#### Conditional sum of multiple columns based on multiple (other) columns

I have a data frame of the form below:

``````ID <- c(1, 2, 3, 4, 5)
Type1 <- c("A", "", "A", "B", "C")
Count1 <- c(40, NA, 10, 5, 100)
Type2 <- c("D", "", "", "C", "D")
Count2 <- c(5, NA, NA, 30, 5)
Type3 <- c("E", "", "", "D", "")
Count3 <- c(10, NA, NA, 5, NA)
df <- data.frame(ID, Type1, Count1, Type2, Count2, Type3, Count3)
``````

I would like to sum the values in the “Count” columns IF they are of the same “Type”. I.e., if Type1, Type2, or Type3 match, sum the corresponding value in Count1, Count2, and Count3.

Ideally, I could get an output of the form below:

``````Type <- c("A", "B", "C", "D", "E")
n <- c(2, 1, 2, 3, 1)
Total <- c(50, 5, 130, 15, 10)

result <- data.frame(Type, n, Total)
``````

I was able to achieve this using the following code, but it’s quite clunky. I’m sure there is a more elegant method!

``````df1 <- data.frame(Type1, Count1)
df2 <- data.frame(Type2, Count2)
df3 <- data.frame(Type3, Count3)

colnames(df1) <- c("Type", "Count")
colnames(df2) <- c("Type", "Count")
colnames(df3) <- c("Type", "Count")

df_all <- rbind(df1, df2, df3)

result <- df_all %>% group_by(Type) %>%
summarize(num = n(),
total = sum(Count))
``````

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