Data types and classes

Lecture 8

Dr. Benjamin Soltoff

Cornell University
INFO 5001 - Fall 2023

2023-09-18

Announcements

Announcements

• Lab 02 due today
• Homework 02 due Wednesday
• No class Wednesday

Types and classes

Types and classes

• Type is how an object is stored in memory, e.g.,

  • double: a real number stored in double-precision floating point format.
  • integer: an integer (positive or negative)

• Class is metadata about the object that can determine how common functions operate on that object, e.g.,

  • factor
  • date
  • date-time

Types of vectors

You’ll commonly encounter:

• logical
• integer
• double
• character

You’ll less commonly encounter:

• list
• NULL
• complex
• raw

We don’t typically think of them as lists, but data frames are lists where every element is a vector and they are all the same length.

Coercing vectors into different types

Base R functions

• as.logical()
• as.integer()
• as.double()
• as.character()

readr functions

• parse_logical()
• parse_integer()
• parse_double()
• parse_character()

Coercing vectors into different types

x <- c("3", "5", "alpha")

as.double(x)

Warning: NAs introduced by coercion

[1]  3  5 NA

parse_double(x)

Warning: 1 parsing failure.
row col expected actual
  3  -- a double  alpha

[1]  3  5 NA
attr(,"problems")
# A tibble: 1 × 4
    row   col expected actual
  <int> <int> <chr>    <chr> 
1     3    NA a double alpha 

y <- c("$23", "$17.67", "$123,000")

as.numeric(y)

[1] NA NA NA

parse_number(y)

[1]     23.00     17.67 123000.00

Types of functions

Functions have types too, but you don’t need to worry about the differences in the context of doing data science.

typeof(mean) # regular function

[1] "closure"

typeof(`$`) # internal function

[1] "special"

typeof(sum) # primitive function

[1] "builtin"

Factors

A factor is a vector that can contain only predefined values. It is used to store categorical data.

x <- factor(c("a", "b", "b", "a"))
x

[1] a b b a
Levels: a b

typeof(x)

[1] "integer"

attributes(x)

$levels
[1] "a" "b"

$class
[1] "factor"

Other classes

Just a couple of examples…

Date:

today <- Sys.Date()
today

[1] "2023-09-18"

typeof(today)

[1] "double"

attributes(today)

$class
[1] "Date"

Date-time:

now <- as.POSIXct("2023-09-18 9:55", tz = "EST")
now

[1] "2023-09-18 09:55:00 EST"

typeof(now)

[1] "double"

attributes(now)

$class
[1] "POSIXct" "POSIXt" 

$tzone
[1] "EST"

Application exercise

ae-06

• Go to the course GitHub org and find your ae-06 (repo name will be suffixed with your GitHub name).
• Clone the repo in RStudio Workbench, open the Quarto document in the repo, and follow along and complete the exercises.
• Render, commit, and push your edits by the AE deadline – end of tomorrow.

Recap of AE

• Vectors have types and classes. In general we don’t need to be too concerned with this distinction, but make sure you use an appropriate type/class for a variable (e.g. don’t store year as a character type)
• forcats is a powerful package for working with factors
• Check out the tidyverse and other packages for working with different classes of vectors
  • lubridate for date and date-time objects
  • forecast and zoo for time-series objects
  • stringr for character strings
  • sf for spatial objects

Ariel the cat