stub: Defines a report stub

Description Usage Arguments Details Value See Also Examples

View source: R/table_spec.r

Description

Combine columns into a nested report stub. The report stub is a common feature of statistical reports. The stub is created with the stub function in combination with some parameters from the define function.

Usage

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stub(
  x,
  vars,
  label = "",
  label_align = NULL,
  align = "left",
  width = NULL,
  format = NULL
)

Arguments

x

The table spec.

vars

A vector of quoted variable names from which to create the stub.

label

The label for the report stub. The default label is an empty string ("").

label_align

The alignment for the stub column label. Valid values are 'left', 'right', 'center', and 'centre'. Default follows the align parameter.

align

How to align the stub column. Valid values are 'left', 'right', 'center', and 'centre'. Default is 'left'.

width

The width of the stub, in report units of measure.

format

A format to apply to the stub column.

Details

The table stub is a nested set of labels that identify rows on the table. The stub is created by combining two or more columns into a single stub column. The relationship between the columns is typically visualized as a hierarchy, with lower level concepts indented under higher level concepts.

A typical stub is created with the following steps:

The stub will be automatically added as an identity variable on the report, and will always appear as the leftmost column. There can only be one stub defined on a report.

Value

The modified table spec.

See Also

Other table: column_defaults(), create_table(), define(), print.table_spec(), spanning_header()

Examples

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library(rptr)
library(magrittr)

# Create temporary path
tmp <- file.path(tempdir(), "example2.txt")

# Read in prepared data
df <- read.table(header = TRUE, text = '
      var      label        A             B          
      "ampg"   "N"          "19"          "13"         
      "ampg"   "Mean"       "18.8 (6.5)"  "22.0 (4.9)" 
      "ampg"   "Median"     "16.4"        "21.4"       
      "ampg"   "Q1 - Q3"    "15.1 - 21.2" "19.2 - 22.8"
      "ampg"   "Range"      "10.4 - 33.9" "14.7 - 32.4"
      "cyl"    "8 Cylinder" "10 ( 52.6%)" "4 ( 30.8%)" 
      "cyl"    "6 Cylinder" "4 ( 21.1%)"  "3 ( 23.1%)" 
      "cyl"    "4 Cylinder" "5 ( 26.3%)"  "6 ( 46.2%)"')

# Create table
tbl <- create_table(df, first_row_blank = TRUE) %>% 
  stub(c("var", "label")) %>% 
  define(var, blank_after = TRUE, label_row = TRUE, 
         format = c(ampg = "Miles Per Gallon", cyl = "Cylinders")) %>% 
  define(label, indent = .25) %>% 
  define(A, label = "Group A", align = "center", n = 19) %>% 
  define(B, label = "Group B", align = "center", n = 13)


# Create report and add content
rpt <- create_report(tmp, orientation = "portrait") %>% 
  page_header(left = "Client: Motor Trend", right = "Study: Cars") %>% 
  titles("Table 1.0", "MTCARS Summary Table") %>% 
  add_content(tbl) %>% 
  footnotes("* Motor Trend, 1974") %>%
  page_footer(left = Sys.time(), 
              center = "Confidential", 
              right = "Page [pg] of [tpg]")

# Write out report
write_report(rpt)

# View report in console
writeLines(readLines(tmp))

# Client: Motor Trend                                                Study: Cars
#                                   Table 1.0
#                              MTCARS Summary Table
# 
#                                     Group A      Group B
#                                      (N=19)       (N=13)
#                  -------------------------------------------
# 
#                 Miles Per Gallon
#                    N                   19           13
#                    Mean            19.3 (6.7)   21.3 (4.8)
#                    Median             17.3         21.0
#                    Q1 - Q3        15.2 - 22.1  19.2 - 22.8
#                    Range          10.4 - 33.9  14.3 - 32.4
#
#                 Cylinders
#                    8 Cylinder     10 ( 52.6%)   4 ( 30.8%)
#                    6 Cylinder      3 ( 15.8%)   4 ( 30.8%)
#                    4 Cylinder      6 ( 31.6%)   5 ( 38.5%)
# 
# ...
# 
# 
# * Motor Trend, 1974
# 
# 2020-08-30 03:50:02              Confidential                      Page 1 of 1
#

dbosak01/reporter documentation built on Sept. 22, 2020, 3:34 p.m.