Instructor Notes

General Notes

It’s all right not to get through the whole lesson.
This lesson is designed for people who have never programmed before, but any given class may include people with a wide range of prior experience. We have therefore included enough material to fill a full day if need be, but expect that many offerings will only get as far as the introduction to Pandas.
Don’t tell people to Google things.
One of the goals of this lesson is to help novices build a workable mental model of how programming works. Until they have that model, they will not know what to search for or how to recognize a helpful answer. Telling them to Google can also give the impression that we think their problem is trivial. (That said, if learners have done enough programming before to be past these issues, having them search for solutions online can help them solidify their understanding.) It’s also worth quoting Trevor King’s comment about online search: “If you find anything, other folks were confused enough to bother with a blog or Stack Overflow post, so it’s probably not trivial.”

Running and Quitting

Variables and Assignment

Data Types and Type Conversion

Built-in Functions and Help

Morning Coffee


Reading Tabular Data into DataFrames

Pandas DataFrames

Instructor Note

Learners often struggle here, many may not work with financial data and concepts so they find the example concepts difficult to get their head around. The biggest problem though is the line generating the wealth_score, this step needs to be talked through throughly: * It uses implicit conversion between boolean and float values which has not been covered in the course so far. * The axis=1 argument needs to be explained clearly.




For Loops


Looping Over Data Sets

Afternoon Coffee

Writing Functions

Variable Scope

Programming Style