CODEWITHSUNDEEP
rdataframeduplicates
Tan
Tan

Reputation: 117

Removing rows of data in R

What's the most reliable way to remove matching Ids from two large data frames in large?

For example, I have a list of participants who do not want to be contacted (n=200). I would like to remove them from my dataset of over 100 variables and 200,000 observations.

This is the list of 200 participants ids that I need to remove from the dataset. 

exclude=read.csv("/home/Project/file/excludeids.csv", header=TRUE, sep=",") 
dataset.exclusion<- dataset[-which(exclude$ParticipantId %in% dataset$ParticipantId  ), ]

Is this the correct command to use?

I don't think this command is doing what I want, because when I verify with the following: length(which(dataset.exclusion$ParticipantId %in% exclusion$ParticipantId)) I don't get 0.

Any insight?

Upvotes: 0

Views: 147

Answers (2)

agstudy
agstudy

Reputation: 121598

You can do this for example:

sample1[!sample1$ParticipantID %in% 
            unique(exclusion$ParticipantId),]

Upvotes: 2

TheComeOnMan
TheComeOnMan

Reputation: 12905

Something like this?

library(data.table)

dataset <- data.table(
a = c(1,2,3,4,5,6),
b = c(11,12,13,14,15,16),
d = c(21,22,23,24,25,26)
)

setkeyv(dataset, c('a','b'))

ToExclude <- data.table(
a = c(1,2,3),
b = c(11,12,13)
)

dataset[!ToExclude]

#    a  b  d
# 1: 4 14 24
# 2: 5 15 25
# 3: 6 16 26

Upvotes: 1

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