Reputation: 3805
dat <- data.frame(id = c(0, 0, 01, 02, 03, 011, 012, 013, 0111, 0112, 0113),
x1 = rnorm(11),
x2 = rnorm(11),
x3 = rnorm(11))
my.df <- data.frame(id = 0, id1 = 01, id2 = 011, id3 = 0111, some.column = 'xyz')
I want to filter rows from dat
using following conditions:
If my.df$id3
is present in dat$id
, filter dat$id == my.df$id3
, if not
check if my.df$id2
is present and filter dat$id == my.df$id2
, if not,
check if my.df$id1
is present and filter dat$id == my.df$id1
, if not
simply filter dat$id == my.df$id
dat %>%
dplyr::filter(ifelse(my.df$id3 %in% id, id == my.df$id3,
ifelse(my.df$id2 %in% id, id == my.df$id2,
ifelse(my.df$id1 %in% id, id == my.df$id1, id == my.df$id))))
It returns null rows.
Upvotes: 0
Views: 78
Reputation: 389265
You can extract the column values in my.df
the required order to create order_vec
, filter values present in it, arrange
the values and select the first row.
library(dplyr)
order_vec <- unlist(my.df[c(paste0('id', 3:1), 'id')])
dat %>%
filter(id %in% order_vec) %>%
arrange(match(id, order_vec)) %>%
slice(1L)
# id x1 x2 x3
#1 111 1.5 0.872 0.848
Upvotes: 0
Reputation: 18581
Is this what you are looking for or how does your expected output look like? In the example below the filter id == my.df$id3
is applied if my.df$id3
is present in dat$id
. Since this is the case, this filter leaves only one row of your original data.
library(dplyr)
dat <- data.frame(id = c(0, 0, 01, 02, 03, 011, 012, 013, 0111, 0112, 0113),
x1 = rnorm(11),
x2 = rnorm(11),
x3 = rnorm(11))
my.df <- data.frame(id = 0, id1 = 01, id2 = 011, id3 = 0111, some.column = 'xyz')
dat %>%
dplyr::filter(if (my.df$id3 %in% id) {
id == my.df$id3
} else if (my.df$id2 %in% id) {
id == my.df$id2
} else if (my.df$id1 %in% id) {
id == my.df$id1 })
#> id x1 x2 x3
#> 1 111 0.3771992 -0.5073165 -0.3555985
Created on 2020-07-13 by the reprex package (v0.3.0)
Upvotes: 1