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Printing (HTML)

Basic printing

If a tabulation function is called from the top level, it should print out its table(s) on its own.

As usual, first, letâs start up the package and pick a survey to analyze:

library(surveytable)
set_survey(namcs2019sv)

Survey info {NAMCS 2019 PUF} Variables Observations Design 33 8,250 Stratified 1 - level Cluster Sampling design (with replacement) With (398) clusters. namcs2019sv = survey::svydesign(ids = ~CPSUM, strata = ~CSTRATM, weights = ~PATWT , data = namcs2019sv_df)

Now, when a tabulation function is called from the top level, it prints. You donât need to do anything extra.

Patient age recode {NAMCS 2019 PUF} Level n Number (000) SE (000) LL (000) UL (000) Percent SE LL UL Under 15 years 887 117,917 14,097 93,229 149,142 11.4 1.3 8.9 14.2 15-24 years 542 64,856 7,018 52,387 80,292 6.3 0.6 5.1 7.5 25-44 years 1,435 170,271 13,966 144,925 200,049 16.4 1.1 14.3 18.8 45-64 years 2,283 309,506 23,290 266,994 358,787 29.9 1.4 27.2 32.6 65-74 years 1,661 206,866 14,366 180,481 237,109 20.0 1.2 17.6 22.5 75 years and over 1,442 167,069 15,179 139,746 199,735 16.1 1.3 13.7 18.8

If a tabulation function is called not from the top level, such as from within a loop or another function, you do need to call print() explicitly for it to print. For example:

for (vr in c("AGER", "SEX")) {
  print( tab_subset(vr, "MAJOR", "Preventive care") )
}

Patient age recode (Major reason for this visit = Preventive care) {NAMCS 2019 PUF} Level n Number (000) SE (000) LL (000) UL (000) Percent SE LL UL Under 15 years 300 50,701 8,556 36,352 70,714 22.7 3.5 16.1 30.4 15-24 years 121 18,196 2,889 13,246 24,996 8.1 1.2 5.9 10.9 25-44 years 370 50,573 6,835 38,749 66,005 22.6 2.5 17.8 28.0 45-64 years 355 53,805 9,478 37,982 76,218 24.1 3.2 17.9 31.1 65-74 years 225 27,985 4,669 20,073 39,017 12.5 1.8 9.2 16.5 75 years and over 197 22,363 3,805 15,925 31,404 10.0 1.7 6.9 13.8 Patient sex (Major reason for this visit = Preventive care) {NAMCS 2019 PUF} Level n Number (000) SE (000) LL (000) UL (000) Percent SE LL UL Female 1,014 139,091 11,845 117,664 164,421 62.2 2.9 56.2 68.0 Male 554 84,532 10,594 66,039 108,204 37.8 2.9 32.0 43.8 Create HTML or PDF tables

Using a Quarto document, you can create tables in many different formats, such as HTML or PDF. Here is a straightforward example of what a Quarto document might look like:

---
title: "My tables"
author: "Me"
format: html
---

# Welcome 

As usual, first, let's start up the package and pick a survey to analyze:

```{r, results='asis'}
library(surveytable)
set_survey(namcs2019sv)
```

# Tables

Take a look at this table:

```{r, results='asis'}
tab("AGER")
```

Note the format setting, which specifies that this document will create HTML tables. Also note that you do have to add the results='asis' argument to the code chunks that print tables.

Print using various table-making packages

Use the output argument of set_opts() to select a table-making package. By default (output = "auto"), surveytable automatically selects a package depending on whether the output is to the screen (huxtable), HTML (gt), or PDF (kableExtra). You can also explicitly select one of these packages.

Changing the table-making package has a couple of uses:

Use as_object() to generate an object from your favorite table-making package, customize this object, and then finally print it, so the table looks exactly the way you want it to look.
Print to destinations other than the screen, HTML, or PDF.

huxtable

set_opts(output = "huxtable")
#> * Printing with huxtable.

This is what printing to the screen looks like.

