I do I remove all rows in a dataframe where a certain row meets a string match criteria?
For example:
A,B,C
4,3,Foo
2,3,Bar
7,5,Zap
How would I return a dataframe that excludes all rows where C = Foo:
A,B,C
2,3,Bar
7,5,Zap
asked Jul 11, 2011 at 13:04
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1Related question: Deleting specific rows from a data frame.Joshua Ulrich– Joshua Ulrich2011-07-11 13:13:16 +00:00Commented Jul 11, 2011 at 13:13
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6 Answers
Just use the == with the negation symbol (!). If dtfm is the name of your data.frame:
dtfm[!dtfm$C == "Foo", ]
Or, to move the negation in the comparison:
dtfm[dtfm$C != "Foo", ]
Or, even shorter using subset():
subset(dtfm, C!="Foo")
answered Jul 11, 2011 at 13:09
5 Comments
Sacha Epskamp
Or just
dftm[dtfm$C != "Foo", ] which is the same but slightly more easier to read.
Karsten W.
.. or
subset(dftm, C!="Foo")
Zelbinian
How would you do this with an arbitrary number of conditions? Like if you wanted to remove all rows where "C = Foo" or "C = Bar"?
Luciano Selzer
That would be another question. But the key is to use %in% and !. In your example !(C %in% c("Foo", "Bar"))
Robert Casey
All good feedback. To complete Luciano's suggestion for the non-subset() example, I found that this worked to trim out undesired rows: dtfm <- dtfm[!(dtfm$C %in% c("Foo", "Bar")),] Just be sure not to forget the trailing comma in the [] brackets.
You can use the dplyr package to easily remove those particular rows.
library(dplyr)
df <- filter(df, C != "Foo")
answered Nov 14, 2017 at 9:38
1 Comment
hjhbb
This is going to apply to all columns in "df" right?
I had a column(A) in a data frame with 3 values in it (yes, no, unknown). I wanted to filter only those rows which had a value "yes" for which this is the code, hope this will help you guys as well --
df <- df [(!(df$A=="no") & !(df$A=="unknown")),]
Comments
if you wish to using dplyr, for to remove row "Foo":
df %>%
filter(!C=="Foo")
answered Jan 7, 2021 at 19:59
Comments
I know this has been answered but here is another option:
library (dplyr)
df %>% filter(!c=="foo)
OR
df[!df$c=="foo", ]
1 Comment
Community
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If your exclusion conditions are stored in another data frame you could use rows_delete:
library(dplyr)
removal_df <- data.frame(C = "Foo")
df %>%
rows_delete(removal_df, by = "C")
A B C
1 2 3 Bar
2 7 5 Zap
This is also handy if you have multiple exclusion conditions so you do not have to write out a long filter statement.
Note: rows_delete is only available if you have dplyr >= 1.0.0
