Utilities for processing d-style string formatting specifications (eg "xx.dx")
Source:R/jjcsformats_d.R, R/zzz_format_d_setup.R
fmt_spec_d.Rd![[Experimental]](figures/lifecycle-experimental.svg)
Usage
fmt_spec_single_d(
d = 1,
stats_in = NULL,
fmt_d_def = junco_def_d_all,
fmt_d_in = NULL
)
fmt_spec_df_d(
df_d,
d_column = "d",
fmt_column = "fmt_d",
stats_in = NULL,
fmt_d_def = junco_def_d_all,
fmt_d_in = NULL
)
fmt_spec_var_d(
var_d,
stats_in = NULL,
fmt_d_def = junco_def_d_all,
fmt_d_in = NULL
)
junco_def_d_all
junco_def_d_alt1
junco_def_d_alt2Format
junco_def_d_allUsed as default input vector for argumentfmt_d_defin functionsfmt_spec_single_d(),fmt_spec_df_d()andfmt_spec_var_d()(corresponds to the named vector of with default available formats junco_default_formats with d = 1)
junco_def_d_alt1Alternative vector of d-style specification defaults.
junco_def_d_alt2Another alternative vector of d-style specification defaults.
Arguments
- d
integer(1)Value ofdfor the translation of "xx.dx" into "xx.xx" style (example whend= 1)- stats_in
(character)Set of statistics to restrict to.- fmt_d_def
Named vector with default format specifications where d-style format is allowed.
- fmt_d_in
Named vector with format specifications where d-style format is allowed. Formats defined here will take higher precedence over formats in
fmt_d_def.- df_d
Dataframe in which the d-column specification is available.
- d_column
Name of column within dataframe
df_dthat contains required integer values ford.- fmt_column
Name of column that will be added to dataframe that will contain resulting format specifications.
- var_d
Named vector of d specifications. Names are to be considered as variables to be analyzed in further processing.
Details
Format specifications in d-style notation (such as "xx.dx")
will be translated to string based formats
(or wrapped with jjcsformat_xx()), eg "xx.dx" will be translated into "xx.xx", when d = 1.
Functions
fmt_spec_single_d(): Function to convert a named list using d-style string format specification into a named list with validformattersformatting specificationfmt_spec_df_d(): Function to convert an input column with d-style formatting specification into a new column with valid formatters formatting specification.The new column can be passed onto argument
formats_varinrtables::analyze()function.fmt_spec_var_d(): Function to convert a named list of variables with d-style formatting specification into a named list with validformattersformatting specification.The result can be used as input for argument
formatinrtables::analyze()call.junco_def_d_all: Named vector of default format specification using d-style notation.junco_def_d_alt1: Alternative vector of d-style specification defaults.junco_def_d_alt2: Another alternative vector of d-style specification defaults.
Examples
junco_def_d <- c(
"mean" = "xx.dx",
"mean_sd" = "xx.dx (xx.dxx)",
"mean_se" = "xx.dx (xx.dxx)",
"range" = "(xx.d, xx.d)"
)
myfmts <- fmt_spec_single_d(
d = 1,
stats_in = c("mean", "mean_sd"),
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
myfmts
#> $mean
#> [1] "xx.xx"
#>
#> $mean_sd
#> [1] "xx.xx (xx.xxx)"
#>
# example for fmt_spec_df_d ----
library(dplyr)
df_d <- tribble(
~PARAMCD, ~d,
"DIABP", 2L,
"PULSE", 3L,
"RESP", 1L
)
yy <- fmt_spec_df_d(df_d,
d_column = "d",
fmt_column = "fmt_d",
stats_in = NULL,
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
df <- ex_advs |>
filter(PARAMCD %in% c("DIABP", "PULSE", "RESP")) |>
filter(AVISIT %in% c("BASELINE", "WEEK 1 DAY 8", "WEEK 2 DAY 15"))
df <- df |>
left_join(yy)
#> Joining with `by = join_by(PARAMCD)`
lyt <- basic_table() |>
split_cols_by("ARMCD") |>
split_rows_by("PARAMCD", split_fun = drop_split_levels) |>
split_rows_by("AVISIT", split_fun = drop_split_levels) |>
analyze(
vars = "AVAL",
afun = tern::a_summary,
extra_args = list(
.stats = c("n", "mean_se", "range"),
.formats = "default"
),
formats_var = "fmt_d"
)
rslt <- build_table(lyt, df, alt_counts_df = ex_adsl)
rslt
#> ARM A ARM B ARM C
#> ———————————————————————————————————————————————————————————————————————————
#> DIABP
#> BASELINE
#> n 134 134 132
#> Mean (SE) 48.602 (0.6878) 50.442 (0.6866) 51.107 (0.6781)
#> Min - Max (27.71, 64.64) (21.68, 67.51) (29.75, 71.40)
