After showing the key similarities and differences between the two languages, I’ll show how to set up a learning environment for Python and JS. The bulk of the chapter will then deal with core syntactical and conceptual differences, followed by a selection of patterns and idioms that I use often while doing data visualization work.
These are the chief similarities:
They both work without needing a compilation step (i.e., they are interpreted).
You can use both with an interactive interpreter, which means you can type in lines of code and see the results right away.
Both have garbage collection.
Neither language has header files, package boilerplate, and so on.
Both are primarily developed with a text ...