This function "defines a dyadic operator that will behave differently than
the "+" operator with regards to missing values". (Quote by 42- in Source
1 below). In this case, add `x`

and `y`

so that `NA`

is ignored
when `x`

is a number and `x = NA`

when `x = 0`

.

1 | ```
x %+na% y
``` |

`x` |
numeric vector that does not contain any |

`y` |
numeric vector which contains at least one |

numeric vector resulting from the `sum`

of `x`

and `y`

Using ':=' in data.table to sum the values of two columns in R, ignoring NAs - Stack Overflow answered by 42- on Oct 28 2012. See http://stackoverflow.com/questions/13106645/using-in-data-table-to-sum-the-values-of-two-columns-in-r-ignoring-nas.

R - merge unequal regular (15 min intervals) and irregular time series within 10 minutes - Stack Overflow asked by iembry on Jan 12 2015 and edited by iembry on Feb 2 2015. See http://stackoverflow.com/questions/27930548/r-data-table-dyadic-operator-and-summing-duplicate-rows-based-on-time-se.

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 27 28 29 30 31 | ```
library(ie2misc)
a <- 1:10
b <- c(98:106, NA)
a %+na% b
# Note that if the vector with the NA value(s) is first, then the additive
# result will still be an NA value(s)
b %+na% a
a1 <- 1:12
b1 <- c(98:106, rep(NA, 3))
a1 %+na% b1
# using a matrix of the numeric vectors a and b
mat1 <- matrix(data = c(a, b), nrow = length(b), ncol = 2, byrow = FALSE,
dimnames = list(c(rep("", length(b))), c("a", "b")))
mat1[, 1] %+na% mat1[, 2]
# using a data.frame of the numeric vectors a and b
df1 <- data.frame(a, b)
df1[, 1] %+na% df1[, 2]
# using a data.table of the numeric vectors a and b
df2 <- data.table(a, b)
df2[, 1, with = FALSE][[1]] %+na% df2[, 2, with = FALSE][[1]]
``` |

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