I am attempting to create a function that will allow a user to define an infinite number of columns and apply matching filters to those columns.
df <- data.frame(a=1:10, b=round(runif(10)), c=round(runif(10)))
|a| b|c|
|1| 1|1|
|2| 0|0|
|3| 0|1|
|4| 1|0|
|5| 1|0|
|6| 1|0|
|7| 1|1|
|8| 1|1|
|9| 1|0|
|10|1|1|
I would like the user to be able to filter the data based off either column, and apply different filters to each column. I know the following does not work. But this would be the general idea.
test <- function(df, fCol, fParam){
df %>% filter(fCol[1] %in% fParam[1] | fCol[2] %in% fParam[2])
}
test(df, c("b","c"),c(1,0)
# Which I would want it to return
|a|b|c|
|4|1|0|
|5|1|0|
|6|1|0|
|9|1|0|
The issue that I run into is that I won't know how many columns the user will want to filter, nor will I know the column names.
Any help at all would be greatly appreciated. Please ask questions if you have them. I tried my best to give a reprex.
I believe this should satisfy what you want
library(tidyr)
library(dplyr)
test <- function(df,
fCol,
fParam,
match_type = "any")
{
if(!is.element(match_type, c("any","all"))|length(match_type)!=1){
stop()
}
df <- df %>% ungroup() %>%
mutate(..id..=1:n())
meta <- data.frame(fCol=fCol,fParam=fParam)
logi <- df %>%
select("..id..",fCol) %>%
gather(key = "key", value = "value", -..id..) %>%
left_join(., y = meta, by = c("key"="fCol")) %>%
mutate(match = value==fParam) %>%
select(-key,-value, -fParam) %>%
group_by_at(setdiff(names(.),"match")) %>%
summarise(match = ifelse(match_type%in%"any",any(match), all(match)))
df2 <- left_join(df, logi, by = intersect(colnames(df),colnames(logi))) %>%
filter(match)%>%
select(-match, -..id..)
return(df2)
}
df <- data.frame(a=1:10, b=round(runif(10)), c=round(runif(10)))
df
# a b c
#1 1 0 1
#2 2 1 0
#3 3 0 0
#4 4 0 1
#5 5 0 1
#6 6 0 1
#7 7 1 0
#8 8 1 1
#9 9 1 0
#10 10 1 0
#use "any" to do an | match
test(df, c("b","c"),c(1,0), match_type = "any")
# a b c
#1 2 1 0
#2 3 0 0
#3 7 1 0
#4 8 1 1
#5 9 1 0
#6 10 1 0
#use "all" to do an & match
test(df, c("b","c"),c(1,0), match_type = "all")
# a b c
#1 2 1 0
#2 7 1 0
#3 9 1 0
#4 10 1 0
You can also specify the same colname for fCol multiple times if you want to match multiple values
test(df, c("b","b"),c(1,0)) #matches everything but you get the point