So I have a data frame.
In which some specific variables may have the value of 0. But I want to delete the row only if the value of zero shows up on 3 or 4 of these specific variables.
Thank you
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1trry `df1 %>% filter_at(yourvars, all_vars(. != 0))` – akrun Mar 06 '19 at 11:59
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1Please edit your question according to [this](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example). – NelsonGon Mar 06 '19 at 11:59
1 Answers
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It can be done with filter_at by specifying the columns of interest
library(dplyr)
df1 %>%
filter_at(vars(col1, col2), all_vars(. != 0))
data
df1 <- data.frame(col1 = c(0, 1, 2, 3), col2 = c(1, 0, 2, 4), col3 = c(1, 1, 0, 0))
akrun
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So I have these variables: login_count : whitch is integer text_length: might be 1 to thousands assignment: 1 to hundreds meaning he had an assignment mindmap_length: also 1 to thousands ( Letter counting) activity: also integer 1 to hunders So basicaly a user to have values >0 on these values the value login must be at least 1 meaning he loged in to the system and wrote something Then also Assignment has to have a value meaning the assignment he had to do But login and assignment might be 1 and the others might be 0 and I still need to delete the row. So how i do if else here? – Alex Rika Mar 06 '19 at 14:58
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@AlexRika I showed a reproducible example based on your description. Sorry, it is not clear to me without a reproducible example – akrun Mar 06 '19 at 15:00
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@AlexRika Please edit your post with a small example and your expected output. – akrun Mar 06 '19 at 15:03