Learn Data Exploration with Pandas by Analysing the Post-University Salaries of Graduates by Major

College degrees are very expensive. But, do they pay you back? Choosing Philosophy or International Relations as a major may have worried your parents, but does the data back up their fears? PayScale Inc. did a year-long survey of 1.2 million Americans with only a bachelor's degree. We'll be digging into this data and use Pandas to answer these questions:

• Which degrees have the highest starting salaries? 

• Which majors have the lowest earnings after college?

• Which degrees have the highest earning potential?

• What are the lowest risk college majors from an earnings standpoint?

• Do business, STEM (Science, Technology, Engineering, Mathematics) or HASS (Humanities, Arts, Social Science) degrees earn more on average?

Today you'll learn

• How to explore a Pandas DataFrame

• How to detect NaN (not a number) values and clean your data

• How to select particular columns, rows, and individual cells

• How to sort your data

• How to group data by category

and so much more! Let's get started!