#> WEEK 1 DAY 8
#> n 134 134 132
#> Mean (SE) 50.260 (0.6491) 49.674 (0.6689) 48.855 (0.6866)
#> Min - Max (33.04, 68.98) (33.71, 66.49) (30.39, 66.99)
#> WEEK 2 DAY 15
#> n 134 134 132
#> Mean (SE) 50.836 (0.6781) 49.718 (0.7296) 49.981 (0.7257)
#> Min - Max (31.89, 70.34) (30.64, 68.11) (24.82, 65.57)
#> PULSE
#> BASELINE
#> n 134 134 132
#> Mean (SE) 51.8606 (0.69774) 50.2698 (0.76090) 50.2549 (0.81518)
#> Min - Max (28.466, 72.897) (26.920, 67.335) (27.779, 71.177)
#> WEEK 1 DAY 8
#> n 134 134 132
#> Mean (SE) 50.0645 (0.71838) 49.2673 (0.64961) 49.7958 (0.66585)
#> Min - Max (26.697, 69.371) (30.697, 67.762) (30.145, 72.893)
#> WEEK 2 DAY 15
#> n 134 134 132
#> Mean (SE) 49.7104 (0.75649) 50.8322 (0.65607) 49.0580 (0.66646)
#> Min - Max (25.968, 69.622) (33.317, 70.273) (32.199, 73.643)
#> RESP
#> BASELINE
#> n 134 134 132
#> Mean (SE) 49.41 (0.699) 51.12 (0.707) 50.75 (0.732)
#> Min - Max (29.3, 69.3) (31.2, 74.5) (26.2, 71.0)
#> WEEK 1 DAY 8
#> n 134 134 132
#> Mean (SE) 49.49 (0.695) 49.98 (0.684) 50.97 (0.681)
#> Min - Max (24.1, 66.1) (25.0, 67.7) (29.9, 69.8)
#> WEEK 2 DAY 15
#> n 134 134 132
#> Mean (SE) 49.66 (0.663) 50.35 (0.748) 49.31 (0.743)
#> Min - Max (30.8, 71.3) (28.5, 77.0) (22.4, 67.6)
# example for fmt_spec_var_d ----
var <- c("AGE" = 0, "BMI" = 1, "BMRKR1" = 2)
vars_fmt <- fmt_spec_var_d(var,
stats_in = NULL,
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
vars_fmt
#> $AGE
#> $AGE$mean
#> [1] "xx.x"
#>
#> $AGE$mean_sd
#> [1] "xx.x (xx.xx)"
#>
#> $AGE$mean_se
#> [1] "xx.x (xx.xx)"
#>
#> $AGE$range
#> [1] "(xx., xx.)"
#>
#>
#> $BMI
#> $BMI$mean
#> [1] "xx.xx"
#>
#> $BMI$mean_sd
#> [1] "xx.xx (xx.xxx)"
#>
#> $BMI$mean_se
#> [1] "xx.xx (xx.xxx)"
#>
#> $BMI$range
#> [1] "(xx.x, xx.x)"
#>
#>
#> $BMRKR1
#> $BMRKR1$mean
#> [1] "xx.xxx"
#>
#> $BMRKR1$mean_sd
#> function (x, output, round_type = valid_round_type, na_str = na_str_dflt)
#> {
#> if (anyNA(na_str) || (replace_na_dflt && any(na_str == "NA"))) {
#> na_inds <- which(is.na(na_str) | (replace_na_dflt & na_str ==
#> "NA"))
#> na_str[na_inds] <- rep(na_str_dflt, length.out = length(na_str))[na_inds]
#> }
#> if (length(x) == 0 || isTRUE(all(x == ""))) {
#> return(NULL)
#> }
#> else if (!length(positions[[1]]) == length(x)) {
#> stop("Error: input str in call to jjcsformat_xx must contain same number of xx as the number of stats.")
#> }
#> round_type <- match.arg(round_type)
#> values <- Map(y = x, fun = roundings, na_str = na_str, function(y,
#> fun, na_str, output) {
#> fun(y, na_str = na_str, round_type = round_type)
#> })
#> regmatches(x = str, m = positions)[[1]] <- values
#> return(str)
#> }
#> <bytecode: 0x5640677e7398>
#> <environment: 0x564061d6c080>
#>
#> $BMRKR1$mean_se
#> function (x, output, round_type = valid_round_type, na_str = na_str_dflt)
#> {
#> if (anyNA(na_str) || (replace_na_dflt && any(na_str == "NA"))) {
#> na_inds <- which(is.na(na_str) | (replace_na_dflt & na_str ==
#> "NA"))
#> na_str[na_inds] <- rep(na_str_dflt, length.out = length(na_str))[na_inds]
#> }
#> if (length(x) == 0 || isTRUE(all(x == ""))) {
#> return(NULL)
#> }
#> else if (!length(positions[[1]]) == length(x)) {
#> stop("Error: input str in call to jjcsformat_xx must contain same number of xx as the number of stats.")
#> }
#> round_type <- match.arg(round_type)
#> values <- Map(y = x, fun = roundings, na_str = na_str, function(y,
#> fun, na_str, output) {
#> fun(y, na_str = na_str, round_type = round_type)
#> })
#> regmatches(x = str, m = positions)[[1]] <- values
#> return(str)
#> }
#> <bytecode: 0x5640677e7398>
#> <environment: 0x564061d50578>
#>
#> $BMRKR1$range
#> [1] "(xx.xx, xx.xx)"
#>
#>
lyt <- basic_table() |>
split_cols_by("ARMCD") |>
analyze(
vars = c("AGE", "BMRKR1"),
afun = tern::a_summary,
extra_args = list(
.stats = c("n", "mean_sd", "range"),
.formats = "default"
),
format = vars_fmt,
section_div = " "
)
rslt <- build_table(lyt, ex_adsl)
rslt
#> ARM A ARM B ARM C
#> ——————————————————————————————————————————————————————————————
#> AGE
#> n 134 134 132
#> Mean (SD) 33.8 (6.55) 35.4 (7.90) 35.4 (7.72)
#> Min - Max (21, 50) (21, 62) (20, 69)
#>
#> BMRKR1
#> n 134 134 132
#> Mean (SD) 5.970 (3.5541) 5.699 (3.3067) 5.618 (3.4940)
#> Min - Max (0.41, 17.67) (0.65, 14.24) (0.17, 21.39)