6) Tables and Tidyverse-2

๐Ÿ“– 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.

๐Ÿ“š Reading

Read chapters 5 to 10 of โ€œR Tidy Hurricanesโ€:

๐Ÿ”ฌ 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.

Also, we are going to review various aspects that have to do with reading in (i.e. importing) tables in R.

๐ŸŽฏ Objectives

Perform basic manipulations on data tables with โ€œdplyrโ€ 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()

๐Ÿ”† 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 barchartโ€”via "ggplot2"โ€”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

๐Ÿ”” Assignments

  • HW4 due this 02/23
  • HW5 released on 02/24, due 03/01