#>                                 Patient age recode {NAMCS 2019 PUF}                                 
#> âââââââââââââââ¬ââââââââ¬ââââââââââââââ¬âââââââââââ¬âââââââââââ¬âââââââââââ¬ââââââââââ¬ââââââ¬âââââââ¬âââââââ
#> â Level       â     n â      Number â SE (000) â LL (000) â UL (000) â Percent â  SE â   LL â   UL â
#> â             â       â       (000) â          â          â          â         â     â      â      â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â Under 15    â   887 â     117,917 â   14,097 â   93,229 â  149,142 â    11.4 â 1.3 â  8.9 â 14.2 â
#> â years       â       â             â          â          â          â         â     â      â      â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 15-24 years â   542 â      64,856 â    7,018 â   52,387 â   80,292 â     6.3 â 0.6 â  5.1 â  7.5 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 25-44 years â 1,435 â     170,271 â   13,966 â  144,925 â  200,049 â    16.4 â 1.1 â 14.3 â 18.8 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 45-64 years â 2,283 â     309,506 â   23,290 â  266,994 â  358,787 â    29.9 â 1.4 â 27.2 â 32.6 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 65-74 years â 1,661 â     206,866 â   14,366 â  180,481 â  237,109 â    20Â Â  â 1.2 â 17.6 â 22.5 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 75 years    â 1,442 â     167,069 â   15,179 â  139,746 â  199,735 â    16.1 â 1.3 â 13.7 â 18.8 â
#> â and over    â       â             â          â          â          â         â     â      â      â
#> âââââââââââââââ´ââââââââ´ââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´ââââââââââ´ââââââ´âââââââ´âââââââ
#>   N = 8250. Checked NCHS presentation standards. Nothing to report.

To create HTML tables from an R Markdown notebook or a Quarto document, add the results='asis' argument to the code chunk, like so:

```{r, results='asis'}
tab("AGER")
```

Patient age recode {NAMCS 2019 PUF} Level n Number (000) SE (000) LL (000) UL (000) Percent SE LL UL Under 15 years 887 117,917 14,097 93,229 149,142 11.4 1.3 8.9 14.2 15-24 years 542 64,856 7,018 52,387 80,292 6.3 0.6 5.1 7.5 25-44 years 1,435 170,271 13,966 144,925 200,049 16.4 1.1 14.3 18.8 45-64 years 2,283 309,506 23,290 266,994 358,787 29.9 1.4 27.2 32.6 65-74 years 1,661 206,866 14,366 180,481 237,109 20Â Â 1.2 17.6 22.5 75 years and over 1,442 167,069 15,179 139,746 199,735 16.1 1.3 13.7 18.8 N = 8250. Checked NCHS presentation standards. Nothing to report. gt

set_opts(output = "gt")
#> * Printing with gt.

With gt, printing to the screen and to HTML look the same. Here is what printing to the screen looks like:

Here is HTML:

```{r, results='asis'}
tab("AGER")
```

auto is the default option. It automatically selects one of the above packages depending on whether the output is to the screen (huxtable), HTML (gt), or PDF (kableExtra).

set_opts(output = "auto")
#> * Printing with huxtable for screen, gt for HTML, or kableExtra for PDF.

Screen output (this should use huxtable):

#>                                 Patient age recode {NAMCS 2019 PUF}                                 
#> âââââââââââââââ¬ââââââââ¬ââââââââââââââ¬âââââââââââ¬âââââââââââ¬âââââââââââ¬ââââââââââ¬ââââââ¬âââââââ¬âââââââ
#> â Level       â     n â      Number â SE (000) â LL (000) â UL (000) â Percent â  SE â   LL â   UL â
#> â             â       â       (000) â          â          â          â         â     â      â      â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â Under 15    â   887 â     117,917 â   14,097 â   93,229 â  149,142 â    11.4 â 1.3 â  8.9 â 14.2 â
#> â years       â       â             â          â          â          â         â     â      â      â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 15-24 years â   542 â      64,856 â    7,018 â   52,387 â   80,292 â     6.3 â 0.6 â  5.1 â  7.5 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 25-44 years â 1,435 â     170,271 â   13,966 â  144,925 â  200,049 â    16.4 â 1.1 â 14.3 â 18.8 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 45-64 years â 2,283 â     309,506 â   23,290 â  266,994 â  358,787 â    29.9 â 1.4 â 27.2 â 32.6 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 65-74 years â 1,661 â     206,866 â   14,366 â  180,481 â  237,109 â    20Â Â  â 1.2 â 17.6 â 22.5 â
#> âââââââââââââââ¼ââââââââ¼ââââââââââââââ¼âââââââââââ¼âââââââââââ¼âââââââââââ¼ââââââââââ¼ââââââ¼âââââââ¼âââââââ¤
#> â 75 years    â 1,442 â     167,069 â   15,179 â  139,746 â  199,735 â    16.1 â 1.3 â 13.7 â 18.8 â
#> â and over    â       â             â          â          â          â         â     â      â      â
#> âââââââââââââââ´ââââââââ´ââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´ââââââââââ´ââââââ´âââââââ´âââââââ
#>   N = 8250. Checked NCHS presentation standards. Nothing to report.

