remove duplicate values based on 2 columns

Question

I want to remove duplicate values based upon matches in 2 columns in a dataframe, v2 & v4 must match between rows to be removed.

> df

   v1  v2  v3   v4  v5
1  7   1   A  100  98 
2  7   2   A  100  97
3  8   1   C   NA  80
4  8   1   C   78  75
5  8   1   C   78  62
6  9   3   C   75  75

For a result of

> df

   v1  v2  v3   v4  v5
1  7   1   A  100  98 
2  8   1   C   NA  80
3  8   1   C   78  75
4  9   3   C   75  75

I know I want something like:

df[!duplicated(df[v2] && df[v4]),]

but this doesn't work.

This question is specifically about dataframes, for those who have a data.table, see Filtering out duplicated/non-unique rows in data.table.

In the example you are providing, it seems that keys are `v1` and `v4` (the first column actually represents the row names). Try `df[!duplicated(df[,c("v1","v4")]),]`. — nicola, Jan 20 '16 at 20:24

score 63 · Accepted Answer · edited Jan 21 '16 at 00:20

63

This will give you the desired result:

df [!duplicated(df[c(1,4)]),]

edited Jan 21 '16 at 00:20

Unheilig

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answered Jan 20 '16 at 20:14

Wyldsoul

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Hi what if you want to use its column name (e.g. v1 & v4) instead of the column numbers 1, 4 ? – Bustergun Apr 29 '20 at 21:22
8

@Bustergun you could use df[!duplicated(df[c("V1","V4")]),] – Michael Ryan Dec 02 '20 at 23:17

remove duplicate values based on 2 columns

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