3 Basic Data |
3.1 Getting Started |
3.1.1 Motivating Example: Flags |
3.1.2 Numbers |
3.1.3 Expressions |
3.1.4 Terminology |
3.1.5 Strings |
3.1.6 Images |
3.1.6.1 Combining Images |
3.1.6.2 Making a Flag |
3.1.7 Stepping Back: Types, Errors, and Documentation |
3.1.7.1 Types and Contracts |
3.1.7.2 Format and Notation Errors |
3.1.7.3 Finding Other
Functions: Documentation |
3.2 Naming Values |
3.2.1 The Definitions Pane |
3.2.2 Naming Values |
3.2.2.1 Names Versus Strings |
3.2.2.2 Expressions versus
Statements |
3.2.3 The Program Directory |
3.2.3.1 Understanding the Run Button |
3.2.4 Using Names to Streamline Building Images |
3.3 From Repeated Expressions to Functions |
3.3.1 Example: Similar Flags |
3.3.2 Defining Functions |
3.3.2.1 How Functions Evaluate |
3.3.2.2 Type Annotations |
3.3.2.3 Documentation |
3.3.3 Functions Practice: Moon Weight |
3.3.4 Documenting Functions with Examples |
3.3.5 Functions Practice: Cost of pens |
3.3.6 Recap: Defining Functions |
3.4 Conditionals and Booleans |
3.4.1 Motivating Example: Shipping Costs |
3.4.2 Conditionals: Computations with Decisions |
3.4.3 Booleans |
3.4.3.1 Other Boolean Operations |
3.4.3.2 Combining Booleans |
3.4.4 Asking Multiple Questions |
3.4.5 Evaluating by Reducing Expressions |
3.4.6 Composing Functions |
3.4.6.1 How Function Compositions Evaluate |
3.4.6.2 Function Composition and the Directory |
3.4.7 Nested Conditionals |
3.4.8 Recap: Booleans and Conditionals |
4 Tabular Data |
4.1 Introduction to Tabular Data |
4.1.1 Creating Tabular Data |
4.1.2 Extracting Rows and Cell Values |
4.1.3 Functions over Rows |
4.1.4 Processing Rows |
4.1.4.1 Finding Rows |
4.1.4.2 Ordering Rows |
4.1.4.3 Adding New Columns |
4.1.4.4 Calculating New Column Values |
4.1.5 Examples for Table-Producing Functions |
4.2 Processing Tables |
4.2.1 Cleaning Data Tables |
4.2.1.1 Loading Data Tables |
4.2.1.2 Dealing with Missing Entries |
4.2.1.3 Normalizing Data |
4.2.1.4 Normalization, Systematically |
4.2.1.5 Using Programs to Detect Data Errors |
4.2.2 Task Plans |
4.2.3 Preparing Data Tables |
4.2.3.1 Creating bins |
4.2.3.2 Splitting Columns |
4.2.4 Managing and Naming Data Tables |
4.2.5 Visualizations and Plots |
4.2.6 Summary: Managing a Data Analysis |
5 Lists |
5.1 From Tables to Lists |
5.1.1 Basic Statistical Questions |
5.1.2 Extracting a Column from a Table |
5.1.3 Understanding Lists |
5.1.3.1 Lists as Anonymous Data |
5.1.3.2 Creating Literal Lists |
5.1.4 Operating on Lists |
5.1.4.1 Built-In Operations on Lists of Numbers |
5.1.4.2 Built-In Operations on Lists in General |
5.1.4.3 An Aside on Naming Conventions |
5.1.4.4 Getting Elements By Position |
5.1.4.5 Transforming Lists |
5.1.4.6 Recap: Summary of List Operations |
5.1.5 Lambda: Anonymous Functions |
5.1.6 Combining Lists and Tables |
5.2 Processing Lists |
5.2.1 Making Lists and Taking Them Apart |
5.2.2 Some Example Exercises |
5.2.3 Structural Problems with Scalar Answers |
5.2.3.1 my-len: Examples |
5.2.3.2 my-sum: Examples |
5.2.3.3 From Examples to Code |
5.2.4 Structural Problems that Transform Lists |
5.2.4.1 my-doubles: Examples and Code |
5.2.4.2 my-str-len: Examples and Code |
5.2.5 Structural Problems that Select from Lists |
5.2.5.1 my-pos-nums: Examples and Code |
5.2.5.2 my-alternating:
Examples and Code |
5.2.6 Structural Problems Over Relaxed Domains |
5.2.6.1 my-max: Examples |
5.2.6.2 my-max: From Examples to Code |
5.2.7 More Structural Problems with Scalar Answers |
5.2.7.1 my-avg: Examples |
5.2.8 Structural Problems with Accumulators |
5.2.8.1 my-running-sum: First Attempt |
5.2.8.2 my-running-sum: Examples and Code |
5.2.8.3 my-alternating: Examples and Code |
5.2.9 Dealing with Multiple Answers |
5.2.9.1 uniq: Problem Setup |
5.2.9.2 uniq: Examples |
5.2.9.3 uniq: Code |
5.2.9.4 uniq: Reducing Computation |
5.2.9.5 uniq: Example and Code Variations |
5.2.9.6 uniq: Why Produce a List? |
5.2.10 Monomorphic Lists and Polymorphic Types |
5.3 Recursive Data |
5.3.1 Functions to Process Recursive Data |
5.3.2 A Template for Processing Recursive Data |
5.3.3 The Design Recipe |
6 Structured Data |
6.1 Introduction to Structured Data |
6.1.1 Understanding the Kinds of Compound Data |
6.1.1.1 A First Peek at Structured Data |
6.1.1.2 A First Peek at Conditional Data |
6.1.2 Defining and Creating Structured and Conditional Data |
6.1.2.1 Defining and Creating Structured Data |
6.1.2.2 Annotations for Structured Data |
6.1.2.3 Defining and Creating Conditional Data |
6.1.3 Programming with Structured and Conditional Data |
6.1.3.1 Extracting Fields from Structured Data |
6.1.3.2 Telling Apart Variants of Conditional Data |
6.1.3.3 Processing Fields of Variants |
6.2 Collections of Structured Data |
6.2.1 Lists as Collective Data |
6.2.2 Sets as Collective Data |
6.2.2.1 Picking Elements from Sets |
6.2.2.2 Computing with Sets |
6.2.3 Combining Structured and Collective Data |
6.2.4 Data Design Problem: Representing Quizzes |
7 Trees |
7.1 Trees |
7.1.1 Data Design Problem – Ancestry Data |
7.1.1.1 Computing Genetic Parents from an Ancestry Table |
7.1.1.2 Computing Grandparents from an Ancestry Table |
7.1.1.3 Creating a Datatype for Ancestor Trees |
7.1.2 Programs to Process Ancestor Trees |
7.1.3 Summarizing How to Approach Tree Problems |
7.1.4 Study Questions |
8 Foundations: Bonus Materials |
8.1 Functions as Data |
8.1.1 A Little Calculus |
8.1.2 A Helpful Shorthand for Anonymous Functions |
8.1.3 Streams From Functions |
8.1.4 Combining Forces: Streams of Derivatives |
8.2 Queues from Lists |
8.2.1 Using a Wrapper Datatype |
8.2.2 Combining Answers |
8.2.3 Using a Picker |
8.2.4 Using Tuples |
8.2.5 A Picker Method |
8.3 Examples, Testing, and Program Checking |
8.3.1 From Examples to Tests |
8.3.2 More Refined Comparisons |
8.3.3 When Tests Fail |
8.3.4 Oracles for Testing |