6) Tables and Tidyverse-2

📖 Lecture

This week we continue with another fundamental tidyverse package "dplyr". Simply put, dplyr comes with functions that allow you to manipulate data-tables (e.g. data-frames, and other 2-dimensional objects) using a modern and syntactic way.

📚 Reading

Read chapters 5 to 10 of “R Tidy Hurricanes”:

🔬 Lab

You will get to practice common manipulation operations of data-tables using a modern and syntactic way following the data plying framework provided by the R package dplyr.

Time permitting, we’ll also review various aspects that have to do with reading in (i.e. importing) tables in R.

🎯 Objectives

Perform basic manipulations on data tables with “dplyr” functions:

Select rows with slice(), and filter()
Select columns with select()
Transform columns with mutate()
Arrange rows with arrange()
Group data with group_by()
Summarize data with summarize()

🔆 Shiny Friday

The shiny app for this week uses the mtcars data set to visualize the top-n cars given a selected variable.

mtcars-topn-barchart: produces a simple barchart—via "ggplot2"—to visualize the top-n cars given a selected variable. In addition to the plot, it also displays a table with the top-n cars. More important, this app uses a so-called reactive conductor element.
https://github.com/data133/shiny/tree/main/mtcars-topn-barchart

🔔 Assignments

HW4 due this 10/04
HW5 released on 10/05, due 10/11