Tables

gtsummary, gt, and gtExtras

1 Tables

Install the gt and gtsummary packages and load them.

Use install.packages() to download the gt and gtsummary packages. When you have done that add library(gt) and library(gtsummary) to the code chunk where you call your libraries. Execute the lines.

1.1 gtsummary

In soldiers use tbl_summary() to show the sex, heightcm, weightkg, and race of the soldiers

• Create a tbl_summary()

Code

soldiers %>% 
  select(sex, heightcm, weightkg) %>% 
  tbl_summary()

In soldiers use tbl_summary() to show the sex, heightcm, weightkg, split by WritingPreference of the soldiers

• Dont display missing values
• add_p() (read here and here if you want to change the default tests).

Try the following functions:

• add_overall()
• add_stat_label()
• bold_labels()
• italicize_levels()
• When you have the table you like use as_gt() %>% gtsave(filename = here(""))

Code

soldiers %>% 
  select(sex, heightcm, weightkg, WritingPreference) %>% 
  tbl_summary(
    by = WritingPreference,
    missing = "no"
  ) %>% 
  add_p() %>% 
  bold_labels() %>% 
  italicize_levels() %>% 
  add_overall() 

Improve the table further

You probably need to investigate the help file for tbl_summary() to solve these. * Change the statistics to mean and sd * Change the statistical test of the continous variables from a “Kruskal-Wallis rank sum test” to a One-way ANOVA * Find better names for sex, heightcm, and weightkg * save the table as a .docx file in your tables folder

Code

my_table <- soldiers %>% 
  select(sex, heightcm, weightkg, WritingPreference) %>% 
  tbl_summary(
    by = WritingPreference,
    missing = "no",
    
    # Change labels
    label = list(
      sex ~ "Sex",
      weightkg ~ "Weight (kg)",
      heightcm ~ "Height (cm)"),
    
    # Change statistics
    statistic = list(all_continuous() ~ "{mean} ({sd})")
    
    
  ) %>% 
  
  # t.test
  add_p(
    test = list(all_continuous() ~ "aov",
                all_categorical() ~ "chisq.test.no.correct")
    ) %>% 
  bold_labels() %>% 
  italicize_levels() %>% 
  add_overall() 

my_table


my_table %>% 
  as_gt() %>% 
  gtsave(filename = here("tables", "my_table.docx"))

Go to your homeassignment and update it with one or more tables

1.2 gt

Explain what the 4 main group of functions in gt are and what they do

• tab_*()
• fmt_*()
• cols_*()
• cells_*()

Find a dataset and prepare it for a table

Below is a suggestion for soldiers, but you are free to try with you own data if you prefer that.

Using soldiers and gt(), create a table in the following steps:

• Keep the columns Installation, sex, and all the columns that ends with circumference,
• Remove Fort Rucker - it only has one soldier
• Group by Installation and sex
• summarise the data and calculate the mean and sd of all the columns that ends with circumference
  • you can do this manually (with many lines of code)
  • or you can do this by using the across() function inside summarise(). If you are going to be working with a dataset that has many columns, I suggest you invest some time into learning about across()
• pipe the summarised table to gt() and set the rowname_col argument to sex
• add a suitable title and subtitle
• Assign the table to an object called my_tbl

Code

my_tbl <- soldiers %>% 
  
  # Select some columns and arrange the tible
  select(Installation, sex, 
         ends_with("circumference")) %>% 
  
  # Remove Fort Rucker
  filter(Installation != "Fort Rucker") %>% 

  # Remove the Installation with only one Soldier
  #group_by(Installation) %>% 
  #add_count() %>% 
  #filter(n > 1) %>% 
  
  # Summary stats by Installation and Race
  group_by(Installation, sex) %>% 
  summarise(
    across(.cols = ends_with("circumference"),
           .fns = list(mean = ~ mean(.x, na.rm = TRUE),
                       sd = ~ sd(.x, na.rm = TRUE)))) %>% 
  
  # group only by installation
  # because we want to use sex in the rowname_col argument in gt() - see below
  group_by(Installation) %>% 
  
  # Send to gt and perform a few styling functions
  gt(rowname_col = "sex") %>% 
  
  tab_header(
    title = md("**Overview of soldiers soldiers by sex and installation**"),
    subtitle = md("*The data is a mock up version of the soldiers dataset*")) %>% 
  
  tab_footnote(
    footnote = "To preserve anonymity, observations from Fort Rucker has been removed becuase of a low number of observations"
  )

my_tbl

Style my_tbl as you like

You can some try some of these functions

• tab_header()

• tab_source_note()

• tab_stubhead()

• tab_spanner()

• tab_spanner_delim()

• fmt_number()
  

• fmt_percent()
  

• fmt_missing()

• col_merge_n_pct()

• cols_label()

• md()

• cells_body() and tab_footnote()

Code

# It is always a choice how much you want to style your in R, and what you leave for manual editing afterwards (e.g. Word)
# You can style everything in R, but it can be code intensive
# In general - you want the basic structure of your table to be in place
# You NEVER want to manually edit values or merge columns.
# Editing column and spanners names are less labour intensive and dont contain the same risk of making errors
# I think the below table is an ok place to stop the styling in R.

my_tbl_styled <- my_tbl %>% 
  
  tab_spanner_delim(
    delim = "_",
    columns = everything()
  ) %>%
  
  fmt_number(
    columns = contains("circumference"),
    decimals = 1
  ) %>% 
  
  cols_merge(
    columns = contains("thigh"),
    pattern = "{1} ({2})"
    ) %>% 
  
  cols_merge(
    columns = contains("waist"),
    pattern = "{1} ({2})"
    ) %>% 
  
  cols_merge(
    columns = contains("ankle"),
    pattern = "{1} ({2})"
    ) %>% 
  
  cols_merge(
    columns = contains("biceps"),
    pattern = "{1} ({2})"
    ) %>% 
  
  cols_merge(
    columns = contains("calf"),
    pattern = "{1} ({2})"
    ) 

my_tbl_styled

Save your table using gtsave()

• Create a folder called “tables”

Code

gtsave(
  data = my_tbl_styled,
  filename = here("tables", "ANSUR_fort_sex.docx")
)

# Word can also open .rtf  files - its sometimes works better in this format
gtsave(
  data = my_tbl_styled,
  filename = here("tables", "ANSUR_fort_sex.rtf")
)

WANT MORE?

Give the row group labels, heading, and column labels a different background color

• Use tab_options()

Code

my_tbl_styled %>% 
  tab_options(row_group.background.color = "#C2B7B7") %>% 
  tab_options(heading.background.color = "#C2B7B7") %>% 
  tab_options(column_labels.background.color = "#C2B7B7")

1.3 gtExtras

Install the package gtExtras and add library(gtExtras) to the codechunk where you load your libraries.

Add a cool theme to your table gt_theme_

Code

my_tbl_styled %>% 
  gt_theme_espn()

Color thighcircumference_mean with Hulk colors using gt_hulk_col_numeric(thighcircumference_mean)

Code

my_tbl_styled %>% 
  gt_theme_espn() %>% 
  gt_hulk_col_numeric(thighcircumference_mean)