Objects

Nicky Wakim

What are R objects?

  • R objects are stored “things” in R

 

  • R objects can be data, numbers, text, model output, etc.
    • It can be a…
      • single piece of data
        • like the number 5
      • collection of data
        • like a dataset with 100 rows and 10 columns

 

  • R objects are created with assignments that can be used in later commands

How can we create an object?

Here is the generic way we assign something like a value to an object_name:

 

object_name <- value

 

  • Reads as “object name gets value” or “value is assigned to object name”

A note on the assignment operator

  • Can assign a variable using either = or <-
    • Using <- is preferable for certain occasions
    • I usually just use = because less typing hehe

 

x = 5
x
[1] 5
x <- 5
x
[1] 5

Types of objects: single piece of data

Class What is it? Examples
Doubles dbl Numbers -5.3, 14.5, or 2000.0001
Integers int Whole numbers (no decimals), more specific than doubles -5, 14, or 2000
Characters chr These are text or words that are in quotations. Math cannot be done on these. “My example character”
Factor fct Categorical variables stored with levels/groups (good pkg: forcats) "blue", "red", "purple"
Logical lgl Values that take TRUE or FALSE TRUE or FALSE
Date date Character that represents a date (good pkg: lubridate) "12-13-2005"

Types of objects: collection of data

Class Dimension What does it contain?
Vector 1D all the same type* of pieces of data
Matrix 2D all the same type* of pieces of data
Array ND all the same type* of pieces of data
Data frame / table 2D different types of pieces of data
List 1D other types of collections of data

*If you put different types of data in a vector, matrix, or array, they will be coerced into characters

Most datasets are data frames

class(hrs_data)
1
The class() function tells us the class of the object (in this case, hrs_data is a data frame) 
[1] "data.frame"
tibble(hrs_data)
2
I want to take a look at the data, so I use the tibble() function to print it as a tibble 
# A tibble: 2,728 × 32
   hhid  pn    id    birthyr birthmo birthdate proxy coupled sex   age_mo age_yr
   <fct> <fct> <chr>   <dbl>   <dbl>     <dbl> <fct> <fct>   <fct>  <dbl>  <dbl>
 1 5527… 010   5527…    1967       9      2814 Resp… Not a … Fema…    665     55
 2 5553… 020   5553…    1966       7      2387 Resp… Couple… Fema…    676     56
 3 5597… 010   5597…    1967       3      2602 Resp… Couple… Male     663     55
 4 5581… 020   5581…    1973      10      5036 Resp… Couple… Male     600     50
 5 5547… 020   5547…    1950       7     -3153 Resp… Couple… Male     860     71
 6 5510… 010   5510…    1970       1      3667 Resp… Not a … Fema…    632     52
 7 5505… 010   5505…    1960       1        14 Resp… Not a … Male     749     62
 8 5590… 010   5590…    1971       4      4122 Resp… Couple… Male     621     51
 9 5562… 020   5562…    1952       9     -2664 Resp… Couple… Male     845     70
10 5507… 010   5507…    1966       1      2206 Resp… Couple… Male     679     56
# ℹ 2,718 more rows
# ℹ 21 more variables: ed <dbl>, degree <fct>, race_original <fct>,
#   smoke_ever <fct>, smoke_now <fct>, drink <fct>, height <dbl>, srh <fct>,
#   act_vig <fct>, bp <fct>, diab <fct>, cancer <fct>, lung <fct>, hrt <fct>,
#   strk <fct>, psych <fct>, sleep <fct>, arth <fct>, cond_count <dbl>,
#   cesd <dbl>, income <dbl>

Data frames and tibbles

  • Did you notice the output of the tibble?

 

  • Tibbles are a newer object type

 

  • They are a modern take on data frames that are part of the tidyverse

 

  • Main difference is that tibbles print a little nicer within the console
    • So we’ll often see them as output for functions that display data frames

Did you see the variables in the data frame?

  • The columns in a data frame are called “variables”
  • We can see the variable types in the tibble display
tibble(hrs_data)
# A tibble: 2,728 × 32
   hhid  pn    id    birthyr birthmo birthdate proxy coupled sex   age_mo age_yr
   <fct> <fct> <chr>   <dbl>   <dbl>     <dbl> <fct> <fct>   <fct>  <dbl>  <dbl>
 1 5527… 010   5527…    1967       9      2814 Resp… Not a … Fema…    665     55
 2 5553… 020   5553…    1966       7      2387 Resp… Couple… Fema…    676     56
 3 5597… 010   5597…    1967       3      2602 Resp… Couple… Male     663     55
 4 5581… 020   5581…    1973      10      5036 Resp… Couple… Male     600     50
 5 5547… 020   5547…    1950       7     -3153 Resp… Couple… Male     860     71
 6 5510… 010   5510…    1970       1      3667 Resp… Not a … Fema…    632     52
 7 5505… 010   5505…    1960       1        14 Resp… Not a … Male     749     62
 8 5590… 010   5590…    1971       4      4122 Resp… Couple… Male     621     51
 9 5562… 020   5562…    1952       9     -2664 Resp… Couple… Male     845     70
10 5507… 010   5507…    1966       1      2206 Resp… Couple… Male     679     56
# ℹ 2,718 more rows
# ℹ 21 more variables: ed <dbl>, degree <fct>, race_original <fct>,
#   smoke_ever <fct>, smoke_now <fct>, drink <fct>, height <dbl>, srh <fct>,
#   act_vig <fct>, bp <fct>, diab <fct>, cancer <fct>, lung <fct>, hrt <fct>,
#   strk <fct>, psych <fct>, sleep <fct>, arth <fct>, cond_count <dbl>,
#   cesd <dbl>, income <dbl>

Accessing variables in a data frame

  • We can access variables in a data frame using the $ operator

 

  • I want to look at the first five entries of birth year
head(hrs_data$birthyr)
[1] 1967 1966 1967 1973 1950 1970
  • I want to look at the first five entries of degree
head(hrs_data$degree)
[1] <NA>                                High school diploma                
[3] <NA>                                Master's degree                    
[5] Master's degree                     Professional degree (Ph.D./M.D./JD)
7 Levels: High school diploma ... Bachelor's degree
  • Notice, degree will also show the levels of the factor variable

Checking the object type of a variable

  • We can also check the object type of each variable without viewing the whole data frame

 

  • Birth year is a numeric variable, so it is a double (dbl)
class(hrs_data$birthyr)
[1] "numeric"
  • While degree is a factor variable, so it is a factor (fct)
class(hrs_data$degree)
[1] "factor"

Wrap-up

  • We learned about…
    • R objects
    • Assigning values to objects
    • Different types of objects
      • single piece of data
      • collection of data
    • Data frames and tibbles

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