Create a Summary Table

Here is an example of a regulatory-style table of summary statistics:

library(reporter)

# 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) %>% 
  define(var, label = "Variable", blank_after = TRUE, dedupe = TRUE,
         format = c(ampg = "Miles Per Gallon", cyl = "Cylinders")) %>% 
  define(label, label = "") %>% 
  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, encoding = "UTF-8"))

# Client: Motor Trend                                                Study: Cars
#                                   Table 1.0
#                              MTCARS Summary Table
# 
#                                            Group A      Group B
#            Variable                         (N=19)       (N=13)
#            ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
# 
#            Miles Per Gallon  N                19           13
#                              Mean         18.8 (6.5)   22.0 (4.9)
#                              Median          16.4         21.4
#                              Q1 - Q3     15.1 - 21.2  19.2 - 22.8
#                              Range       10.4 - 33.9  14.7 - 32.4
# 
#            Cylinders         8 Cylinder  10 ( 52.6%)   4 ( 30.8%)
#                              6 Cylinder   4 ( 21.1%)   3 ( 23.1%)
#                              4 Cylinder   5 ( 26.3%)   6 ( 46.2%)
# 
# 
# ...
# 
# 
# * Motor Trend, 1974
# 
# 2020-10-16 18:57:02              Confidential                      Page 1 of 1

Next: Example 3: Table Stub