HTML output (this should use gt):

```{r, results='asis'}
tab("AGER")
```

Advanced users can add functionality to use any table-making package that they want. For more information, see help("surveytable-options").

The âquick-and-dirtyâ approach

The tabulation functions return either:

for a single table, a data frame, with certain attributes set; or
for more than one table, a list of such data frames.

You can convert a single table to a data.frame with as.data.frame(), like so:

tab("AGER") |> as.data.frame()
#>               Level    n Number (000) SE (000) LL (000) UL (000) Percent  SE
#> 1    Under 15 years  887       117917    14097    93229   149142    11.4 1.3
#> 2       15-24 years  542        64856     7018    52387    80292     6.3 0.6
#> 3       25-44 years 1435       170271    13966   144925   200049    16.4 1.1
#> 4       45-64 years 2283       309506    23290   266994   358787    29.9 1.4
#> 5       65-74 years 1661       206866    14366   180481   237109    20.0 1.2
#> 6 75 years and over 1442       167069    15179   139746   199735    16.1 1.3
#>     LL   UL
#> 1  8.9 14.2
#> 2  5.1  7.5
#> 3 14.3 18.8
#> 4 27.2 32.6
#> 5 17.6 22.5
#> 6 13.7 18.8

Alternatively, you can pass this data frame to your favorite table-making package. This example passes it to gt:

set_opts(count = "1k")
#> * Rounding counts to the nearest thousand.

Level n Number (000) SE (000) LL (000) UL (000) Percent SE LL UL Under 15 years 887 117917 14097 93229 149142 11.4 1.3 8.9 14.2 15-24 years 542 64856 7018 52387 80292 6.3 0.6 5.1 7.5 25-44 years 1435 170271 13966 144925 200049 16.4 1.1 14.3 18.8 45-64 years 2283 309506 23290 266994 358787 29.9 1.4 27.2 32.6 65-74 years 1661 206866 14366 180481 237109 20.0 1.2 17.6 22.5 75 years and over 1442 167069 15179 139746 199735 16.1 1.3 13.7 18.8

The reason that this is the âquick-and-dirtyâ approach is that the output it creates is not as nice as conventional tables, described above. The output does not have table title (which has important information about the variable and the survey), table footer (which has important information about sample size and low-precision estimates), and it does not format the estimates. Nevertheless, there could be situations in which this approach is helpful, such as

extracting an exact value from a table using as.data.frame(); or
quickly using your favorite table-making package.

Save the tables Save to a CSV file

All tabulation functions have an argument called csv. Use it to specify the name of a CSV (comma-separated values) file, like so:

tab("AGER", csv = "myfile.csv")

Open this CSV file in Excel or your favorite text editor or spreadsheet.

Save to an R data file

Use the built-in saveRDS() function to save a table to an R data file:

tab("AGER") |> saveRDS("myfile.rds")

You can later load this data file back into R. To print the table, just load the file, like so:

There are times when you might want to prevent the tabulation functions from printing tables. If you are saving the tables to a CSV file anyway, you might not need screen printing.

As mentioned above, if the tabulation functions are called from within a loop without using the print() command, they wonât print.

An easy way to suppress printing when the tabulation functions are called from the top level is to assign the output to some variable. For example, this will save the table to a CSV file, but wonât print it to the screen:

tmp = tab("AGER", csv = "myfile.csv")

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