Introduction to Python for Data Science

Course Description

Welcome to Introduction to Python for Data Science! This short course provides a gentle, hands-on introduction to the Python programming language for data science applications. You will learn the fundamentals of Python as a language and how to work with data using the pandas library.

Objectives

The following are the primary learning objectives of students:

1. Develop comprehensive skills in the importing/exporting, wrangling, aggregating and joining of data using Python.

2. Establish a mental model of the Python programming language to enable future self-learning.

3. Build awareness and basic skills in the core data science area of data visualization.

Agenda

Due to the Coronavirus pandemic, this workshop offering will be 100% virtual and span 4 half-days.

Day	Topic	Time
Day 1	Introductions	12:30 - 12:45
	Python and Jupyter Overview	12:45 - 1:15
	Fundamentals	1:15 - 2:00
	Break	2:00 - 2:15
	Packages, Modules, Methods, Functions	2:15 - 3:00
	Importing Data	3:00 - 3:45
	Q&A	3:45 - 4:15
Day 2	Q&A	12:45 - 1:15
	Selecting and Filtering Data	1:15 - 2:00
	Working with Columns	2:00 - 2:45
	Break	2:45 - 3:00
	Case Study, pt. 1	3:00 - 3:45
	Q&A	3:45 - 4:15
Day 3	Q&A	12:45 - 1:15
	Review	1:15 - 1:30
	Summarizing Data	1:30 - 2:15
	Break	2:15 - 2:30
	Summarizing Grouped Data	2:30 - 3:00
	Joining Data	3:00 - 3:45
	Q&A	3:45 - 4:15
Day 4	Q&A	12:45 - 1:15
	Exporting Data	1:15 - 1:45
	Visualizing Data	1:45 - 2:45
	Break	2:45 - 3:00
	Case Study, pt. 2	3:00 - 3:45
	Q&A	3:45 - 4:15

Course Preparation

In an effort to simplify the setup for this class, we are using Binder for all materials (slides, worksheets, etc.). In result, there is no pre-requisite installation required for the in-class material.

With that being said, it's smart to install the appropriate technologies and download the materials anyways. This will provide you a backup in case there are network issues, and it will also be required to apply your learnings outside of class.

Follow these steps to download the technologies and materials:

1. Python, Jupyter and package installation.

These easiest way to install Python, Jupyter, and the necessary packages is through Anaconda. To download and install Anaconda:

1. Visit the Anaconda Individual Edition page
2. Scroll down to the "Anaconda Installers" section.
3. Choose to download the Graphical Installer for your operating system. (If you are comfortable with the command line, you may choose that option instead.)
4. Open the installer when the download completes, and then follow the prompts. If you are prompted about installing PyCharm, elect not to do so.
5. Once installed, open the Anaconda Navigator and launch a Jupyter Notebook to ensure it works.
6. Follow the package installation instructions to ensure pandas and seaborn packages are installed.

2. Download class materials

There are two ways to download the class materials:

1. Clone it - If you're familiar with how to do so, you can clone this repository.
2. Download the files as a zip - use this link

Questions

If you have any specific questions prior to the class you can reach out to us directly via GitHub or email:

• Ethan Swan: GitHub & Email
• Bradley Boehmke: GitHub & Email
• Gus Powers: GitHub & Email
• Jay Cunningham: GitHub & Email