Reading text data: `readdlm` is deprecated, so how CSV package is used?

[ryofurue]

@oheil

using CSV, DataFrames

myfile = "infile.txt"
df = CSV.read(myfile,DataFrame)

Thanks! I’ve made some progress using that. But I got stuck with delimiters. According to the thread (from 2021) which I quote at the end of this message, you have to preprocess the input text file if it uses multiple delimiters. Is that still true today? I thought that it was quite usual to expect to be able to specify a Regex, along the lines of

   df = CSV.read(myfile, DataFrame; delim=r"\s+") # any sequence of "space" characters

so that any nonzero sequence of “space” characters ( \s ) be tread as one single delimiter.

Currently CSV.read() isn’t able to “guess” the number of columns in my datafile, presumably because the datafile uses a mixture of tabs and spaces. readdlm() correctly detects the delimiters.

Reading data text files delimited with both spaces & tabs

Is it possible in CSV.jl, DelimitedFiles.jl, or other, to read text files that contain both spaces & tabs, in the header and/or data sections? An example is provided below. NB: the hidden spaces and tabs should be there after copy and paste, also added row with missing value Col1 Col2 Col3 1 1 012 2 1 013 2 1 2 1 015 Currently, the workaround used is to replace all tabs by spaces in a text editor and then read the file using CSV.jl: using CSV, DataFrames df = CSV.read(file, …