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I am in the midst of dealing with a big data project where I want to filter one column from highlighting with another.

For example, I want to showcase house 1, and as a result of that, I want to compare House 1 with other values from other URBAN houses, not all houses.

table <- data.frame( house=paste("House", 1:15), category = c("Urban", "Rural", "Suburban") ) table # house category # 1 House 1 Urban # 2 House 2 Rural # 3 House 3 Suburban # 4 House 4 Urban # 5 House 5 Rural # 6 House 6 Suburban # 7 House 7 Urban # 8 House 8 Rural # 9 House 9 Suburban # 10 House 10 Urban # 11 House 11 Rural # 12 House 12 Suburban # 13 House 13 Urban # 14 House 14 Rural # 15 House 15 Suburban

I tried to give this a go, but it is not working for me...

table %>% filter(house == house1) %>% filter(category == table$house)

I want the output to look like this...

# house category # 1 House 1 Urban # 2 House 4 Urban # 3 House 7 Urban # 4 House 10 Urban # 5 House 13 Urban

Any suggestions are truly appreciated.

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4 Answers 4

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2

Maybe you can try the base R code below

subset(df,category == category[house=="House1"])

or dplyr option

df %>% filter(category == category[house == "House1"])

which gives

 house category 1 House1 Urban 3 House3 Urban 5 House5 Urban 12 House12 Urban 13 House13 Urban 14 House14 Urban

dummy data

df <- structure(list(house = c("House1", "House2", "House3", "House4", "House5", "House6", "House7", "House8", "House9", "House10", "House11", "House12", "House13", "House14", "House15"), category = c("Urban", "Suburban", "Urban", "Rural", "Urban", "Suburban", "Suburban", "Rural", "Rural", "Suburban", "Suburban", "Urban", "Urban", "Urban", "Rural")), class = "data.frame", row.names = c(NA, -15L))
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That's the answer I'm looking for! Thank you so much.
1

Using dplyr you might do something like this

table %>% filter(category == filter(table, house=="House 1") %>% pull(category))

Basically just a sub-query to find the category of House 1.

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0

Try

table %>% filter(category == "Urban")

Remember you need to use quotes " " in your filter statements.

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You can also use match which will return index of first match and you can get corresponding category from it.

subset(table, category == category[match('House 1', house)]) house category 1 House 1 Urban 4 House 4 Urban 7 House 7 Urban 10 House 10 Urban 13 House 13 Urban

Same code with filter if you want to use dplyr :

dplyr::filter(table, category == category[match('House 1', house)])
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