bkamins commented on code in PR #487:
URL: https://github.com/apache/arrow-julia/pull/487#discussion_r1329655181


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docs/src/manual.md:
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@@ -66,6 +66,7 @@ So, what can you do with an `Arrow.Table` full of data? Quite 
a bit actually!
 Because `Arrow.Table` implements the 
[Tables.jl](https://juliadata.github.io/Tables.jl/stable/) interface, it opens 
up a world of integrations for using arrow data. A few examples include:
 
 * `df = DataFrame(Arrow.Table(file))`: Build a 
[`DataFrame`](https://juliadata.github.io/DataFrames.jl/stable/), using the 
arrow vectors themselves; this allows utilizing a host of DataFrames.jl 
functionality directly on arrow data; grouping, joining, selecting, etc.
+* `df = copy(DataFrame(Arrow.Table(file)))`: Build a 
[`DataFrame`](https://juliadata.github.io/DataFrames.jl/stable/), where the 
columns are regular `Vector`s. This requires that you have enough memory to 
load the entire DataFrame into memory.

Review Comment:
   I thought of it and it seems that these are only going to be `Vector`s or 
`PooledVector`s, and it is not going to change in the future. Right @quinnj? In 
this case I think it is OK to be specific (the first option)



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