Python is a seriously powerful library widely used for data analysis. In this course, we'll dig into the Pandas and NumPy libraries that can be used to speed up the process of analyzing large data sets. We will also look at creating different charts using MatPlotLib.
The goal of the course is to take large data sets and draw conclusions based on the features found in Python and its affiliated libraries.
Building on the Python basics, we'll set up an environment for Python development, and use it to analyze data sets large and small. This course will include a variety of hands-on activities. Students can expect to leave this course with a greater understanding of data analysis and data frameworks, so they can immediately put their new skills to work.
Learners must have attended the "Python Workshop: Introduction and Beyond" class, OR have equivalent knowledge/experience.
Topics covered include:
- Python Refresh: A quick overview of lists and dictionaries in Python
- Setting up your dev environment: How to install frameworks and configure your IDE for Python development
- Data types and how to parse them: Working with JSON, Excel, and other data formats
- Intro to Pandas: Understanding the benefits of working with the Pandas frameworks
- Pandas Syntax: Understanding the Pandas types
- Intro to NumPy: Using NumPy for data analysis
- Intro to MatPlotLib: Overview of different chart types available
University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.