R/relabel_proportions.R
rename_redundant.RdThese function are only to be used cosmetically before kable and will likely return a data frame with duplicate names.
rename_redundant(x, ...)
augment_redundant(x, ...)a data frame
a series of keys and values to replace columns that match specific patterns.
a data frame.
rename_redundant fully replaces any column names matching the keys
augment_redundant will take a regular expression and rename columns
via gsub().
df <- data.frame(
x = letters[1:10],
`a n` = 1:10,
`a prop` = (1:10) / 10,
`a deff` = round(pi, 2),
`b n` = 10:1,
`b prop` = (10:1) / 10,
`b deff` = round(pi * 2, 2),
check.names = FALSE
)
df
#> x a n a prop a deff b n b prop b deff
#> 1 a 1 0.1 3.14 10 1.0 6.28
#> 2 b 2 0.2 3.14 9 0.9 6.28
#> 3 c 3 0.3 3.14 8 0.8 6.28
#> 4 d 4 0.4 3.14 7 0.7 6.28
#> 5 e 5 0.5 3.14 6 0.6 6.28
#> 6 f 6 0.6 3.14 5 0.5 6.28
#> 7 g 7 0.7 3.14 4 0.4 6.28
#> 8 h 8 0.8 3.14 3 0.3 6.28
#> 9 i 9 0.9 3.14 2 0.2 6.28
#> 10 j 10 1.0 3.14 1 0.1 6.28
print(df <- rename_redundant(df, "%" = "prop", "Design Effect" = "deff"))
#> x a n % Design Effect b n % Design Effect
#> 1 a 1 0.1 3.14 10 1.0 6.28
#> 2 b 2 0.2 3.14 9 0.9 6.28
#> 3 c 3 0.3 3.14 8 0.8 6.28
#> 4 d 4 0.4 3.14 7 0.7 6.28
#> 5 e 5 0.5 3.14 6 0.6 6.28
#> 6 f 6 0.6 3.14 5 0.5 6.28
#> 7 g 7 0.7 3.14 4 0.4 6.28
#> 8 h 8 0.8 3.14 3 0.3 6.28
#> 9 i 9 0.9 3.14 2 0.2 6.28
#> 10 j 10 1.0 3.14 1 0.1 6.28
print(df <- augment_redundant(df, " (n)" = " n$"))
#> x a (n) % Design Effect b (n) % Design Effect
#> 1 a 1 0.1 3.14 10 1.0 6.28
#> 2 b 2 0.2 3.14 9 0.9 6.28
#> 3 c 3 0.3 3.14 8 0.8 6.28
#> 4 d 4 0.4 3.14 7 0.7 6.28
#> 5 e 5 0.5 3.14 6 0.6 6.28
#> 6 f 6 0.6 3.14 5 0.5 6.28
#> 7 g 7 0.7 3.14 4 0.4 6.28
#> 8 h 8 0.8 3.14 3 0.3 6.28
#> 9 i 9 0.9 3.14 2 0.2 6.28
#> 10 j 10 1.0 3.14 1 0.1 6.28