Customize data frame and tibble printing methods

_common.R

@@ -13,3 +13,25 @@ rtf2pdf <- function(input) {
   z <- paste(x, y, sep = " && ")
   if (Sys.getenv("GITHUB_ACTIONS") != "") system(z) else invisible(NULL)
 }
+
+# Customize data frame and tibble printing methods.
+# See <https://github.com/elong0527/r4csr/issues/115> for details.
+knit_print.data.frame <- function(x, ...) {
+  paste(capture.output(base::print.data.frame(head(x, 4))), collapse = "\n")
+}
+
+registerS3method(
+  "knit_print", "data.frame", knit_print.data.frame,
+  envir = asNamespace("knitr")
+)
+
+options(pillar.advice = FALSE)
+
+knit_print.tbl_df <- function(x, ...) {
+  paste(capture.output(print(x, n = 4)), collapse = "\n")
+}
+
+registerS3method(
+  "knit_print", "tbl_df", knit_print.tbl_df,
+  envir = asNamespace("knitr")
+)

tlf-ae-specific.qmd

@@ -70,7 +70,7 @@ t1 <- ana %>%
   summarise(n = fmt_num(n_distinct(USUBJID), digits = 0)) %>%
   mutate(AEDECOD = AESOC, order = 0)
 
-t1 %>% head(4)
+t1
 ```
 
 In the code below, we count the number of subjects in each AE term by
@@ -83,7 +83,7 @@ t2 <- ana %>%
   summarise(n = fmt_num(n_distinct(USUBJID), digits = 0)) %>%
   mutate(order = 1)
 
-t2 %>% head(4)
+t2
 ```
 
 We prepare reporting data for AE information using code below:
@@ -100,7 +100,7 @@ t_ae <- bind_rows(t1, t2) %>%
   arrange(AESOC, order, AEDECOD) %>%
   select(AESOC, AEDECOD, starts_with("n"))
 
-t_ae %>% head(4)
+t_ae
 ```
 
 We prepare reporting data for analysis population using code below:
@@ -161,7 +161,7 @@ tbl_ae_spec <- bind_rows(
     AEDECOD, paste0("  ", AEDECOD)
   ))
 
-tbl_ae_spec %>% head(4)
+tbl_ae_spec
 ```
 
 We define the format of the output as below:

tlf-ae-summary.qmd

@@ -58,7 +58,7 @@ tidy_ae <- adae %>%
   select(USUBJID, TRTAN, all, drug, ser, drug_ser, die) %>%
   pivot_longer(cols = c(all, drug, ser, drug_ser, die))
 
-tidy_ae %>% head(4)
+tidy_ae
 ```
 
 We summarize the number and percentage of participants who meet each AE criteria.
@@ -86,7 +86,7 @@ ana <- tidy_ae %>%
     pct = paste0("(", pct, ")")
   )
 
-ana %>% head(4)
+ana
 ```
 
 We prepare reporting-ready dataset for each AE group.

tlf-disposition.qmd

@@ -43,9 +43,7 @@ The following variables are used in the preparation of a simplified disposition
 - DCREASCD: discontinued from study reason coded
 
 ```{r}
-adsl %>%
-  select(USUBJID, TRT01P, TRT01PN, DISCONFL, DCREASCD) %>%
-  head(4)
+adsl %>% select(USUBJID, TRT01P, TRT01PN, DISCONFL, DCREASCD)
 ```
 
 In the code below, we calculate the number of participants in the analysis population by treatment arms.

tlf-efficacy-ancova.qmd

@@ -63,9 +63,7 @@ Below is the first few records of the analysis dataset.
 - CHG: change from baseline
 
 ```{r}
-ana %>%
-  select(USUBJID, TRTPN, AVISIT, AVAL, BASE, CHG) %>%
-  head(4)
+ana %>% select(USUBJID, TRTPN, AVISIT, AVAL, BASE, CHG)
 ```
 
 ## Helper functions

tlf-overview.qmd

@@ -179,9 +179,7 @@ of the dataset, which can be accessed by using the command `?r2rtf_adae` in R.
 :::
 
 ```{r}
-r2rtf_adae |>
-  select(USUBJID, TRTA, AEDECOD) |>
-  head(4)
+r2rtf_adae |> select(USUBJID, TRTA, AEDECOD)
 ```
 
 To manipulate the data and create a data frame containing the necessary
@@ -193,7 +191,7 @@ tbl <- r2rtf_adae %>%
   count(TRTA, AEDECOD) %>%
   pivot_wider(names_from = TRTA, values_from = n, values_fill = 0)
 
-tbl %>% head(4)
+tbl
 ```
 
 Having prepared the dataset `tbl`, we can now proceed with constructing the
@@ -222,7 +220,8 @@ pipes to create an RTF table.
 - `write_rtf()` save RTF encoding into a file with file extension `.rtf`.
 
 ```{r}
-head(tbl) |>
+tbl |>
+  head() |>
   rtf_body() |>
   rtf_encode() |>
   write_rtf("tlf/intro-ae1.rtf")
@@ -252,7 +251,8 @@ as they maintain the same ratio.
 :::
 
 ```{r}
-head(tbl) |>
+tbl |>
+  head() |>
   rtf_body(col_rel_width = c(3, 2, 2, 2)) |>
   rtf_encode() |>
   write_rtf("tlf/intro-ae2.rtf")
@@ -276,7 +276,8 @@ In the following example, we define the column header as
 representing the four columns in the table:
 
 ```{r}
-head(tbl) |>
+tbl |>
+  head() |>
   rtf_colheader(
     colheader = "Adverse Events | Placebo | Xanomeline High Dose | Xanomeline Low Dose",
     col_rel_width = c(3, 2, 2, 2)
@@ -309,7 +310,8 @@ Below is an example to make the first column left-aligned and the rest columns
 center-aligned.
 
 ```{r}
-head(tbl) |>
+tbl |>
+  head() |>
   rtf_body(text_justification = c("l", "c", "c", "c")) |>
   rtf_encode() |>
   write_rtf("tlf/intro-ae5.rtf")
@@ -336,7 +338,8 @@ headers with proper border lines.
 :::
 
 ```{r}
-head(tbl) %>%
+tbl |>
+  head() |>
   rtf_colheader(
     colheader = " | Treatment",
     col_rel_width = c(3, 6)

tlf-population.qmd

@@ -40,9 +40,7 @@ population table using variables below:
 - SAFFL: safety population flag
 
 ```{r}
-adsl %>%
-  select(USUBJID, ITTFL, EFFFL, SAFFL) %>%
-  head(4)
+adsl %>% select(USUBJID, ITTFL, EFFFL, SAFFL)
 ```
 
 ## Helper functions