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basically I have a single column data set of 53 values. what I am trying to achieve is binning them into sets based on a 400 point difference, ranging from ~500 to 4500. you can just be vague if needed and state a function for doing so, I can work out the rest

Jonah_huggins
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  • Hi @Jonah_huggins. Welcome to StackOverflow. Please, visit this thread on how to make a great R reproducible example. Could you provide a `dput()`? https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example – cmirian Apr 05 '20 at 15:22

3 Answers3

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A dplyr option

library(dplyr)
df_test <- data.frame(x = runif(1000, 400, 5000),
                      y = rep("A", 1000))

df_test <- df_test %>% 
  mutate(bins = case_when(between(x, 400, 800) ~ "Set 1",
                          between(x, 801, 1600) ~ "Set 2",
                          between(x, 1601, 5000) ~ "Set 3"))
head(df_test)
              x y  bins
    1 1687.2854 A Set 3
    2 3454.1035 A Set 3
    3 4979.5434 A Set 3
    4  796.6475 A Set 1
    5 3665.7444 A Set 3
    6 3083.8969 A Set 3

You can of course adjust the between ranges as you see fit.

Greg
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Here's a base R approach that uses cut with breaks = defined with a predetermined seq. 

set.seed(1)
data <- runif(n=53,500,4500)
groups <- as.integer(cut(data,c(-Inf,seq(500,4500,by=400),Inf))) 
data.frame(data,groups)
      data groups
1 1562.035      4
2 1988.496      5
3 2791.413      7
4 4132.831     11
Ian Campbell
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  • Hi! thank you so much for responding with this, however I would love to ask you a following question: I read up on cut() and used: signals.2 – Jonah_huggins Apr 05 '20 at 22:18
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Hi i would do it like this:

data$group<-cut(data$value,
               breaks = seq(0,4500,500),
               labels = paste("Group",LETTERS[1:9], sep="_"))

or if you prefer more basic style of R use [ ] :

under_500<-data[data$value<500 ,]

over500_under900<-data[data$value %in% 501:900 ,]
## etc..
over4000<-data[data$value>4000 ,]
user12256545
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