I’ve been using Julia to work with output from a stellar evolution code. My data files have several columns (~60 or more) and hundreds of rows. In previous versions of Julia, I used readtable in the DataFrame package to work with my data. I really appreciated that readtable not only read the numerical data, but also the headers, which I could then call by their names. For example: if I read file X as
data = readtable(X, skipstart=5, separator = ’ ')
and one of the column headers is “star_age”, then I could operate on, plot with, etc. the that column with
Since readtable has been depreciated, it is not clear to me what the best package to use is. It’s been previously noted that read in the CSV package is very slow. I’ve also found that CSV.read and DelimitedFiles.readdlm require specifying the header names? Since my files have ~60 columns, I’d rather not do that.