# Delimited Files

`DelimitedFiles.readdlm` — Method

    readdlm(source, delim::AbstractChar, T::Type, eol::AbstractChar; header=false, skipstart=0, skipblanks=true, use_mmap, quotes=true, dims, comments=false, comment_char='#')

Read a matrix from the source where each line (separated by `eol`) gives one row, with elements separated by the given delimiter. The source can be a text file, stream or byte array. Memory mapped files can be used by passing the byte array representation of the mapped segment as source.

If `T` is a numeric type, the result is an array of that type, with any non-numeric elements as `NaN` for floating-point types, or zero. Other useful values of `T` include `String`, `AbstractString`, and `Any`.

If `header` is `true`, the first row of data will be read as header and the tuple `(data_cells, header_cells)` is returned instead of only `data_cells`.

Specifying `skipstart` will ignore the corresponding number of initial lines from the input.

If `skipblanks` is `true`, blank lines in the input will be ignored.

If `use_mmap` is `true`, the file specified by `source` is memory mapped for potential speedups. Default is `true` except on Windows. On Windows, you may want to specify `true` if the file is large, and is only read once and not written to.

If `quotes` is `true`, columns enclosed within double-quote (") characters are allowed to contain new lines and column delimiters. Double-quote characters within a quoted field must be escaped with another double-quote. Specifying `dims` as a tuple of the expected rows and columns (including header, if any) may speed up reading of large files. If `comments` is `true`, lines beginning with `comment_char` and text following `comment_char` in any line are ignored.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = [5; 6; 7; 8];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y])
           end

    julia> readdlm("delim_file.txt", '\t', Int, '\n')
    4×2 Array{Int64,2}:
     1  5
     2  6
     3  7
     4  8

    julia> rm("delim_file.txt")

source
`DelimitedFiles.readdlm` — Method

    readdlm(source, delim::AbstractChar, eol::AbstractChar; options...)

If all data is numeric, the result will be a numeric array. If some elements cannot be parsed as numbers, a heterogeneous array of numbers and strings is returned.

source
`DelimitedFiles.readdlm` — Method

    readdlm(source, delim::AbstractChar, T::Type; options...)

The end of line delimiter is taken as `\n`.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = [1.1; 2.2; 3.3; 4.4];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y], ',')
           end;

    julia> readdlm("delim_file.txt", ',', Float64)
    4×2 Array{Float64,2}:
     1.0  1.1
     2.0  2.2
     3.0  3.3
     4.0  4.4

    julia> rm("delim_file.txt")

source
`DelimitedFiles.readdlm` — Method

    readdlm(source, delim::AbstractChar; options...)

The end of line delimiter is taken as `\n`. If all data is numeric, the result will be a numeric array. If some elements cannot be parsed as numbers, a heterogeneous array of numbers and strings is returned.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = [1.1; 2.2; 3.3; 4.4];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y], ',')
           end;

    julia> readdlm("delim_file.txt", ',')
    4×2 Array{Float64,2}:
     1.0  1.1
     2.0  2.2
     3.0  3.3
     4.0  4.4

    julia> z = ["a"; "b"; "c"; "d"];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x z], ',')
           end;

    julia> readdlm("delim_file.txt", ',')
    4×2 Array{Any,2}:
     1  "a"
     2  "b"
     3  "c"
     4  "d"

    julia> rm("delim_file.txt")

source
`DelimitedFiles.readdlm` — Method

    readdlm(source, T::Type; options...)

The columns are assumed to be separated by one or more whitespaces. The end of line delimiter is taken as `\n`.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = [5; 6; 7; 8];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y])
           end;

    julia> readdlm("delim_file.txt", Int64)
    4×2 Array{Int64,2}:
     1  5
     2  6
     3  7
     4  8

    julia> readdlm("delim_file.txt", Float64)
    4×2 Array{Float64,2}:
     1.0  5.0
     2.0  6.0
     3.0  7.0
     4.0  8.0

    julia> rm("delim_file.txt")

source
`DelimitedFiles.readdlm` — Method

    readdlm(source; options...)

The columns are assumed to be separated by one or more whitespaces. The end of line delimiter is taken as `\n`. If all data is numeric, the result will be a numeric array. If some elements cannot be parsed as numbers, a heterogeneous array of numbers and strings is returned.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = ["a"; "b"; "c"; "d"];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y])
           end;

    julia> readdlm("delim_file.txt")
    4×2 Array{Any,2}:
     1  "a"
     2  "b"
     3  "c"
     4  "d"

    julia> rm("delim_file.txt")

source
`DelimitedFiles.writedlm` — Function

    writedlm(f, A, delim='\t'; opts)

Write `A` (a vector, matrix, or an iterable collection of iterable rows) as text to `f` (either a filename string or an `IO` stream) using the given delimiter `delim` (which defaults to tab, but can be any printable Julia object, typically a `Char` or `AbstractString`).

For example, two vectors `x` and `y` of the same length can be written as two columns of tab-delimited text to `f` by either `writedlm(f, [x y])` or by `writedlm(f, zip(x, y))`.

Examples

    julia> using DelimitedFiles

    julia> x = [1; 2; 3; 4];

    julia> y = [5; 6; 7; 8];

    julia> open("delim_file.txt", "w") do io
               writedlm(io, [x y])
           end

    julia> readdlm("delim_file.txt", '\t', Int, '\n')
    4×2 Array{Int64,2}:
     1  5
     2  6
     3  7
     4  8

    julia> rm("delim_file.txt")

source

Theme

This document was generated with Documenter.jl on Sunday 2 August 2020. Using Julia version 1.5.0.