Description Usage Arguments Value Examples
Replace erroneous data by NA
1 |
x |
input data.frame |
... |
condition(s) that define bad data, which will be replaced by NA. Each condition is treated separately and all variables used in the condition are affected by the NA replacement. |
The input data with some elements replaced by NA
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | x <- read.csv(text="
pressure,salinity,sigma theta
1, 38, 29
2, -2, 2
3, 56, 28
4, 37, 35",
check.names=FALSE)
# remove negative salinities
censor(x, salinity < 0)
# variable names with special characters (e.g. spaces) need to be quoted
censor(x, `sigma theta` < 10)
# two conditions that affect the same column can be defined at once
censor(x, salinity < 0 | salinity > 40)
# or one after the other
censor(x, salinity < 0, salinity > 40)
# but when several names appear in a single condition,
# all columns are affected.
censor(x, salinity < 0 | `sigma theta` > 32)
# and the result is therefore different from
censor(x, salinity < 0 , `sigma theta` > 32)
# so, to affect column B based on a condition in column A only,
# use a dummy, always TRUE, condition for B, just so that it appears
censor(x, salinity < 0 & `sigma theta` > -Inf)
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