crime Clean Ruby Compiling To Assembly From Scratch Crossing The Chasm Deep Work Educated Grit Inside The Tornado Long Walk To Freedom Mans Search For Meaning Meditations Radical Candor Refactoring Street Fighting Mathematics The Art Of War The Choice The Little Mler The Mythical Man Month The New Economics The Rust Programming Language Zero To One A Tour Of C Algorithms Classes Concepts And Generic Programming Concurrency Containers Essential Operations History And Compatibility Input And Output Library Overview Modularity Numerics Strings And Regular Expressions Templates The Basics User Defined Types Utilities Being Mortal Category Theory For Programmers Adjuctions Algebras For Monads Categories Great And Small Category The Essence Of Composition Comonads Declarative Programming Ends And Coends Enriched Categories F Algebras Free Monoids Freeforgetful Adjunctions Function Types Functoriality Functors Its All About Morphisms Kan Extensions Kleisli Categories Lawvere Theories Limits And Colimits Monads And Effects Monads Categorically Monads Monoids And Categories Monads Programmers Definition Natural Transformations Products And Coproducts Representable Functors Simple Algebraic Data Types The Yoneda Lemma Topoi Types And Functions Yoneda Embedding Clean Code Boundaries Comments Emergence Error Handling Formatting Functions Junit Internals Meaningful Names Objects And Data Structures Refactoring Serialdate Smells And Heuristics About Me.

Contact Us. Privacy policy. Guest Posts. Secure Hash Algorithms. Best Way to Learn Java. How to Start New Blog. Weeks 1 to 13 of the ebook, including the assignments and weekly bulletins, have been written in Finnish and translated into English by Juha Sorva. The appendices glossary , Scala reference , FAQ , etc. The illustrations at the top of each chapter, and the similar drawings elsewhere in the ebook, are the work of Christina Lassheikki.

The Stars project is an adaptation of a programming assignment by Karen Reid. It uses star data from VizieR.

The site will not be available during the break. The break is expected to last for two hours, but site will be available as soon as the upgrade is complete. More information. Skip course navigation Language Change language suomi Course. This course has already ended. CS-A Week 9 Chapter 9. Chapter 9. What Will I Do? Read and program. Rough Estimate of Workload:?

Five hours. Introduction You have already seen many examples of a common need: there is a bunch of numbers, strings, or other objects, and you need to find the one that is the greatest, least, longest, shortest, or otherwise best matches a particular criterion.

We will again visit the Scala API for tools. You know this already: Our intention in O1 is not to wade through the entire Scala API but to highlight some parts of it that are useful for our purpose of learning the basics of programming. The methods max and min Collections have a max method that seeks and returns the largest element. In the case of numerical elements, this means exactly what you think it means: Vector 3, 5, , 20, 1, 5.

Vector "a", "bb", "b", "abc", "ba". Natural ordering Numbers and strings have a so-called natural ordering, which min and max rely on. Pos objects, for instance, do not: Vector Pos 10, 5 , Pos 7, Sorting a collection with sorted The sorted method sorts the elements of a collection — which must be comparable with each other — in ascending order: Vector 3, 5, , 20, 1, 5.

Comparing Elements by Custom Criteria max , min , and sorted work admirably as long as the elements have a natural ordering. Sorting with sortBy The sortBy method is similar. You can sort strings by length, numbers by their second power, and shapes by their area: Vector "a", "bb", "b", "abc", "ba".

Both of the expressions below work: Vector 3, 5, , 20, 1, 5. Notice the following in particular: The methods stars , minCoords , and maxCoords are missing.

We construct a constellation from a vector of pairs. The variables stars has the type Set[Star] : a set of stars. A set is a collection of elements.

Unlike a vector or a buffer, a set can never contain multiple copies of the same element. One way to form a set is to call toSet on an existing collection e. Even if the original collection had multiple copies of the same elements, each element will appear only once in the resulting Set. Add the missing parts: Implement Constellation as specified. Implement placeConstellation on SkyPic. A diagram of the Stars project.

Recommended steps and other hints Implement stars in class Constellation. The given GUI displays those texts whenever the mouse cursor is located in the rectangular area between the minCoords and maxCoords of a constellation.

The program recognizes a handful of constellations, which are defined in the northern folder. Or if you prefer, you can use a version of place that takes in any number of pairs as illustrated here: myBackground. Preparations: pairs in a vector The first thing we need is a way to form key—value pairs that consist of member IDs as keys and Member objects as values. We could have written brackets around this expression, just for clarity. Making a Map from a vector What we have now is a vector of key—value pairs.

We create a map that stores a Vector of members behind each key. Eventually, Excel gets the hint and redocks it. Note that you can dock the PivotTable Fields list on either the right side or the left side of the screen. As shown in Figure , a small gear-wheel icon appears near the top of the PivotTable Fields list. Select this drop-down menu to see its five possible arrangements. Although the default is to have the Fields section at the top of the list and the Areas section at the bottom of the list, four other arrangements are possible.

Other options let you control whether the fields in the list appear alphabetically or in the same sequence that they appeared in the original data set. The final three arrangements offered in the drop-down menu are rather confusing.

If someone changes the PivotTable Fields list to show only the Areas section, you cannot see new fields to add to the pivot table. If you ever encounter a version of the PivotTable Fields list with only the Areas section see Figure or only the Fields section, remember that you can return to a less-confusing view of the data by using the arrangement drop-down menu.

As shown in Figure , every field in the Areas section has a visible drop-down arrow. When you select this drop-down arrow, you see four categories of choices:. The first four choices enable you to rearrange the field within the list of fields in that area of the pivot table. You can accomplish this by dragging the field up or down in the area.