R - Create a new variable where each observation depends on another table and other variables in the data frame

Question

I have the two following tables:

df <- data.frame(eth = c(\"A\",\"B\",\"B\",\"A\",\"C\"),ZIP1 = c(1,1,2,3,5))
Inc <- data.frame(ZIP2 = c(1,2,3,4,5,6,7)         


        

Answer 1

Another option:

library(dplyr)
library(tidyr)
Inc %>%
  gather(eth, value, -ZIP2) %>%
  left_join(df, ., by = c("eth", "ZIP1" = "ZIP2"))

Answer 2

my solution(which maybe seems awkward)

for (i in 1:length(df$eth)) {
    df$Inc[i] <- Inc[as.character(df$eth[i])][df$ZIP[i],]
}

Answer 3

What about this?

library(reshape2)
merge(df, melt(Inc, id="ZIP2"), by.x = c("ZIP1", "eth"), by.y = c("ZIP2", "variable"))
  ZIP1 eth value
1    1   A    56
2    1   B    49
3    2   B    10
4    3   A    43
5    5   C    17

Answer 4

Sure, it can be done in data.table:

library(data.table)
setDT(df)

df[ melt(Inc, id.var="ZIP2", variable.name="eth", value.name="Inc"), 
  Inc := i.Inc
, on=c(ZIP1 = "ZIP2","eth") ]

The syntax for this "merge-assign" operation is X[i, Xcol := expression, on=merge_cols].

You can run the i = melt(Inc, id.var="ZIP", variable.name="eth", value.name="Inc") part on its own to see how it works. Inside the merge, columns from i can be referred to with i.* prefixes.

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Alternately...

setDT(df)
setDT(Inc)
df[, Inc := Inc[.(ZIP1), eth, on="ZIP2", with=FALSE], by=eth]

This is built on a similar idea. The package vignettes are a good place to start for this sort of syntax.

Answer 5

We can use row/column indexing

df$Inc <- Inc[cbind(match(df$ZIP1, Inc$ZIP2), match(df$eth, colnames(Inc)))]

df
#  eth ZIP1 Inc
#1   A    1  56
#2   B    1  49
#3   B    2  10
#4   A    3  43
#5   C    5  17