I'm trying to solve a tricky R problem that I haven't been able to solve via Googling keywords. Specifically, I'm trying to take a subset one data frame whose values don't appear in another. Here is an example:
> test
number fruit ID1 ID2
item1 "number1" "apples" "22" "33"
item2 "number2" "oranges" "13" "33"
item3 "number3" "peaches" "44" "25"
item4 "number4" "apples" "12" "13"
> test2
number fruit ID1 ID2
item1 "number1" "papayas" "22" "33"
item2 "number2" "oranges" "13" "33"
item3 "number3" "peaches" "441" "25"
item4 "number4" "apples" "123" "13"
item5 "number3" "peaches" "44" "25"
item6 "number4" "apples" "12" "13"
item7 "number1" "apples" "22" "33"
I have two data frames, test and test2, and the goal is to select all entire rows in test2 that don't appear in test, even though some of the values may be the same.
The output I want would look like:
item1 "number1" "papayas" "22" "33"
item2 "number3" "peaches" "441" "25"
item3 "number4" "apples" "123" "13"
There may be an arbitrary amount of rows or columns, but in my specific case, one data frame is a direct subset of the other.
I've used the R subset(), merge() and which() functions extensively, but couldn't figure out how to use these in combination, if it's possible at all, to get what I want.
edit: Here is the R code I used to generate these two tables.
test <- data.frame(c("number1", "apples", 22, 33), c("number2", "oranges", 13, 33),
c("number3", "peaches", 44, 25), c("number4", "apples", 12, 13))
test <- t(test)
rownames(test) = c("item1", "item2", "item3", "item4")
colnames(test) = c("number", "fruit", "ID1", "ID2")
test2 <- data.frame(data.frame(c("number1", "papayas", 22, 33), c("number2", "oranges", 13, 33),
c("number3", "peaches", 441, 25), c("number4", "apples", 123, 13),c("number3", "peaches", 44, 25), c("number4", "apples", 12, 13) ))
test2 <- t(test2)
rownames(test2) = c("item1", "item2", "item3", "item4", "item5", "item6")
colnames(test2) = c("number", "fruit", "ID1", "ID2")
Thanks in advance!
Method 1: Using sqldf() Our query will be sqldf('SELECT * FROM df1 EXCEPT SELECT * FROM df2'). It will exclude all the rows from df1 that are also present in df2 and will return only rows that are only present in df1. Example 1: R.
By using bracket notation on R DataFrame (data.name) we can select rows by column value, by index, by name, by condition e.t.c. You can also use the R base function subset() to get the same results. Besides these, R also provides another function dplyr::filter() to get the rows from the DataFrame.
To remove all rows having NA, we can use na. omit function. For Example, if we have a data frame called df that contains some NA values then we can remove all rows that contains at least one NA by using the command na. omit(df).
Here's another way:
x <- rbind(test2, test)
x[! duplicated(x, fromLast=TRUE) & seq(nrow(x)) <= nrow(test2), ]
# number fruit ID1 ID2
# item1 number1 papayas 22 33
# item3 number3 peaches 441 25
# item4 number4 apples 123 13
Edit: modified to preserve row names.
There are two ways to solve this, using data.table and sqldf
library(data.table)
test<- fread('
item number fruit ID1 ID2
item1 "number1" "apples" "22" "33"
item2 "number2" "oranges" "13" "33"
item3 "number3" "peaches" "44" "25"
item4 "number4" "apples" "12" "13"
')
test2<- fread('
item number fruit ID1 ID2
item1 "number1" "papayas" "22" "33"
item2 "number2" "oranges" "13" "33"
item3 "number3" "peaches" "441" "25"
item4 "number4" "apples" "123" "13"
item5 "number3" "peaches" "44" "25"
item6 "number4" "apples" "12" "13"
item7 "number1" "apples" "22" "33"
')
data.table approach, this enables you to select which columns you want to compare
setkey(test,item,number,fruit,ID1,ID2)
setkey(test2,item,number,fruit,ID1,ID2)
test[!test2]
item number fruit ID1 ID2
1: item1 number1 apples 22 33
2: item3 number3 peaches 44 25
3: item4 number4 apples 12 13
Sql approach
sqldf('select * from test except select * from test2')
item number fruit ID1 ID2
1: item1 number1 apples 22 33
2: item3 number3 peaches 44 25
3: item4 number4 apples 12 13
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