EXPERIMENTAL! This function joins two dataframes together by key, and then coalesces any columns that have shared names (i.e. fills in NAs). A utility function primarily used internally within nflverse to help build player IDs
Arguments
- x, y
dataframes. Will be coerced to data.table
- by
keys to join on, as a plain or named character vector
- type
one of "left" (all rows of x and matching rows of y), "inner" (matching rows of x and y), "full" (all rows of x and y)
- ...
other args passed to
merge.data.frame()- by.x, by.y
alternate form of keys to join on - if provided, will override
by.- sort
whether to sort output by the join keys
- incomparables
keys to NOT match on, i.e. NA should not match on NA.
Value
a data.table joining x and y dataframes together, with every column from both x and y and patching NA values in x with those in y.
Examples
x <- data.frame(id1 = c(NA_character_,letters[1:4]), a = c(1,NA,3,NA,5), b = 1:5 * 10)
y <- data.frame(id2 = c(letters[3:11],NA_character_), a = -(1:10), c = 1:10 * 100)
join_coalesce(x,y, by = c("id1"="id2"))
#> Warning: Join `by` keys in x have NAs
#> Join `by` keys in y have NAs
#> id1 a b c
#> 1: a NA 20 NA
#> 2: b 3 30 NA
#> 3: c -1 40 100
#> 4: d 5 50 200
#> 5: <NA> 1 10 NA
join_coalesce(x,y, by.x = "id1", by.y = "id2")
#> Warning: Join `by` keys in x have NAs
#> Join `by` keys in y have NAs
#> id1 a b c
#> 1: a NA 20 NA
#> 2: b 3 30 NA
#> 3: c -1 40 100
#> 4: d 5 50 200
#> 5: <NA> 1 10 NA
join_coalesce(x,y, by = c("id1"="id2"), type = "inner")
#> Warning: Join `by` keys in x have NAs
#> Join `by` keys in y have NAs
#> id1 a b c
#> 1: c -1 40 100
#> 2: d 5 50 200
join_coalesce(x,y, by = c("id1"="id2"), type = "full")
#> Warning: Join `by` keys in x have NAs
#> Join `by` keys in y have NAs
#> id1 a b c
#> 1: a NA 20 NA
#> 2: b 3 30 NA
#> 3: c -1 40 100
#> 4: d 5 50 200
#> 5: e -3 NA 300
#> 6: f -4 NA 400
#> 7: g -5 NA 500
#> 8: h -6 NA 600
#> 9: i -7 NA 700
#> 10: j -8 NA 800
#> 11: k -9 NA 900
#> 12: <NA> 1 10 NA
#> 13: <NA> -10 NA 1000