DilumAluthge commented on code in PR #487: URL: https://github.com/apache/arrow-julia/pull/487#discussion_r1326663199
########## docs/src/manual.md: ########## @@ -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: @bkamins Should this say `copy(DataFrame(...); copycols=true)` instead, just to be safe? Is there any chance that the default value (`copycols=true`) might change to `copycols=false` in the future? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
