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R in 3 Months (Spring 2025)

Working with labelled data

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View code shown in video
# Load Packages -----------------------------------------------------------

library(tidyverse)
library(zip)
library(haven)
library(labelled)

# Download Data -----------------------------------------------------------

# download.file("https://gss.norc.org/content/dam/gss/get-the-data/documents/stata/2022_stata.zip",
#   destfile = "data-raw/gss-2022.zip"
# )
#
# unzip(
#   zipfile = "data-raw/gss-2022.zip",
#   exdir = "data-raw",
#   junkpaths = TRUE
# )

# Work with Labelled Data -------------------------------------------------

gss_marital_status <-
  read_dta("data-raw/GSS2022.dta") |>
  select(marital)

gss_marital_status

gss_marital_status |> 
  count(marital) |> 
  ggplot(
    aes(
      x = n,
      y = marital
    ) 
  ) +
  geom_col()


# Convert to Factor -------------------------------------------------------

gss_marital_status |>
  generate_dictionary()

gss_marital_status |>
  as_factor()

gss_marital_status_factor <-
  gss_marital_status |>
  as_factor()

gss_marital_status_factor |> 
  count(marital) |> 
  ggplot(
    aes(
      x = n,
      y = marital
    ) 
  ) +
  geom_col()

Have any questions? Put them below and we will help you out!

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Odile DOREUS

Odile DOREUS • October 3, 2024

Hi David, I was trying to use the "labeled" package with a multiple-choice options survey question and encountered an issue. I realized that I needed to tidy my question first before using the function; otherwise, it would not work. Is there a difference when dealing with a single-choice question versus a multiple-choice one?

David Keyes

David Keyes Founder • October 3, 2024

I'm not really sure because I haven't worked with labelled data much. However, I can imagine that having multiple choice data in a single variable could make the labelled package not work right. Happy to look at an example if you have some code you can share.

Odile DOREUS

Odile DOREUS • October 3, 2024

Here you go David. Thanks.

#Daframe for type of kits 
type_kit1 <- pdm_subset_cleandata |>
  select(1,4:7)
              
#Tidy q2 Survey question
type_kit1 <- type_kit1 |>
  pivot_longer(
  cols = c(q_2_1,q_2_2,q_2_3,q_2_4),
  names_to = "q_2",
  values_to = "type_kit1_received",
  values_drop_na = TRUE
  )      
 
# Update the type of kits dataframe as a factor
type_kit1 |>
  generate_dictionary()

type_kit1 |>
  as_factor()

type_kit1_factor <- 
  type_kit1 |>
  as_factor ()


#Aggregate the variable type_kit1_received
type_kit1_factor <- type_kit1_factor|>
  count(type_kit1_received)
David Keyes

David Keyes Founder • October 3, 2024

Can you make this fully reproducible so I can run your code? I'd need to have the data importing step work so I can see what your data looks like.

Hilde Karlsen

Hilde Karlsen • October 10, 2024

Thank you for taking the time to create this video, David! I have been using both the labelled() and haven() packages before, basically doing that you are showing us here. However, what I would love is to do it the way you do it, not the way I have done it (earlier, using stata). Do you think you could create a similar video, where you show the process you would use, working with the same data and the same variable and then creating a meaningful plot?

David Keyes

David Keyes Founder • October 11, 2024

I'm happy to do this, but I'm not quite sure what you mean. Do you want me to make a different plot than the one I show in the video?

Hilde Karlsen

Hilde Karlsen • October 11, 2024

I am sorry for being vague. What I meant is: Can you use data in the form that you would normally use it (i.e. not labelled data from spss/stata etc), and then create a similar plot that you did in the video (i.e. the video where you used the labelled data by transforming the variable into a factor)? What I would love to do is create plots/graphs etc that have meaningful text in it, so that the plot/graph is intuitive for the reader of the report. In order to do that - don´t you often need some type of text string that explains what we are looking at? Even if we don´t call it "a variable label" and "value labels" it is often more meaningful to have variables show up with text (such as in the penguins data, where Islands and Penguins have character string names, they are not calles 1, 2, 3 (for the three different penguin types), for example. I really want to understand what is the best practice of dealing with data in R, and it seems a bit time consuming to always have to specify in a plot that what the x and y labels/values are.

Gracielle Higino

Gracielle Higino Coach • October 11, 2024

If I might chime in here, I think what you'll need is a combination of a tailored function and the use of the fct() function. You can have a vector containing your "labels" and assign them to another variable values when mutating them into a factor using fct(). We have an extra lesson on factors, we'll put it up so you can take a look! Also, we'll discuss some of that a bit later, after we go through advanced data wrangling and data viz! =D

David Keyes

David Keyes Founder • October 11, 2024

Gracielle's suggestion is probably your best bet. Since she knows your data too, maybe she can put something together for you based on your data.

Sara Parisi

Sara Parisi • October 11, 2024

Hi David,

Thanks for recording this extra lesson! Can you add a "View code shown in video" section here so we can copy and paste your code?

David Keyes

David Keyes Founder • October 11, 2024

Oh yes, I meant to do this! Will add it now.

Hilde Karlsen

Hilde Karlsen • October 11, 2024

Gracielle, what you are mentioning about using the combination of a tailored function and the use of the fct() function, so that I can have a vector containing your "labels" and assign them to another variable values when mutating them into a factor using fct() - sounds very much what I would like to do. I am really looking forward to understanding how I can do it, because I am able to to somthing similar, but I don´t really understand what is happening under the hood. If you have an extra lesson on factors, I´ll jump right into it and take a look. It will be sooooo cool to be able to do this in a more programmatic fashion, rather than labelling the data in advande (which is what I want to un-learn) :-)

Gracielle Higino

Gracielle Higino Coach • October 12, 2024

Awesome! The extra lesson is already up here: https://rfortherestofus.com/courses/r-in-3-months-fall-2024/lessons/factors

I'll try a couple of things with your data and then we can book a 1:1 to go through it =D

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