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Coding for Planners: Up and Running with Python
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Coding for Planners: Up and Running with Python

Coding for Planners: Up and Running with Python

72 min
Credit: AICP CM

This course is approved for 1.25 AICP CM credit.

In this course we will learn how to get Python up and running on your computer. Python is one of the world’s most popular programming languages, particularly among beginners, thanks to its clear and straightforward syntax. It is also one of the most widely used languages for data science. After we install Python, we will learn how to work with third-party packages and then run through the basics of the language.

In This Course

  1. The instructor introduces the course.
  2. Installing Python
    This chapter demonstrates how to download and install Python on your computer using the Anaconda installer.
  3. Installing Third-Party Packages
    This chapter introduces the idea of Python packages—small libraries of code developed by third parties so you don’t have to reinvent the wheel with every task. We survey a couple of useful packages as examples. Then we demonstrate how to configure Anaconda’s conda package manager to download and install any package we want.
  4. Launching a Python Notebook
    This chapter demonstrates how to launch a Python programming environment—specifically, an interactive Jupyter notebook.
  5. Python Language Basics, Part 1
    This chapter introduces some of the basic syntax, conventions, and capabilities of the Python programming language. We use an interactive Jupyter notebook to work with simple Python code and demonstrate data types
  6. Python Language Basics, Part 2
    This chapter discusses some of the basic syntax, conventions, and capabilities of the Python programming language. We use an interactive Jupyter notebook to work with simple Python code and demonstrate data types
  7. Python Control Flow, Part 1
    This chapter introduces the computer science concept of control flow: the order in which code statements are executed. This is a fundamental idea underlying all programming. In particular, it focuses on if-then-else statements. These conditional statements allow the code to do different things based on the input value.
  8. Python Control Flow, Part 2
    This chapter continues the introduction of the computer science concept of control flow, focusing this time on loops—that is, having the code do some process repeatedly over a set of input values.
  9. Python Functions
    This chapter introduces the computer science concept of a function. Functions let us encapsulate useful bits of code to reuse repeatedly throughout our script. We show how functions, loops, and conditional statements can all work together.
  10. Closing Thoughts
    This chapter presents an overview of everything we’ve covered in this session. It briefly recaps the material and discusses further resources and next steps. In subsequent courses we’ll explore using Python to load data files, conduct simple analyses and visualizations, perform basic GIS queries, and conduct street network analyses.