Paste data.frame rows into character vector

Paste data.frame rows into a character vector, optionally removing empty fields in order to avoid delimiters being duplicated.

pasteByRow(
  x,
  sep = "_",
  na.rm = TRUE,
  condenseBlanks = TRUE,
  includeNames = FALSE,
  sepName = ":",
  blankGrep = "^[ ]*$",
  verbose = FALSE,
  ...
)

Arguments

x

data.frame or comparable object such as matrix or tibble.

sep

character string separator to use between columns.

na.rm

logical whether to remove NA values, or include them as "NA" strings.

condenseBlanks

logical whether to condense blank or empty values without including an extra delimiter between columns.

includeNames

logical whether to include the colname delimited prior to the value, using sepName as the delimiter.

sepName

character string relevant when includeNames=TRUE, this value becomes the delimiter between name:value.

blankGrep

character string used as regular expression pattern in grep() to recognize blank entries; by default any field containing no text, or only whitespace, is considered a blank entry.

verbose

logical whether to print verbose output.

...

additional arguments are ignored.

Value

character vector of length nrow(x).

Details

This function is intended to paste data.frame (or matrix, or tibble) values for each row of data. It differs from using apply(x, 2, paste):

• it handles factors without converting to integer factor level numbers.

• it also by default removes blank or empty fields, preventing the delimiter from being included multiple times, per the condenseBlanks argument.

• it is notably faster than apply, by means of running paste() on each column of data, making the output vectorized, and scaling rather well for large data.frame objects.

The output can also include name:value pairs, which can make the output data more self-describing in some circumstances. That said, the most basic usefulness of this function is to create row labels.

See also

Other jam string functions: asSize(), breaksByVector(), cPasteSU(), cPasteS(), cPasteUnique(), cPasteU(), cPaste(), fillBlanks(), formatInt(), gsubOrdered(), gsubs(), makeNames(), mixedOrder(), mixedSortDF(), mixedSorts(), mixedSort(), mmixedOrder(), nameVectorN(), nameVector(), padInteger(), padString(), pasteByRowOrdered(), sizeAsNum(), tcount(), ucfirst(), uniques()

Examples

# create an example data.frame
a1 <- c("red","blue")[c(1,1,2)];
b1 <- c("yellow","orange")[c(1,2,2)];
d1 <- c("purple","green")[c(1,2,2)];
df2 <- data.frame(a=a1, b=b1, d=d1);
df2;
#>      a      b      d
#> 1  red yellow purple
#> 2  red orange  green
#> 3 blue orange  green

# the basic output
pasteByRow(df2);
#>                   1                   2                   3 
#> "red_yellow_purple"  "red_orange_green" "blue_orange_green" 

# Now remove an entry to show the empty field is skipped
df2[3,3] <- "";
pasteByRow(df2);
#>                   1                   2                   3 
#> "red_yellow_purple"  "red_orange_green"       "blue_orange" 

# the output tends to make good rownames
rownames(df2) <- pasteByRow(df2);

# since the data.frame contains colors, we display using
# imageByColors()
par("mar"=c(5,10,4,2));
imageByColors(df2, cellnote=df2);