Hello List,
Last time, Arun's following solution worked to create 3 new columns (1,3,5).
Now how would I tweak this function to create corresponding (additional)
columns (7,8,9) of mode factor (levels = 1,2,3,4,5)?
Thanks for your continued support.
Pradip
####### cut and paste from the reproducible example
CutQuintiles <- function( x) {
cut (x,quantile (x, (0:5/5)),include.lowest=TRUE)
}
#apply the CutQuintile () on every odd-numbered columns of the "test1" data
frame
test1$newcols <- sapply(test1 [, seq (1,6,2)], CutQuintiles)
# name 3 new columns based on the odd-numbered columns
names(test1$newcols) <- paste (names(test1 [, seq (1,6,2)]), "_cat")
###### Reproducible Example
test1 <- read.table (text=
"State,ObtMj_P,ObtMj_SE,ExpPrevMed_P,ExpPrevMed_SE,ParMon_P,ParMon_SE
Alabama,49.60,1.37,80.00,0.91,12.10,0.68
Alaska,55.00,1.41,81.80,1.08,12.40,0.90
Arizona,52.50,1.56,79.60,1.20,15.80,1.08
Arkansas,50.50,1.22,78.00,0.78,12.80,0.72
California,51.10,0.65,80.50,0.53,13.00,0.41
Colorado,55.10,1.26,81.70,1.03,12.10,0.72
Connecticut,56.30,1.28,85.00,0.93,14.60,0.77
Delaware,53.60,1.30,79.50,1.04,14.70,0.97
District of Columbia,53.50,1.22,76.20,1.03,14.30,1.13
Florida,52.70,0.67,78.90,0.52,14.10,0.45
Georgia,52.50,1.15,79.30,1.02,15.90,0.98
Hawaii,49.40,1.33,83.80,1.12,16.00,1.06
Idaho,48.30,1.23,82.40,0.99,11.90,0.74
Illinois,52.70,0.63,81.00,0.46,13.60,0.40
Indiana,49.60,1.16,80.90,0.91,12.60,0.82
Iowa,46.30,1.37,82.10,1.01,13.60,0.87
Kansas,44.30,1.43,79.20,0.98,12.90,0.79
Kentucky,52.90,1.37,78.70,1.05,14.60,0.98
Louisiana,49.70,1.23,76.80,1.06,14.50,0.76
Maine,55.60,1.44,82.90,0.93,16.70,0.83
Maryland,53.90,1.46,83.60,0.95,14.00,0.80
Massachusetts,55.40,1.41,81.00,1.15,14.70,0.80
Michigan,52.40,0.62,80.50,0.47,15.00,0.43
Minnesota,51.50,1.20,84.40,0.87,14.40,0.86
Mississippi,43.20,1.14,76.60,0.91,12.30,0.78
Missouri,48.70,1.20,80.30,0.90,13.70,0.12
Montana,56.40,1.16,83.70,0.95,12.10,0.68
Nebraska,45.70,1.51,83.40,0.95,12.40,0.90
Nevada,54.20,1.17,80.60,1.07,15.80,1.08
New Hampshire,56.10,1.30,83.30,0.93,12.80,0.72
New Jersey,53.20,1.45,83.70,0.95,13.00,0.41
New Mexico,57.60,1.34,78.90,1.03,12.10,0.72
New York,53.70,0.67,82.60,0.48,14.60,0.77
North Carolina,52.20,1.26,81.90,0.84,14.70,0.97
North Dakota,48.60,1.34,84.20,0.88,14.30,1.13
Ohio,50.90,0.61,82.70,0.49,14.10,0.45
Oklahoma,47.20,1.42,78.80,1.33,15.90,0.98
Oregon,54.00,1.35,80.60,1.14,16.00,1.06
Pennsylvania,53.00,0.63,79.90,0.47,11.90,0.74
Rhode Island,57.20,1.20,79.50,1.02,13.60,0.40
South Carolina,50.50,1.21,79.50,0.95,12.60,0.82
South Dakota,43.40,1.30,81.70,1.05,13.60,0.87
Tennessee,48.90,1.35,78.40,1.35,12.90,0.79
Texas,48.70,0.62,79.00,0.48,14.60,0.98
Utah,42.00,1.49,85.00,0.93,14.50,0.76
Vermont,58.70,1.24,83.70,0.84,16.70,0.83
Virginia,51.80,1.18,82.00,1.04,14.00,0.80
Washington,53.50,1.39,84.10,0.96,14.70,0.80
West Virginia,52.80,1.07,79.80,0.93,15.00,0.43
Wisconsin,49.90,1.50,83.50,1.02,14.40,0.86
Wyoming,49.20,1.29,82.00,0.85,12.30,0.78
", sep=",", row.names='State', header=TRUE, as.is=TRUE)
# change names () to lower case
names (test1) <- tolower (names (test1))
#Write a cut/quantile function to apply on different columns of the data frame
CutQuintiles <- function( x) {
cut (x,quantile (x, (0:5/5)),include.lowest=TRUE)
}
#apply the CutQuintile () on every odd-numbered columns of the "test1" data
frame
test1$newcols <- sapply(test1 [, seq (1,6,2)], CutQuintiles)
# name 3 new columns based on the odd-numbered columns
names(test1$newcols) <- paste (names(test1 [, seq (1,6,2)]), "_cat")
dim (test1)
options (width=100)
test1
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