Working with multiple data frames

Day 4

Dr. Elijah Meyer

Duke University
STA 199 - Summer 2023

May 23rd, 2023

Checklist

– Clone ae-04

– Make sure you are keeping up with Preparation Videos

– Lab-1 due Thursday (25th before class)

– HW-1 due Monday (29th at 11:59 PM)

– All AEs for this week due Friday (26th at 11:59 PM)

Announcements

Videos

– Requesting videos for missed classes

Homework + Labs

– Late work policy

– Drop 1

Announcements

Exam

– June 1st

– Take home

– Open Notes / Internet / etc

Exam

– Coding + Short answer questions

– Extension questions

– Can NOT be late

– Pull -> Commit -> Push after every question

Questions on Content for Class

– Posted in Slack #class-questions

– Reply under the comment

– Will guide warm up questions for Thursday

Warm up

Please define the following…

– select()

– slice()

– arrange()

Warm up (2)

We glossed over this on Monday…. it needs more attention!

We can string multiple pipes together. That’s the purpose of tidyverse!

flights |> 
  select(tailnum, carrier, dep_delay) |>
  arrange(desc(dep_delay)) |>
  slice(1) 

Render Discussion

Why can’t I Render?

– Error in your code?

– Duplicate code chunk label?

– Are you using a function that brings up an external panel such as View()?

GitHub Discussion

Why are my changes not showing up in GitHub?

– Are you in the right project?

You can see the project you are working in in the top right corner of your screen. This MUST be the project that you cloned for the exam / assignment / lab. Do not use the files tab to go search for a file outside of your project repo.

Tibble vs Data Frame in R

In the console, type mtcars in the data set

Now, type as_tibble(mtcars)

TIbble vs Data Frame in R

– A tibble is often considered a neater format of a data frame

– Tibble has a more advanced print function

– Tidyverse functions are built to work with tibbles

https://stackoverflow.com/questions/64856424/what-are-the-differences-between-data-frame-tibble-and-matrix

Function of the day

fct_reorder

Function of the day

iris |>
  ggplot(
  aes(x = fct_reorder(Species, Sepal.Width), y = Sepal.Width)
) + 
  geom_boxplot()
  

Goals

– Play with dplyr functions

– Understand join functions

– Join multiple data frames

ae-04

Motivation

Messy data

– The sheer volume of information is sometimes referred to as “messy” data, because it’s hard to make sense of it all.

Messy data

How?

Joining datasets

Data merging is the process of combining two or more data sets into a single data set. Most often, this process is necessary when you have raw data stored in multiple files, worksheets, or data tables, that you want to analyze together.

Joining datasets

– Left Join

– Inner Join

– Right Join

– Full Join

Joining datasets

AE-04

– ae-04 part 2!

– Joining Fisheries

Recap of AE

– This is important! Data are messy!

– Think carefully about the join you use