extended-equality: Extended equality operators

In moodymudskipper/powerjoin: Extensions of 'dplyr' and 'fuzzyjoin' Join Functions

Extended equality operators

Description

⁠%==%⁠ is the bone operator, it works like == but NA %==% 1 is FALSE and NA %==% NA is TRUE. ⁠%in.%⁠ is the a vectorized %in%, that can be seen as a rowwise %in% when applied to data frame columns. These are convenient helpers for fuzzy joins.

Usage

x %==% y

x %in.% y

Arguments

x	A vector
y	A vector for ⁠%==%⁠, a list of vectors for ⁠%in.%⁠

Examples

df1 <- data.frame(key = c("b", "z"))
df2 <- data.frame(key1 = c("a", "b", "c"), key2 = c("x", "y", "z"), val = 1:3)
power_left_join(df1, df2, ~ .x$key %in.% list(.y$key1, .y$key2))

df3 <- data.frame(key1 = c("a", NA))
df4 <- data.frame(key2 = c("a", "b", NA), val = 1:3)

# note the difference
power_inner_join(df3, df4, by = ~ .x$key1 == .y$key2)
power_inner_join(df3, df4, by = ~ .x$key1 %==% .y$key2)

# typically we would only use the conditions above as part of more complex conditions.
# In this precise case they are equivalent to these equi joins
power_inner_join(df3, df4, by = c(key1 = "key2"))
power_inner_join(df3, df4, by = c(key1 = "key2"), na_matches = "never")

moodymudskipper/powerjoin documentation built on Dec. 10, 2024, 12:07 a.m.