using CSV, DataFrames iris = CSV.read(joinpath(dirname(pathof(DataFrames)),"..","test/data/iris.csv")) head(iris) 6×5 DataFrame │ Row │ SepalLength │ SepalWidth │ PetalLength │ PetalWidth │ Species │ │ │ Float64⍰ │ Float64⍰ │ Float64⍰ │ Float64⍰ │ String⍰ │ ├─────┼─────────────┼────────────┼─────────────┼────────────┼─────────┤ │ 1 │ 5.1 │ 3.5 │ 1.4 │ 0.2 │ setosa │ │ 2 │ 4.9 │ 3.0 │ 1.4 │ 0.2 │ setosa │ │ 3 │ 4.7 │ 3.2 │ 1.3 │ 0.2 │ setosa │ │ 4 │ 4.6 │ 3.1 │ 1.5 │ 0.2 │ setosa │ │ 5 │ 5.0 │ 3.6 │ 1.4 │ 0.2 │ setosa │ │ 6 │ 5.4 │ 3.9 │ 1.7 │ 0.4 │ setosa │ I want to find all rows where Species is in setosa or virginica. Note that the answer must use a lookup into an array of values to find since I want the result to work when looking for arbitrarily many values.
There is a function called indexin. It gets me halfway there:
iris[indexin(iris.Species ,["setosa", "virginica"])] But when I try to use it for indexing the result is:
ERROR: ArgumentError: Only Integer values allowed when indexing by vector of numbers 3 Answers
iris[ in.(iris[:Species],(["virginica","setosa"],)),: ] The additional tuple around ["virginica","setosa"] allows to avoid broadcasting over the search list.
A way to achieve this is to use findall:
iris[findall(in(["setosa", "virginica"]), iris.Species), :] You can use the findin function.
iris[findin(iris[:Species],["setosa","virginica"]),:] Note that if you want to use findin to search only one value, it has to be always an array, like
iris[findin(iris[:Species],["setosa"]),:] 
