Summer and Fall Coding Lab

This website (harris-coding-lab.github.io) contains the content for the Harris School's Summer and Fall Coding Labs. The workshop aims to introduce R programming concepts with a focus on preparing and analyzing data, and conducting statistical simulations. We will cover how to read data into R, manipulate data with a suite of tools from the tidyverse package dplyr. We will also discuss some basic programming concepts including data types, operators, control flow with if statements and for loops, and how to write your own functions.

Prerequisites

We ask that Coding Lab attendees have the latest stable versions of R and RStudio pre-installed on their local machine. If you need help getting set up, Harris IT is hosting office hours during on Sept 1 and 2 (you should have an email with the details.) and you can email the amazing staff of Harris IT at [email protected].

Fall Lab Materials: Accelerated pace

Accelerated coding lab meets twice in the quarter. You will either attend week 1 and week 3 or week 2 and week 4.

Class	Videos	Slides & Code	Problem sets	Additional Resources
Accelerated Class 1: Functions	video	slides slide code	- basics review - acc. lab 1 - acc. lab 1 solved
Accelerated Class 2: Iteration	video	slides slide code	- basics review - acc lab 2

Fall Lab Materials: Regular pace

Recap slides for all of our meetings here.

Class	Videos	Slides & Code	Problem sets	Additional Resources
Class 1: Why R? & Vectors and Data Types	video part 1: why R? video part 2: a quick introduction to R, Rstudio and tidyverse video: vectors	-slides: video part 1 and 2 - slides code: video part 1 and 2 - slides: vectors - slides: vectors slide code	- intro to r (dataquest) - basics review -read me for labs - lab 1 - lab 1 solved
Class 2: Reading data files and manipulating data with dplyr	video 1: reading data video 2: manipulating data with dplyr video 3: grouped analysis	- slides: reading data - slide code: reading data - slides: manipulating data with dplyr - slide code: manipulating data with dplyr - slides: grouped analysis -slide code: grouped analysis	- basics review (dataquest) - lab 2 - lab 2 solved	FED data from slides (you can download to follow along) texas data from slides drug cartel data from slide (you'll need to download the dta from Dataverse)
Class 3: If Statements	video	slides slide code	- basic review - lab 3 - lab 3 solved
Class 4: Functions	video	slides slide code	- basics review - lab 4 - lab 4 solved
Class 5: Iteration	video	slides slide code	- basics review - lab 5 - lab 5 solved
Additional material: Visualizing data with ggplot	video	slides slide code	basic review

Final Project (Regular Pace Only)

Your final project is quite simple. You will pick a data set that speaks to you and try to uncover something interesting which you will visualize in a plot. You will also compute some summary statistics that you will show in a summary table. We'll provide feedback on your submission. Click on the link for details.

Summer Lab Materials

Links to materials for each week's workshop will be posted here as provided. For each class, watch the video. Then, go to lab and attempt the lab

Class	Videos	Slides & Code	Problem sets	Additional Resources
Class 0: Why R?	video part 1: why R? (~ 12 min) video part 2: a quick introduction to R, Rstudio and tidyverse (~ 14 min)	slides slide code	lab solutions	load covid_data code
Class 1: Reading data files and manipulating data with dplyr	video 1: reading data (~ 10 min) video 2: manipulating data with dplyr (~ 18 min)	- slides: reading data - slides: manipulating data with dplyr - slide code: reading data - slide code: manipulating data with dplyr	lab 1 solutions	FED data from slides (you can download to follow along) texas data from slides drug cartel data from slide (you'll need to download the dta from Dataverse)
Class 2: Vectors and Data Types	video (~ 22 min)	slides slide code	lab 2 basics review solutions	lab code
Class 3: If Statements	video (~ 20 min)	slides slide code	lab 3 basic review solutions	lab code
Class 4: Grouped analysis with dplyr	video (~13 min)	slides slide code	lab 4 basic review solutions	lab code
Class 5: Visualizing data with ggplot	video (~ 18 min)	slides slide code to come	Work on final project with TA and peer support basic review

The first three weeks of fall coding lab covers the same material (minus ggplot). Week 4 and 5 cover new material on for loops and functions. Accelerated fall coding lab consists solely of new material on for loops and functions.

Questions

Post questions on Piazza

Additional Resources

• tidyverse cheetsheets start with dplyr and ggplot
• R for Data Science: free online book with clear explanations of many tidyverse functions, the book to read on data analysis with R
• DataQuest.io: online modules about specific programming concepts, access provided by Harris. For students who would like additional guided practice we recommend:
  • Vectors
    • introduction to programming in r
    • working with vectors
    • vectorized functions
  • Data frames
    • working with data frames
    • dplyr to investigate frequency distributions of data
  • Control flow and if statements
    • control flow
  • Functions
    • writing custom functions
    • working with functionals (includes discussion of map)
  • Extensions
    • random sampling with sample()
    • basic string manipulation
    • gather() and correlations
      • "step 2" is all about ggplot and potentially useful.
  • They're always adding content, so we probably missed some good ones.

Instructors

The instructors for this course are (see Canvas for emails):

• Ari Anisfeld
• Terence Chau

Teaching Assistants

The teaching assistants for this course are:

• Michael Gorman
• Nguyen Luong
• Alysha Rashid
• Milan Rivas
• Paola Riveros
• Dominic Teo
• Ryan Webb
• Fanmei Xia