filter_missing {framecleaner} | R Documentation |
filter out missings
Description
More complex wrapper around dplyr::filter(!is.na())
to remove NA
rows using tidyselect. If any specified column contains an NA
the whole row is removed. Reports the amount of rows removed containing NaN
, NA
, Inf
, in that order.
For example if one row contains Inf
in one column and in another, the removed row will be counted in the NA
tally.
Usage
filter_missing(.data, ..., remove_inf = TRUE)
## S3 method for class 'data.frame'
filter_missing(.data, ..., remove_inf = TRUE, condition = c("any", "all"))
Arguments
.data |
dataframe |
... |
tidyselect. default selection is all columns |
remove_inf |
logical. default is to also remove |
condition |
defaults to "any". in which case removes rows if |
Details
S3 method, can also be used on vectors
Value
data frame
Examples
tibble::tibble(x = c(NA, 1L, 2L, NA, NaN, 5L, Inf),
y = c(1L, NA, 2L, NA, Inf, 5L, Inf)) -> tbl1
tbl1
# remove any row with a missing or Inf
tbl1 %>%
filter_missing()
# remove any row with Na or NaN in the x column
tbl1 %>%
filter_missing(x, remove_inf = FALSE)
# only remove rows where every entry is Na, NaN, or Inf
tbl1 %>%
filter_missing(condition = "all")
[Package framecleaner version 0.2.1 Index]