Make lookup table from data.frame
I have data.frame
one that has only one unique value not NA
in all columns except one that only has one NA
.
data <- data.frame(A = c("egg", "egg"), B = c(NA, "bacon"), C = c("ham", "ham"), D = c(NA, NA))
How can I use it to create a matching table of the form below?
lookup <- make_lookup(key=unique_values(data), value=names(data))
lookup[["egg"]] # returns "A"
lookup[["bacon"]] # returns "B"
lookup[["ham"]] # returns "C"
lookup[["NA"]] # returns "D"
EDIT
Based on Frank's answer below, I'm trying to get my lookup table to reference multiple values.
keys <- lapply(data, function(x) if(is.factor(x)) levels(x) else "bacon")
vals <- names(data)
keys
$A
[1] "egg"
$B
[1] "bacon"
$C
[1] "ham"
$D
[1] "bacon"
Vals
[1] "A" "B" "C" "D"
tapply (vals, keys, c)
Error in tapply(vals, keys, c) : arguments must have same length
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Here's one way. Search is a vector:
keys <- sapply(data,function(x)if(is.factor(x))levels(x)else "NA")
vals <- names(data)
lookup <- setNames(vals,keys)
I replaced NA
with "NA"
since I couldn't figure out how to use the first one.
The syntax lookup[["egg"]]
works, but also lookup["egg"]
. Reverse Search rlookup <- keys
is available in the same way: rlookup["A"]
.
For keys with multiple values. If keys can map to a vector of values, use
lookup <- tapply(vals,keys,c)
Try it with keys <- sapply(data,function(x)if(is.factor(x))levels(x)else "bacon")
and vals
as above, for example (as in OP's comment, below). Now the search - a list, so access to them is only possible with double brackets: lookup[["bacon"]]
. The reverse lookup still works.
For general column classes. If the columns data
are not all factors, the conditions if
/ else
will need to be modified or summarized. Here is a version of @akrun's generalized solution from the comments:
keys <- sapply(data,function(x)c(unique(as.character(x)[!is.na(x)]),"NA")[1])
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