[ahurmazda]

Not familiar with matlab but its not as terse as R

``` using GLM, CSV, Plots

data = CSV.read("data.csv", header=["x","y"], types=[Float64, Float64]) #returns dataframe

ols = lm(@formula(y ~ x), data)

ypred = predict(ols)

yall = Base.hcat(data.y, ypred)

plot(data.x, yall, linewidth=2, title="Linear regression", label=["y", "ypred"], xlabel="x", ylabel="y")

```

[cbkeller]

The comment I was going to reply to disappeared, but for something closer in form to the Matlab example that used to be here:

  using Plots, DelimitedFiles
  d = readdlm("data.tsv",'\t')
  A = [ones(10,1) d[:,1:2]]; B = copy(d[:,3]); X = A\B
  plot(B, seriestype=:scatter, color=:blue); plot!(A*X, seriestype=:scatter, color=:red)

I find Julia syntax feels closer to Matlab than to Python or R, just different enough to be frustrating for the first month or so (followed by a period of "oh, that's why Julia does it this way instead!")

[DNF2]

No need to `copy` from `d[:,3]`. Slicing already creates copies (so you're copying twice), but even if it made a view you could still just write `B = d[:, 3]`.

[cbkeller]

Ah, didn't realize slicing always made copies. A view/alias/whatever would have been fine for the example, but having multiple variable names referring to the same memory has caused me enough problems to try to avoid it by default.