md -[jupytext 1.1.0]-> ipynb -[jupytext 1.3.0rc1]-> md

Author: rsokl

Python/Module1_GettingStartedWithPython/GettingStartedWithPython.md

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    :description: Topic: Basic description of the Python programming language, Difficulty: Easy, Category: Background
    :keywords: python, install, basics, scripts, interpreter, foundations
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 # Introducing the Python Programming Language
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 Now that you have a Python script, how do you get the computer to read it and follow its instructions? You will need to install a **Python interpreter** on your computer to accomplish this. This is what people mean, whether they know it or not, when they tell you to "install Python" on your computer.
 
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 ## What is a Python Interpreter and What Does it Mean to "Install Python"?
 
 A Python interpreter is any computer program that is capable of doing the following:
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 In practice, you will be able to simply execute `python my_script.py` in any directory, and your computer will know where to look to find the `python` program. This will be set up during the installation process.
 
 It may be confusing to think that the Python language is interpreted by using a program written in another language. How, then, is that language interpreted? The answer, in the case of CPython, is that C code need not be interpreted; programs exist for Windows, Mac, and Linux that can translate C code directly into machine instructions. 
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 ## Why Python?

Python/Module1_GettingStartedWithPython/Getting_Started_With_IDEs_and_Notebooks.md

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    :description: Topic: Integrated Development Environments, Difficulty: Easy, Category: Tools
    :keywords: python, introduction, IDE, PyCharm, VSCode, Jupyter, recommendation, tools
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 # Setting Up a Development Environment
 ## What You Will Learn

Python/Module1_GettingStartedWithPython/Informal_Intro_Python.md

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    :description: Topic: Informal Introduction to Python, Difficulty: Easy, Category: Tutorial
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 # An Informal Introduction to Python
 Now that you have the Anaconda distribution of Python installed on your machine, let's write some simple Python code! We are going to forego writing a full Python script for now, and instead make use of a convenient tool for doing quick code scratchwork. The IPython console was installed as a part of Anaconda; it will allow us to build incrementally off of snippets of code, instead of having to execute an entire script all at once. 

Python/Module1_GettingStartedWithPython/Installing_Python.md

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    :description: Topic: Installing Python with Anaconda, Difficulty: Easy, Category: Tutorial
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 ## Installing Python
 
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 You will need to know how to open a terminal (cmd.exe for Windows users) on your computer, and how to navigate between directories in the terminal. If you do not know how to do this, read a 'how-to' for whatever operating system you are using.
 
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 ### What did this just do to my computer?
 
 This created a directory called `Anaconda3` (or some variant of this) on your computer, which contains all of the files associated with the CPython interpreter, all of the modules in Python's standard library, the aforementioned 3rd party packages that come as part of the Anaconda distribution (e.g. NumPy, SciPy, Jupyter, iPython), and the `conda` package manager. It also contains the executable files for all of these applications. The default install location for Anaconda is:
@@ -101,4 +101,3 @@ And like that, conda environments give you all of the powers of a necromancer, a
 Conda environments have more uses than simply switching back and forth between Python 3 and 2. Many people like to make a new conda environment for every major project that they work on, so that they can freely install any dependencies that are needed for that particular project, without worrying about conflicts with their other work. You should be keen on making regular use of conda environments.
 
 It is highly recommended that you take time to read through [this tutorial on managing conda environments](https://conda.io/docs/user-guide/tasks/manage-environments.html).
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Python/Module1_GettingStartedWithPython/Jupyter_Notebooks.md

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 # Jupyter Notebooks
 In recent years, the Jupyter Notebook has become a massively popular tool for doing research-oriented work in Python and other languages alike. Its emergence marked a paradigm shift in the way data science is conducted. 

Python/Module1_GettingStartedWithPython/Numerical_Work_In_Python.md

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Python/Module1_GettingStartedWithPython/SiteFormatting.md

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    :description: Topic: Overview of formatting in Python Like You Mean It, Difficulty: Easy, Category: Instructions
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 # A Quick Guide to Formatting

Python/Module2_EssentialsOfPython/Basic_Objects.md

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    :description: Topic: Basics of Python Objects, Difficulty: Easy, Category: Section
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 <!-- #region -->
 # Basic Object Types
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 3\. Remove the whitespace from both ends of: `"  basket    "` 
 
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 4\. Create a string that will print as (the second line begins with a tab-character):
 ```
 Hello
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 6\. Only kids 13 and up are allowed to see Wayne's World. Given the variables `name` (a string) and `age` (an integer), use an f-string that will display: "NAME is old enough to watch the movie: BOOL", where NAME is to be replaced with the kid's name, and BOOL should be `True` if the kid is at least 13 years old, and `False` otherwise.
 
 </div>
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 <!-- #region -->
 ## Lists

Python/Module2_EssentialsOfPython/ConditionalStatements.md

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    :description: Topic: Conditional Statements, Difficulty: Easy, Category: Section
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 # Conditional Statements

Python/Module2_EssentialsOfPython/DataStructures.md

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 <!-- #region -->
 # Data Structures (Part I): Introduction