问题
I'll illustrate my question with an example.
Sample data:
df <- data.frame(ID = c(1, 1, 2, 2, 3, 5), A = c("foo", "bar", "foo", "foo", "bar", "bar"), B = c(1, 5, 7, 23, 54, 202))
df
ID A B
1 1 foo 1
2 1 bar 5
3 2 foo 7
4 2 foo 23
5 3 bar 54
6 5 bar 202
What I want to do is to summarize, by ID, the sum of B and the sum of B when A is "foo". I can do this in a couple steps like:
require(magrittr)
require(dplyr)
df1 <- df %>%
group_by(ID) %>%
summarize(sumB = sum(B))
df2 <- df %>%
filter(A == "foo") %>%
group_by(ID) %>%
summarize(sumBfoo = sum(B))
left_join(df1, df2)
ID sumB sumBfoo
1 1 6 1
2 2 30 30
3 3 54 NA
4 5 202 NA
However, I'm looking for a more elegant/faster way, as I'm dealing with 10gb+ of out-of-memory data in sqlite.
require(sqldf)
my_db <- src_sqlite("my_db.sqlite3", create = T)
df_sqlite <- copy_to(my_db, df)
I thought of using mutate
to define a new Bfoo
column:
df_sqlite %>%
mutate(Bfoo = ifelse(A=="foo", B, 0))
Unfortunately, this doesn't work on the database end of things.
Error in sqliteExecStatement(conn, statement, ...) :
RS-DBI driver: (error in statement: no such function: IFELSE)
回答1:
You can do both sums in a single dplyr
statement:
df1 <- df %>%
group_by(ID) %>%
summarize(sumB = sum(B),
sumBfoo = sum(B[A=="foo"]))
回答2:
Writing up @hadley's comment as an answer
df_sqlite %>%
group_by(ID) %>%
mutate(Bfoo = if(A=="foo") B else 0) %>%
summarize(sumB = sum(B),
sumBfoo = sum(Bfoo)) %>%
collect
回答3:
If you want to do counting instead of summarizing, then the answer is somewhat different. The change in code is small, especially in the conditional counting part.
df1 <- df %>%
group_by(ID) %>%
summarize(countB = n(),
countBfoo = sum(A=="foo"))
df1
Source: local data frame [4 x 3]
ID countB countBfoo
1 1 2 1
2 2 2 2
3 3 1 0
4 5 1 0
回答4:
If you wanted to count the rows, instead of summing them, can you pass a variable to the function:
df1 <- df %>%
group_by(ID) %>%
summarize(RowCountB = n(),
RowCountBfoo = n(A=="foo"))
I get an error both with n()
and nrow()
.
来源:https://stackoverflow.com/questions/23528862/summarize-with-conditions-in-dplyr