I would like to know if there is an elegant and concise way to do conditional filtering with data.table.
My aim is the following:
if condition 1 is met, filter based on condition 2.
For instance, in the case of the iris dataset,
how can I drop the observations among Species=="setosa" where Sepal.Length<5.5, while keeping all observations with Sepal.Length<5.5 for other species?
I know how to do this in steps, but I wonder if there is a better way to do it in a single liner
# this is how I would do it in steps.
data("iris")
# first only select observations in setosa I am interested in keeping
iris1<- setDT(iris)[Sepal.Length>=5.5&Species=="setosa"]
# second, drop all of setosa observations.
iris2<- setDT(iris)[Species!="setosa"]
# join data,
iris_final<-full_join(iris1,iris2)
head(iris_final)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1: 5.8 4.0 1.2 0.2 setosa
2: 5.7 4.4 1.5 0.4 setosa
3: 5.7 3.8 1.7 0.3 setosa
4: 5.5 4.2 1.4 0.2 setosa
5: 5.5 3.5 1.3 0.2 setosa # only keeping setosa with Sepal.Length>=5.5. Note that for other species, Sepal.Length can be <5.5
6: 7.0 3.2 4.7 1.4 versicolor
is there a more concise and elegant way of doing this?
>Solution :
Is something like the following what you are looking for? It is not very clear what you want.
library(data.table)
dt <- data.table(iris)
dt[Sepal.Length >= 5.5 & Species == "setosa" | Species != "setosa"]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1: 5.8 4.0 1.2 0.2 setosa
#> 2: 5.7 4.4 1.5 0.4 setosa
#> 3: 5.7 3.8 1.7 0.3 setosa
#> 4: 5.5 4.2 1.4 0.2 setosa
#> 5: 5.5 3.5 1.3 0.2 setosa
#> ---
#> 101: 6.7 3.0 5.2 2.3 virginica
#> 102: 6.3 2.5 5.0 1.9 virginica
#> 103: 6.5 3.0 5.2 2.0 virginica
#> 104: 6.2 3.4 5.4 2.3 virginica
#> 105: 5.9 3.0 5.1 1.8 virginica