Sum of hybrid data frames depending on multiple conditions in R - r

Question

This is a more complex follow-up to my previous question. The answer there was to use a matrix, but that doesn't work with data frames having values of different modes.
I want to combine data frames of different sizes, with character and integer columns, and calculate their sum depending on multiple conditions.
Conditions
sums are only calculated for those rows that have a matching "Name"-value
sums are calculated for matching column names only
if a cell in df4 is not 0 and not NA, the sum should be df3 + df4
else the sum should be df1 + df2 + df3
Example
> df1 <- data.frame(Name=c("Joe","Ann","Lee","Dan"), "1"=c(0,1,5,2), "2"=c(3,1,0,0), "3"=c(2,0,2,2), "4"=c(2,1,3,4))
> df1
Name X1 X2 X3 X4
1 Joe 0 3 2 2
2 Ann 1 1 0 1
3 Lee 5 0 2 3
4 Dan 2 0 2 4
> df2 <- data.frame(Name=c("Joe","Ann","Ken"), "1"=c(3,4,1), "2"=c(2,3,0), "3"=c(2,4,3))
> df2
Name X1 X2 X3
1 Joe 3 2 2
2 Ann 4 3 4
3 Ken 1 0 3
> df3 <- data.frame(Name=c("Lee","Ben"), "1"=c(1,3), "2"=c(3,4), "3"=c(4,3))
> df3
Name X1 X2 X3
1 Lee 1 3 4
2 Ben 3 4 3
The condition depends on this frame:
> df4 <- data.frame(Name=c("Lee","Ann","Dan"), "1"=c(6,0,NA), "2"=c(0,0,4), "3"=c(0,NA,0))
> df4
Name X1 X2 X3
1 Lee 6 0 0
2 Ann 0 0 NA
3 Dan NA 4 0
With the above examples, this is the expected result (* values depend on df4):
> dfsum
Name X1 X2 X3 X4
1 Joe 3 5 4 2
2 Ann 5 4 4 1
3 Lee 7* 3 6 3
4 Dan 2 4* 2 4
5 Ken 1 0 3 NA
6 Ben 3 4 3 NA
Possible steps?
First expand df1, df2, df3, df4 to 5 columns and 6 rows, fill missing data with NA.
Then for each data frame:
sort rows by "Name"
separate "Name" column from "X1"..."X4"
transform "X1"..."X4" columns to matrix
calculate sums of the matrices like in the answer to my other question but with the additional condition 1
transform result matrix to data frame
cbind the "Name" column with the result data frame
How can this be done in R?
Solution
#Ricardo Saporta's solution works with little changes:
Add , padValue=NA) in the four addCols().
As answered here, replace the definitions of sumD3D4 and dtsum with:
plus <- function(x) {
if(all(is.na(x))){
c(x[0],NA)} else {
sum(x,na.rm = TRUE)}
}
sumD3D4 <- setkey(rbind(dt3, dt4)[,lapply(.SD, plus), by = Name], "Name")
dtsum <- setkey(rbind(dt1, dt2, dt3)[, lapply(.SD, plus), by=Name], "Name")

Answer 1

If you use data.table instead of data.frame, you could use its by=xxxx feature, to add by name.
The code below should give you your expected results.
Please note that I am padding the data.tables with extra empty columns. However, we compute condTrue prior to then.
library(data.table)
dt1 <- data.table(df1)
dt2 <- data.table(df2)
dt3 <- data.table(df3)
dt4 <- data.table(df4)
# make sure all dt's have the same columns
#-----------------------------------------#
# identify which dt4 satisfy the condition
condTrue <- as.data.table(which(!(is.na(dt4) | dt4==0), arr.ind=TRUE))
# ignore column "Name" from dt4
condTrue <- condTrue[col>1]
# convert from (row, col) index to ("Name", columnName)
condTrue <- data.table(Name=dt4[condTrue$row, Name], colm=names(dt4)[condTrue$col], key="Name")
# First make a list of all the unique column names
allColumnNames <- unique(c(names(dt1), names(dt2), names(dt3), names(dt4)))
# add columns as necessary, using addCols (definted below)
addCols(dt1, allColumnNames)
addCols(dt2, allColumnNames)
addCols(dt3, allColumnNames)
addCols(dt4, allColumnNames)
sumD3D4 <- setkey(rbind(dt3, dt4)[, lapply(.SD, sum), by=Name], "Name")
dtsum <- setkey(rbind(dt1, dt2, dt3)[, lapply(.SD, sum), by=Name], "Name")
for (Nam in condTrue$Name) {
colsRepl <- condTrue[.(Nam)]$colm
valsRepl <- unlist(sumD3D4[.(Nam), c(colsRepl), with=FALSE])
dtsum[.(Nam), c(colsRepl) := as.list(valsRepl)]
}
dtsum
# Name 1 2 3 4
# 1: Ann 5 4 4 1
# 2: Ben 3 4 3 0
# 3: Dan 2 4 2 4
# 4: Joe 3 5 4 2
# 5: Ken 1 0 3 0
# 6: Lee 7 3 6 3
addCols <- function(x, cols, padValue=0) {
# adds to x any columns that are in cols but not in x
# Returns TRUE if columns were added
# FALSE if no columns added
colsMissing <- setdiff(cols, names(x))
# grab the actual DT name that was passed to function
dtName <- as.character(match.call()[2])
if (length(colsMissing)) {
get(dtName, envir=parent.frame(1))[, c(colsMissing) := padValue]
return(TRUE)
}
return(FALSE)
}