hello, I have two different dataframes with different columns and headers, but the columns Start and Start_site are related and in particular I want to select the rows of the first dataframe with Start matching the second dataframe with Start_site. Essentially I am looking for the julia equivalent…

julia> x=["a","b","c"] julia> df = DataFrame(X = ["a","c","d","g"]) julia> df[.!in(x).(df.X),:] 2×1 DataFrame │ Row │ X │ │ │ String │ ├─────┼────────┤ │ 1 │ d │ │ 2 │ g │

Nevermind, I found it: join(df1, df2; on = :Start, kind = :semi, makeunique = false, indicator = nothing, validate = (false, false)) I had to call the columns with the same name

There is also the in function: start = [1, 3, 4, 6] start_site = 1:5 in_start_site = in(start_site) # in(...) returns a function in_start_site.(start) # [true, true, true, false] in(collection) returns a function that tests if something is in collection. You can also write this in one line: in…

cf [image] Julia's in.() seems slow compared to R's %in% Performance Hi everyone, I want to compare if elements of vector x are in elements of vector y. In R, I can do this as follows: > x <- c("a", "b", "c") > y <- c("b", "a") > x %in% y [1] TRUE TRUE FALSE In Julia…

Hello, I got a slight variation of this problem. Instead of testing arrays, I would like to select the rows of a dataframe whose column X corresponds to the all the elements of an array. In other words: if I have an array x=["a", "b", "c"] and a dataframe df with unique(df[:X]) = "a", "c", "d", "g…

or: join(df1, df2, on=:X, kind=:anti) ?join

filter(df) do row row.X in x end

What is Julia's equivalent of R's %in%

New to Julia

Luigi_Marongiu November 21, 2019, 1:26pm 7

what would be the negation of this? that is how to select the rows of the dataframe whose field X IS NOT in x?

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What is Julia's equivalent of R's %in%

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