Overview of data structures, iteration, flow control, and program design relevant to data exploration and analysis. When and how to exploit pre-existing libraries.
By the end of the course, students are expected to be able to:
- Write pseudo-code to specify, break down, and solve problems before being translated into code.
- Write modular, easy-to-understand Python and R code that uses flow control, iteration, lists (arrays), and functions–and has appropriate style and organization.
- Design and write Python and R programs to: perform calculations; read and write files; and use classes, objects, methods, and Python and R libraries. Determine which language (Python or R) is more appropriate for a given task.
Sedgewick, Robert; Wayne, Kevin; and Dondero, Robert. Introduction to Programming in Python: An Interdisciplinary Approach. Addison-Wesley, 2015.
- Style guides for R:
- Style guide for Python (pep8):
Note: information on this page is preliminary and subject to change.