How to merge and sum two data frames - r

Question

Here is my issue:
df1 <- data.frame(x = 1:5, y = 2:6, z = 3:7)
rownames(df1) <- LETTERS[1:5]
df1
x y z
A 1 2 3
B 2 3 4
C 3 4 5
D 4 5 6
E 5 6 7
df2 <- data.frame(x = 1:5, y = 2:6, z = 3:7)
rownames(df2) <- LETTERS[3:7]
df2
x y z
C 1 2 3
D 2 3 4
E 3 4 5
F 4 5 6
G 5 6 7
what I wanted is:
x y z
A 1 2 3
B 2 3 4
C 4 6 8
D 6 8 10
E 8 10 12
F 4 5 6
G 5 6 7
where duplicated rows were added up by same variable.

Answer 1

A solution with base R:
# create a new variable from the rownames
df1$rn <- rownames(df1)
df2$rn <- rownames(df2)
# bind the two dataframes together by row and aggregate
res <- aggregate(cbind(x,y,z) ~ rn, rbind(df1,df2), sum)
# or (thx to #alistaire for reminding me):
res <- aggregate(. ~ rn, rbind(df1,df2), sum)
# assign the rownames again
rownames(res) <- res$rn
# get rid of the 'rn' column
res <- res[, -1]
which gives:
> res
x y z
A 1 2 3
B 2 3 4
C 4 6 8
D 6 8 10
E 8 10 12
F 4 5 6
G 5 6 7

Answer 2

With dplyr,
library(dplyr)
# add rownames as a column in each data.frame and bind rows
bind_rows(df1 %>% add_rownames(),
df2 %>% add_rownames()) %>%
# evaluate following calls for each value in the rowname column
group_by(rowname) %>%
# add all non-grouping variables
summarise_all(sum)
## # A tibble: 7 x 4
## rowname x y z
## <chr> <int> <int> <int>
## 1 A 1 2 3
## 2 B 2 3 4
## 3 C 4 6 8
## 4 D 6 8 10
## 5 E 8 10 12
## 6 F 4 5 6
## 7 G 5 6 7

Answer 3

could also vectorize the operation turning the dfs to matrices:
result_df <- as.data.frame(as.matrix(df1) + as.matrix(df2))

Answer 4

This might need some teaking to get the rownames logic working on a longer example:
dfr <-rbind(df1,df2)
do.call(rbind, lapply( split(dfr, sapply(rownames(dfr),substr,1,1)), colSums))
x y z
A 1 2 3
B 2 3 4
C 4 6 8
D 6 8 10
E 8 10 12
F 4 5 6
G 5 6 7
If the rownames could all be assumed to be alpha characters a gsub solution should be easy.

Answer 5

An alternative is to melt the data and cast it. At first we set the row names to the last column of both data frames thanks to #Jaap
df1$rn <- rownames(df1)
df2$rn <- rownames(df2)
Then we melt the data based on the name
melt(list(df1, df2), id.vars = "rn")
Then we use dcast with mget function which is used to retrieve multiple variables at once.
mydf<- dcast(melt(mget(ls(pattern = "df\\d+")), id.vars = "rn"),
rn ~ variable, value.var = "value", fun.aggregate = sum)
rownames(mydf) <- mydf$rn
# get rid of the 'rn' column
mydf <- mydf[, -1]
> mydf
# x y z
#A 1 2 3
#B 2 3 4
#C 4 6 8
#D 6 8 10
#E 8 10 12
#F 4 5 6
#G 5 6 7