drop_row: Filter Rows That Contain Markers

In trinker/textclean: Text Cleaning Tools

Description

drop_row - Remove rows from a data set that contain a given marker/term.

keep_row - Keep rows from a data set that contain a given marker/term.

drop_empty_row - Removes the empty rows of a data set that are common in reading in data.

drop_NA - Removes the NA rows of a data set.

Usage

drop_row(dataframe, column, terms, ...)

keep_row(dataframe, column, terms, ...)

drop_empty_row(dataframe)

drop_NA(dataframe, column = TRUE, ...)

Arguments

dataframe	A dataframe object.
column	Column name to search for markers/terms.
terms	The regex terms/markers of the rows that are to be removed from the dataframe.
...	Other arguments passed to grepl.

Value

drop_row - returns a dataframe with the termed/markered rows removed.

drop_empty_row - returns a dataframe with empty rows removed.

drop_NA - returns a dataframe with NA rows removed.

Examples

## Not run: 
## drop_row EXAMPLE:
drop_row(DATA, "person", c("sam", "greg"))
keep_row(DATA, "person", c("sam", "greg"))
drop_row(DATA, 1, c("sam", "greg"))
drop_row(DATA, "state", c("Comp"))
drop_row(DATA, "state", c("I "))
drop_row(DATA, "state", c("you"), ignore.case=TRUE)

## drop_empty_row EXAMPLE:
(dat <- rbind.data.frame(DATA[, c(1, 4)], matrix(rep(" ", 4), 
   ncol =2, dimnames=list(12:13, colnames(DATA)[c(1, 4)]))))
drop_empty_row(dat)

## drop_NA EXAMPLE:
DATA[1:3, "state"] <- NA
drop_NA(DATA)

## End(Not run)

trinker/textclean documentation built on Nov. 3, 2021, 7:20 p.m.