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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

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
 

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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 <!-- #region -->
 # A Quick Guide to Formatting

Python/Module2_EssentialsOfPython/Basic_Objects.md

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 # Basic Object Types

Python/Module2_EssentialsOfPython/ConditionalStatements.md

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 # Conditional Statements

Python/Module2_EssentialsOfPython/DataStructures.md

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

Python/Module2_EssentialsOfPython/DataStructures_III_Sets_and_More.md

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 # Data Structures (Part III): Sets & the Collections Module

Python/Module2_EssentialsOfPython/DataStructures_II_Dictionaries.md

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 #  Data Structures (Part II): Dictionaries
 Python's dictionary allows you to store key-value pairs, and then pass the dictionary a key to quickly retrieve its corresponding value. Specifically, you construct the dictionary by specifying one-way mappings from key-objects to value-objects. **Each key must map to exactly one value**, meaning that a key must be unique. 

Python/Module2_EssentialsOfPython/ForLoops.md

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    :description: Topic: Contorl flow with for-loops and while-loops, Difficulty: Easy, Category: Section
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 # For-Loops and While-Loops
 In this section, we will introduce the essential "for-loop" control flow paradigm along with the formal definition of an "iterable". The utility of these items cannot be understated. Moving forward, you will likely find use for these concepts in nearly every piece of Python code that you write!

Python/Module2_EssentialsOfPython/Functions.md

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 <!-- #region -->
 # Basics of Functions

Python/Module2_EssentialsOfPython/Generators_and_Comprehensions.md

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 # Generators & Comprehension Expressions
 <div class="alert alert-warning">

Python/Module2_EssentialsOfPython/Introduction.md

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 <!-- #region -->
 # Introducing Control Flow

Python/Module2_EssentialsOfPython/Iterables.md

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 # Iterables
 Our encounter with for-loops introduced the term *iterable* - an object that can be "iterated over", such as in a for-loop.