Data Analysis in Python with pandas & matplotlib in Spyder

Code and run your first Python script in minutes without installing anything! This course is designed for learners with no coding experience, providing a crash course in Python, which enables the learners to delve into core data analysis topics that can be transferred to other languages. In this course, you will learn how to import and organize your data, use functions to gather descriptive statistics, and perform statistical tests. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours. Finally, a longer-form lab at the end of the course will provide you an opportunity to apply all learned concepts within a real-world context.

• Describing a Numerical Data Set
• Welcome to Week 1 of the Python Data Science with Jupyter course. These assignments cover introductory topics such as Printing and Sorting, Data Types, and Statistical Functions.
• Importing and Describing Mixed Data Sets (pandas)
• Statistical Tests to Determine if Populations are Different
• Statistical Tests to Describe Relationships
• Python Data Analysis Lab