CODEWITHSUNDEEP
rdataframe
deemel
deemel

Reputation: 1036

R remove rows containing a certain value

So it got a csv I'm reading into an R dataframe, it looks like this

clientx,clienty,screenx,screeny
481,855,481,847
481,784,481,847
481,784,481,847
879,292,879,355

First line is of course the header. So we have 4 columns with numeric data in it, ranging from 1 to 4 digits. There are no negative numbers in the set except -1 which marks a missing value. I want to remove every row that contains a -1 in any of the 4 columns.

Thanks in advance for the help

Upvotes: 3

Views: 23478

Answers (2)

DrDom
DrDom

Reputation: 4133

The direct way:

df <- df[!apply(df, 1, function(x) {any(x == -1)}),]

UPDATE: this approach will fail if data.frame contains character columns because apply implicitly converts data.frame to matrix (which contains data of only one type) and character type has a priority over numeric types thus data.frame will be converted into character matrix.

Or replace -1 with NA and then use na.omit:

df[df==-1] <- NA
df <- na.omit(df)

These should work, I didn't check. Please always try to provide a reproducible example to illustrate your question.

Upvotes: 8

Andrie
Andrie

Reputation: 179558

Your most efficient way will be to use the na.strings argument of read.csv() to code all -1 values as NA, then to drop incomplete cases.

Step 1: set na.strings=-1 in read.csv():

x <- read.csv(text="
clientx,clienty,screenx,screeny
481,855,481,847
481,784,481,847
481,784,481,847
-1,292,879,355", header=TRUE, na.strings=-1)

x
clientx clienty screenx screeny
1     481     855     481     847
2     481     784     481     847
3     481     784     481     847
4      NA     292     879     355

Step 2: Now use complete.cases or na.omit:

x[complete.cases(x), ]
  clientx clienty screenx screeny
1     481     855     481     847
2     481     784     481     847
3     481     784     481     847

na.omit(x)
  clientx clienty screenx screeny
1     481     855     481     847
2     481     784     481     847
3     481     784     481     847

Upvotes: 9

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