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I think it should be returning a DataFrame, preserving the inner type
here an example
using Distributed
# add two further julia processes which could run on other machinesaddprocs(2, exeflags="--threads=2")
# Distributed.@everywhere execute code on all machines@everywhereusing Dagger # needed for all_processors# Dagger uses both Threads and Machines as processes
Dagger.all_processors()
using DTables, DataFrames, CSV
url ="https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv"
files = [url, url, url, url, url]
d =DTable(DataFrame ∘ CSV.File ∘ download, files)
g = DTables.groupby(d, :species)
r =reduce(+, g, cols=[:sepal_width])
fetch(r)
# returns# (species = String15["virginica", "setosa", "versicolor"], result_sepal_width = [743.5, 856.9999999999998, 692.4999999999995])
The text was updated successfully, but these errors were encountered:
I think it should be returning a DataFrame, preserving the inner type
here an example
The text was updated successfully, but these errors were encountered: