You should use either indexing or the subset function. For example :
R> df df
x y z u
1 1 2 3 4
2 2 3 4 5
3 3 4 5 6
4 4 5 6 7
5 5 6 7 8Then you can use the which function and the - operator in column indexation :
R> df[ , -which(names(df) %in% c("z","u"))]
x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6Or, much simpler, use the select argument of the subset function : you can then use the - operator directly on a vector of column names, and you can even omit the quotes around the names !
R> subset(df, select=-c(z,u))
x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6Note that you can also select the columns you want instead of dropping the others :
R> df[ , c("x","y")]
x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6
R> subset(d服务器托管网f, select=c(x,y))
x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6
===============================Simple R functions to keep or remove data frame columns
This function removes columns from a data frame by name:
removeCols
This function keeps columns of a data frame by name:
keepCols return(服务器托管网data[,names(data) %in% cols])}
or just one function
colKeepRemove if(remove == 1){ return(data[,!names(data) %in% cols]) }else { return(data[,!names(data) %in% cols]) }}
===============================data(mtcars)
mtcars[mtcars[, "mpg"]>25, ]
mpg cyl disp hp drat wt qsec vs am gear carb
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
mtcars[mtcars$mpg>25, ]
mpg cyl disp hp drat wt qsec vs am gear carb
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
subset(mtcars, mpg>25)
mpg cyl disp hp drat wt qsec vs am gear carb
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2===============================
REF:
http://stackoverflow.com/questions/4605206/drop-columns-r-data-frame
http://stackoverflow.com/questions/5234117/how-to-drop-columns-by-name-in-a-data-frame
http://ewens.caltech.edu/2011/05/17/simple-r-functions-to-keep-or-remove-data-frame-columns/服务器托管，北京服务器托管，服务器租用 http://www.fwqtg.net
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