r equivalent of sql update? [duplicate] - sql

Question

This question already has answers here:
Conditional merge/replacement in R
(8 answers)
Closed 5 years ago.
I've looked around and I can't find a simple answer to this.
How do I do what in SQL would be an update table?
For example:
> df1 = data.frame(id=seq(1:3), v1=c("a", "b", NA))
> df1
id v1
1 1 a
2 2 b
3 3 <NA>
> df2 = data.frame(id=seq(1:3), v2=c("z", "y", "c"))
> df2
id v2
1 1 z
2 2 y
3 3 c
How do I update df1 with values from v2 in v1, but only when id matches and when id > 2?
I've looked at data.table, but can't figure out the := syntax, and hoping there is something simple in base R? Desired output would be:
> df1
id v1
1 1 a
2 2 b
3 3 c

Answer 1

SQLite One can use an update in sqlite via sqldf:
library(sqldf)
sqldf(c("update df1
set v1 = (select v2 from df2 where df2.id = df1.id)
where id > 2",
"select * from df1"))
which gives:
id v1
1 1 a
2 2 b
3 3 c
MySQL This works in MySQL:
library(RMySQL)
library(sqldf)
sqldf(c("update df1
left join df2 on (df1.id = df2.id and df1.id > 2)
set df1.v1 = coalesce(df2.v2, df1.v1)",
"select * from df1")
)
giving:
id v1
1 1 a
2 2 b
3 3 c
base R This also works. The first two lines are just to convert v1 and v2 to character and they can be avoided if v1 and v2 were already character:
df1c <- transform(df1, v1 = as.character(v1))
df2c <- transform(df2, v2 = as.character(v2))
transform(df1c, v1 = ifelse(id > 2, df2c[match(id, df2c$id), "v2"], v1))
Update Have incorporated comments and added base R solution.

Answer 2

Updated to work when there are ids present in df1 not in df2, and also if orders are different. This works so long as there is only one id column:
df1 <- data.frame(id=seq(1:5), v1=c("a", "b", NA, NA, NA), stringsAsFactors=F)
df2 <- data.frame(id=seq(1:3), v2=c("z", "y", "c"), stringsAsFactors=F)
df1[df1$id > 2, -1] <- df2[df1$id[df1$id > 2], -1]
df1
Produces:
id v1
1 1 a
2 2 b
3 3 c
4 4 <NA>
5 5 <NA>
Here is a simple solution that works so long as both data frames have the same id set:
df1[df1$id > 2, ] <- df2[df1$id > 2, ]
Produces:
id v1
1 1 a
2 2 b
3 3 c
Big note though, v1 and v2 need to be character, so run this before as they are factor by default:
df1$v1 <- as.character(df1$v1)
df2$v2 <- as.character(df2$v2)
If you need to join on multiple columns or if the ids in one table don't all exist in the other you can use merge or data.table to get both variables on one table, and then construct the new column by combining the columns with ifelse.