x1Instructors: John Fay2TA's Edgar Virguez and Jun Shepard3Sept 6,GH 1104
Here, we introduce the Python and R scripting environments in the context of analyzing the same water flow data we did in the Unit 1. In doing so, we touch on the following concepts:
Basics of coding (variables, syntax, data types, packages, etc.)
Basics of data in a coding environment (import/export, data types, & data structures)
Data operations: subset, field calculations, summarizing, transforming, statistical analysis, and plotting.
| Time | Topic |
|---|---|
| 3:00 | Welcome and Intro |
| 3:10 | PYTHON Set up: Duke containers, Jupyter notebooks, Cloning data (NB-0) |
| 3:25 | NB-1: Quick start |
| 3:30 | NB-2a: "Python in 5 minutes" |
| 3:45 | NB-2b: DataFrames in Pandas |
| 3:55 | NB-3: Importing water flow data |
| 4:10 | NB-4: Exploring and plotting water flow data |
| 4:25 | NB-5: Flood frequency analysis |
| 4:40 | Python Recap |
| 4:45 | Break |
| 5:00 | R - Set up: R-Studio overview, Install libraries, Get code |
| 5:10 | Exploratory data analysis in R: LoadStreamflowDescription.R |
| 5:30 | Trend analysis and Leaflet: MannKendall_Description.R |
| 5:55 | Wrap-up |