Delete rows from dataframe based on column value in R

Question

Sample_ID<-c("a1","a2","a3","a4","a5","a6")
Heart_attack<-c("1", "0", "1", "1", "0", "2")
DF<-data.frame(Sample_ID,Heart_attack)

I want to exclude from my data frame, all the samples having "0" in Heart_attack.How to do that?

Chris Ruehlemann · Accepted Answer · 2020-07-01 16:45:26Z

1

If you do str(DF) you will see that Heart_attack is of type factor. Therefore you need to drop the 0 level:

df2 <- droplevels(DF[-which(DF$Heart_attack == "0"), ])
df2
  Sample_ID Heart_attack
1        a1            1
3        a3            1
4        a4            1
6        a6            2

To check whether the 0level really has disappeared, you can use table:

table(df2$Heart_attack)
1 2 
3 1

edited Jul 1, 2020 at 16:45

answered Jul 1, 2020 at 16:36

Chris Ruehlemann

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Matt · Accepted Answer · 2020-07-01 16:46:48Z

0

Here is a dplyr solution:

  DF <- DF %>% 
  filter(Heart_attack != 0) %>% 
  droplevels()

edited Jul 1, 2020 at 16:46

answered Jul 1, 2020 at 16:33

Matt

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2 Comments

Chris Ruehlemann Over a year ago

The level 0is still there even after the subset operation. Check out table(DF)(after the subset): table(DF$Heart_attack) 0 1 2 0 3 1 This goes for both the base R and the dplyr solution!

Matt Over a year ago

Thanks! I didn't realize that. Updated the dplyr solution with droplevels()

akrun · Accepted Answer · 2020-07-01 18:37:22Z

0

An option with subset from base R

df2 <-  droplevels(subset(DF, as.logical(as.integer(Heart_attack))))

answered Jul 1, 2020 at 18:37

akrun

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