Hacker News Reader

Hacker News

Comment by ahurmazda | Hacker News Reader

Parent Full thread

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")

```

View on HN

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!")

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]`.

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.

Reply on news.ycombinator.com