In Julia, using CSV.jl
, it is possible to read a DataFrame from a .csv
file:
using CSV
df = CSV.read("data.csv", delim=",")
However, how can I instead read a CSV file into an Vector{Float64}
data type?
You can use the DelimitedFiles
module from stdlib:
julia> using DelimitedFiles
julia> s = """
1,2,3
4,5,6
7,8,9"""
"1,2,3\n4,5,6\n7,8,9"
julia> b = IOBuffer(s)
IOBuffer(data=UInt8[...], readable=true, writable=false, seekable=true, append=false, size=17, maxsize=Inf, ptr=1, mark=-1)
julia> readdlm(b, ',', Float64)
3×3 Array{Float64,2}:
1.0 2.0 3.0
4.0 5.0 6.0
7.0 8.0 9.0
I am showing you the example reading from IOBuffer
to be fully reproducible, but you can also read data from file. In the docstring of readdlm
you can find more details about the available options.
Notice that you will get Matrix{Float64}
not Vector{Float64}
, but I understand that this is what you wanted. If not then in order to convert a matrix into a vector you can call vec
function on it after reading the data in.
This is how you can read back a Matrix
using CSV.jl:
julia> df = DataFrame(rand(2,3))
2×3 DataFrame
│ Row │ x1 │ x2 │ x3 │
│ │ Float64 │ Float64 │ Float64 │
├─────┼───────────┼──────────┼──────────┤
│ 1 │ 0.0444818 │ 0.570981 │ 0.608709 │
│ 2 │ 0.47577 │ 0.675344 │ 0.500577 │
julia> CSV.write("test.csv", df)
"test.csv"
julia> CSV.File("test.csv") |> Tables.matrix
2×3 Array{Float64,2}:
0.0444818 0.570981 0.608709
0.47577 0.675344 0.500577