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i´m very new at R and have some basic problems.

I have a dataset and will filter some data and save them in a new table. I have to do this for many different Datasets so i would like to use a loop. So i have a table with different Ages (from 0-100) and i want a Table for each age. The basic Idea was :

n<-100    
for( i in 0:n){Age[i] <- subset(Data, Data$AGE == [i], select = c(XXX, XX, XXX))

Gets me Error: Objekt not found?

structure(list(PAT_ALTER = c(3, 0, 8, 1, 8, 17, 11, 12, 2, 6, 3, 6, 5, 5, 1, 12, 9, 11, 0, 6, 6, 10, 6, 9, 2, 16, 3, 4, 3, 6, 14, 3, 0, 4, 2, 3, 3, 3, 2, 8, 0, 7, 0, 1, 1, 1, 7, 8, 14, 2, 0, 4, 0, 2, 3, 0, 0, 0, 2, 5, 4, 3, 12, 8, 0, 12, 11, 2, 0, 0, 0, 1, 0, 9, 12, 2, 4, 4, 5, 16, 0, 10, 8, 0, 4, 3, 2, 7, 5, 4, 0, 11, 1, 3, 5, 0, 8, 2, 0, 9), SEX = c("w", "w", "w", "m", "m", "w", "m", "m", "m", "m", "w", "m", "m", "m", "m", "w", "m", "w", "m", "w", "w", "m", "w", "w", "w", "m", "m", "w", "w", "w", "m", "m", "m", "w", "m", "m", "m", "m", "w", "w", "m", "m", "w", "m", "m", "m", "w", "w", "w", "w", "w", "w", "m", "m", "m", "w", "m", "w", "w", "m", "w", "w", "w", "w", "w", "w", "m", "m", "w", "m", "w", "m", "w", "m", "m", "w", "m", "w", "w", "m", "m", "m", "m", "m", "w", "m", "m", "m", "w", "w", "m", "w", "w", "m", "w", "m", "w", "m", "w", "w") ICD_KAPITEL = c(test1, test2, test3, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_), ICD_KODE = c(test1, test2, test3, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_), ICD_KODE_TEXT = c(Test1, test2, test3, test4, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, NA_character_), BETT_REAL = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), DRINGLICHKEIT = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ZUBRING_REAL = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)

Thanks for your help, Alex.

scarlet
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    You didn't give a lot of information in your question which makes it kind of hard to help. Maybe you can improve your question after reading [this](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example/5963610#5963610)? – iron9 May 05 '20 at 16:14

1 Answers1

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Here is an example using Iris dataset.

You can split a data set by a variable, save it as a list, then export the contents of the list to the .GlobalEnv.

#split data frame by a variable
list_df <- split(iris, iris$Species)
#export contents of list to .GlovalEnv
list2env(list_df, envir = .GlobalEnv)

In your case it might look something like this (I can't verify without a sample dataset)

list_df2 <- split(df, df$age)
namesoflist <- paste0("age_",1:100)
setNames(list_df2,namesoflist)
list2env(list_df2,envir=.GlovalEnv)
Mike
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  • Thank you very much. im afraid your solution does not perfectly fit for my problem. To make it more clear here a Data-Example:13 1 aa 4 bb 14 aa 2 cc 11 aa 4 bb 1 14 cc now i would have for each Age ( in this example for 1,2,4 and 14) a seperate Table with the information (aa,cc....); The problem is that there are numbers left (for example no date in the age of 55). Thanks a lot, Alex – scarlet May 05 '20 at 16:09
  • @scarlet would you be able to edit your question to provide your data. If you have a data.frame you can use `dput(df) `and then copy and paste that into your question above. If the data is large you can also do `dput(head(df,100))` to provide the first 100 rows of the data.frame. – Mike May 05 '20 at 16:43
  • So i hope the provided Data helps. For what i am looking for at the end is a data investigation of the different Group of People. For example i need a histogram for all 2 Yeah old Patient of the 5 most commen ICD Diagnosis. The Dataset is of a better Quality (not so much NA_Charakters) it was just for putting it online. Thanks for your help once again. – scarlet May 05 '20 at 17:18