1

I have a dynamic dataframe of the top 5 'events' over the last year; produced by performing: head(source_df, 5). This produces a dataframe of the following structure:

top_5  <- structure(list(Date = structure(c(1670284800, 1669852800, 
1669161600, 1668470400, 1668470400), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), Name = c("lt 20", 
"lt 201", "lt 45", "lt 212", 
"lt 01"),
    Volume = c(3252, 2511.221, 
    3559.5, 3250, 2250), Amount = c(2.1, 2.4, 
    1.21, 1.44, 6.12), AAP = c(3.472214, 
    3.411409, 3.346509, 3.425947, 3.591546), Code= c("C7720", "Z8158", 
    "K7110", "Z2138", "G7751")), row.names = c(NA, 
5L), class = "data.frame")

I have a number of huge dataframes that cover various transactions in these codes. What I would like to do is dynamically create 5 subsetted dataframes (df1, df2, df3, df4, df5) for each of the codes in the above dataframe. Does anyone have any advice on how to achieve this? Apologies for any issue, English is not a first language.

As request, here is a portion of dput:

df <- structure(list(Code = c("CK1204", "CK1204", "C7720", "C7720", 
"C7720", "C7720", "C7720", "CK1204", "CK1204", "CK1204", "C7720", 
"C7720", "C7720", "CK1204", "C7720", "CK1204", "CK1204", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "CK1204", "CK1204", "C7720", "CK1204", "C7720", 
"C7720", "C7720", "C7720", "CK1204", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "CK1204", "C7720", "C7720", "C7720", "C7720", "C7720", 
"CK1204", "CK1204", "C7720", "CK1204", "C7720", "C7720", "C7720", 
"C7720", "C7720", "CK1204", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "CK1204", "C7720", "C7720", "C7720", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "C7720", 
"CK1204", "C7720", "CK1204", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "CK1204", 
"C7720", "CK1204", "C7720", "C7720", "C7720", "C7720", "CK1204", 
"CK1204", "C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "C7720", 
"CK1204", "CK1204", "C7720", "C7720", "C7720", "C7720", "C7720", 
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"C7720", "CK1204", "CK1204", "CK1204", "CK1204", "CK1204", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", 
"C7720", "CK1204", "CK1204", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "CK1204", 
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"C7720", "C7720", "C7720", "CK1204", "CK1204", "CK1204", "CK1204", 
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"C7720", "C7720", "C7720", "C7720", "CK1204", "C7720", "C7720", 
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"C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", "CK1204", 
"CK1204", "CK1204", "C7720", "C7720", "C7720", "CK1204", "C7720", 
"CK1204", "CK1204", "C7720", "C7720", "C7720", "CK1204", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "CK1204", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"C7720", "C7720", "C7720", "C7720", "C7720", "C7720", "C7720", 
"CK1204", "CK1204", "C7720", "C7720", "C7720", "C7720", "CK1204", 
"C7720", "C7720", "C7720", "C7720", "CK1204", "CK1204", "CK1204", 
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"C7720", "CK1204", "C7720", "CK1204", "CK1204", "C7720", "C7720", 
"C7720", "C7720", "CK1204", "C7720"), created_date = structure(c(1665648152, 
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MrFlick
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alec22
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  • I would suggest not creating separate global variables, but you can split the data into a list. To reduce a larger dataset to only those values, you can use a `merge()` or `dplyr::inner_join()`. Then you can use `split()` to separate by group. Your example here is incomplete so it's hard to give the exact code. It's easier to help you if you include a simple [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) with sample input and desired output that can be used to test and verify possible solutions. – MrFlick Dec 06 '22 at 14:52
  • Thanks, I've now added some dput – alec22 Dec 06 '22 at 15:21
  • Most likely `merge(df, top_5) |> split(~Code)` will do what you need. It will return a list with 5 elements each containing a data.frame with the data for a single code. – MrFlick Dec 06 '22 at 15:25
  • Thanks for help, one problem. The df I'm trying to filter dynamically has >1mn observations (with many many different codes), meaning merging causes some issues. Is there any way to dynamically filter, and create some fixed dataframe objects for each code from that? – alec22 Dec 06 '22 at 15:34
  • 1
    Sadly the merge(df, top_5) |> split(~Code) delivers: Error: unexpected '>' in "merge(df, top_5)) |>" – alec22 Dec 06 '22 at 15:55
  • What version of R are you using? The `|>` was introduced in R 4.1 – MrFlick Dec 06 '22 at 15:56
  • R version 4.0.5 (2021-03-31) – alec22 Dec 06 '22 at 16:00

0 Answers0