Dataframe Filter

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While the effect is minimal in this example, you can gain a bit of efficiency by passing only the column(s) you’re interested in to filter i.e.

julia> @btime filter(row -> row.final>45, df)
  18.120 μs (25 allocations: 1.88 KiB)

vs

julia> @btime filter(:final => f-> f>45, df)
  15.324 μs (24 allocations: 1.81 KiB)

for multiple

julia> @btime filter(row -> row.name=="b" && row.final>45, df)
  19.188 μs (25 allocations: 1.80 KiB)

vs

julia> @btime filter([:name, :final] => (n,f)-> n=="b" && f>45, df)
  18.529 μs (29 allocations: 1.98 KiB)
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