8.14

III From Pyret to Python🔗

    9 From Pyret to Python

      9.1 From Pyret to Python

        9.1.1 Expressions, Functions, and Types

        9.1.2 Returning Values from Functions

        9.1.3 Examples and Test Cases

        9.1.4 An Aside on Numbers

        9.1.5 Conditionals

        9.1.6 Creating and Processing Lists

          9.1.6.1 Filters, Maps, and Friends

        9.1.7 Data with Components

          9.1.7.1 Accessing Fields within Dataclasses

        9.1.8 Traversing Lists

          9.1.8.1 Introducing For Loops

          9.1.8.2 An Aside on Order of Processing List Elements

          9.1.8.3 Using For Loops in Functions that Produce Lists

          9.1.8.4 Summary: The List-Processing Template for Python

      9.2 Dictionaries

        9.2.1 Creating and Using a Dictionary

        9.2.2 Searching Through the Values in a Dictionary

        9.2.3 Dictionaries with More Complex Values

        9.2.4 Dictionaries versus Dataclasses

          Summary

      9.3 Arrays

        9.3.1 Two Memory Layouts for Ordered Items

        9.3.2 Iterating Partly through an Ordered Datum

    10 Tables in Python via Pandas

      10.1 Introduction to Pandas

        10.1.1 Pandas Table Basics

          10.1.1.1 Core Datatypes: DataFrame and Series

          10.1.1.2 Creating and Loading DataFrames

          10.1.1.3 Using Labels and Indices to Access Cells

        10.1.2 Filtering Rows

        10.1.3 Cleaning and Normalizing Data

          10.1.3.1 Clearing out unknown values

          10.1.3.2 Repairing Values and Column Types

        10.1.4 Computing New Columns

        10.1.5 Aggregating and Grouping Columns

        10.1.6 Wide Versus Tall Data

          Converting Between Wide and Tall Data

        10.1.7 Plotting Data

        10.1.8 Takeaways

      10.2 Reshaping Tables

        10.2.1 Binning Rows

        10.2.2 Wide versus Tall Datasets