Data Analysis with Python

Instructor: John Kelly

This class meets online

This course is an introduction to data analysis using Python. In this course, the student will learn the steps of data analysis:

• Data loading
• Data cleaning and preparation
• Data wrangling (joining, combining, reshaping)
• Plotting and visualization
• Data storage

The student will learn essential Python tools for data analysis, including:

• essential Python data structures, functions, and files
• numpy - working with arrays
• pandas - working with tabular data in series and data frames
• matplotlib - plotting data
• and more

Prerequisites/Corequisites: None. However, familiarity with Python or another programming language is useful.

The objective of this course is to introduce the student to methods of manipulating, processing, cleaning, and analyzing data in Python. The student will understand how to work with structured data from a variety of sources.

Required Texts and Resources:

Text: Python for Data Analysis, 3rd Ed. by Wes McKinney. Sebastopol, California: O'Reilly Media, 2022. Open Edition of the book is available here.
Student must have a computer (desktop, laptop, Chromebook) with an Internet connection. The student will primarily work in Jupyter Notebooks which can be accessed locally or through a web browser.
Recommended: Anaconda Python distribution and PyCharm IDE installed on a personal computer.

Note: Class time is Pacific time throughout the year