Did you try it? It should work.
julia> lm(@formula(log(y) ~ x), df)
StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Array{Float64,1}},GLM.DensePredChol{Float64,LinearAlgebra.Cholesky{Float64,Array{Float64,2}}}},Array{Float64,2}}
:(log(y)) ~ 1 + x
Coefficients:
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Estimate Std. Error t value Pr(>|t|) Lower 95% Upper 95%
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(Intercept) 0.37625 0.0381661 9.85821 <1e-15 0.30051 0.451989
x 0.0331787 0.0735028 0.451394 0.6527 -0.112685 0.179043
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