View source: R/dropAllMissing.R
dropAllMissing | R Documentation |
This function is useful for dealing with NA
s in data frames. Only
rows in the data specified by columns
that have only missing values
are removed.
dropAllMissing(data, columns = "All", ...)
data |
the dataset to subset for all missing values. |
columns |
the columns to check for missing values. See Details. |
... |
any additional arguments to |
The value for columns
can be a character vector containing the
name of the columns to check, or "All," which checks all columns. Or it can be
a function that returns a logical value–TRUE
checks the column and
FALSE
does not. Any additonal arguments the the function can be given
by ....
The dataset data
having rows with at least one nonmissing value
in the columns specified by columns
.
# create a short test dataset test.df <- data.frame(A=c("a", "b", "c", "d", "e"), B=c(1, 2, NA, NA, 5), # numeric values C=c(1L, 3L, NA, 4L, NA), # integer values D=c(1, 2, NA, NA, 5)) # more numeric values # The default, no row has all missing values dropAllMissing(test.df) # Check 2 columns dropAllMissing(test.df, columns=c("B", "C")) # check all numeric, including both integer and numeric types dropAllMissing(test.df, columns=is.numeric) # Check only those that are type numeric dropAllMissing(test.df, columns=inherits, what="numeric")
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