I have the following data.frame
, where the multiple X columns (1,2,3... N) are blank:
df1 <- data.frame( name = c("A","B","C"),
X1 = c("","", ""),
Y1 = c("aa","bb","cc"),
Z1 = c("AA","BB","CC"),
X2 = c("","", ""),
Y2 = c("dd","",""),
Z2 = c("AA","",""),
X3 = c("","", ""),
Y3 = c("","","ee"),
Z3 = c("","","CC"))
Another data.frame
contains the value that should be assigned to the X columns accordingly to the combination of values observed in the Ys and Zz columns:
df2 <- data.frame( Y = c("aa","bb","cc","dd","ee"),
Z = c("AA","BB","CC","AA","CC"),
X = c (1,2,3,4,5))
How could I assign the values of X in df1 based on the information I have on df2, So I can get df3?:
df3 <- data.frame( name = c("A","B","C"),
X1 = c("1","2", "3"),
Y1 = c("aa","bb","cc"),
Z1 = c("AA","BB","CC"),
X2 = c("4","", ""),
Y2 = c("dd","",""),
Z2 = c("AA","",""),
X3 = c("","", "5"),
Y3 = c("","","ee"),
Z3 = c("","","CC"))`
Please note that in my real database each name may contain, ,but not necessarily does, several columns (for example, X1,Y1,Z1... X10,Y10,Z10
).
This strategy reshapes your data from a wide format to a long format, does the merge, then reshapes everything back.
# go from wide to long
x1 <- reshape(df1,
varying=Map(function(x) paste0(x, 1:3), c("X","Y","Z")),
v.names=c("X","Y","Z"),
idvar="name",
timevar="time",
direction="long")
x2 <- merge(subset(x1, select=-X), df2, by=c("Y","Z"), all.x=T)
# replace NA values with blanks
x2[is.na(x2$X),"X"] <- ""
# go back to wide
x3 <- reshape(x2,idvar="name",direction="wide", sep="")
and x3
is then
name Y1 Z1 X1 Y2 Z2 X2 Y3 Z3 X3
1 A aa AA 1 dd AA 4
2 B bb BB 2
3 C cc CC 3 ee CC 5
Here you get the columns in a slightly different order but you can easily fix after the fact if necessary.
You can see there is one place i hard-coded 1:3
. If you have more repetitions of columns, you can adjust that vector.
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