apply - R: Trying to determine which decile each data point is in, for all variables in a data frame -


i have data containing information on prices consumers willing pay services. i'm trying find deciles each response falls into, several services using cut function.

for (i in 2:13){     x<-quantile(data1[,i],c(0,.1,.2,.3,.4,.5,.6,.7,.8,.9,1),na.rm=true)      data1[paste(names(data1[i]), "deciles", sep="_")] <- cut(data1[,i], breaks=x, includ) }

however, have 2 problems: there variables 2 deciles same value (e.g. 0 =0, .1=0), cut function not accept. also, initial columns code work, actual decile , not decile number (for example "(1.99,2.56]" instead of .2.

if has ideas, appreciate it.

for first problem: can use unique breaks , pass cut. second, convert factor integer , use integer index in probs vector pull out appropriate quantile break.

## sample data, third column fail `cut` set.seed(0) data1 <- data.frame(x=rnorm(100), y=rnorm(100), z=sample(0:5, 100, rep=t)) qs <- seq(0, 1, by=0.1)                                                      # probs quantile (i in 1:3){     x <- quantile(data1[,i], qs, na.rm=true)     used <- qs[which(diff(c(0, x)) > 0)]                                     # quantiles worked     cuts <- cut(data1[,i], breaks=unique(x), include=t)                      # factors had them     data1[paste(names(data1[i]), "deciles", sep="_")] <- cuts     data1[paste(names(data1[i]), "num", sep="_")] <- used[as.integer(cuts)]  # numeric values } #            x          y z       x_deciles x_num       y_deciles y_num z_deciles # 1  1.2629543  0.7818592 0     (1.24,2.44]   1.0      (0.78,1.5]   0.9   [0,1.7] # 2 -0.3262334 -0.7767766 3 (-0.421,-0.252]   0.4 (-0.956,-0.714]   0.3     (2,3] # 3  1.3297993 -0.6159899 1     (1.24,2.44]   1.0 (-0.714,-0.459]   0.4   [0,1.7] # 4  1.2724293  0.0465803 5     (1.24,2.44]   1.0  (0.0262,0.376]   0.7     (4,5] # 5  0.4146414 -1.1303858 5   (0.234,0.421]   0.7   [-1.68,-1.12]   0.1     (4,5] # 6 -1.5399500  0.5767188 5   [-2.22,-1.07]   0.1    (0.376,0.78]   0.8     (4,5] #   z_num # 1   0.3 # 2   0.6 # 3   0.3 # 4   0.8 # 5   0.8 # 6   0.8

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