# Alternatives to Query.jl for aggregation
**URL:** https://discourse.julialang.org/t/alternatives-to-query-jl-for-aggregation/85496
**Category:** General Usage
**Created:** [August 8, 2022, 6:04pm UTC](https://discourse.julialang.org/t/alternatives-to-query-jl-for-aggregation/85496 "2022-08-08T18:04:42Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@IljaK91](https://discourse.julialang.org/u/IljaK91)
#### Post date: [August 8, 2022, 6:04pm UTC](https://discourse.julialang.org/t/alternatives-to-query-jl-for-aggregation/85496/1 "2022-08-08T18:04:42Z")
Hi everybody,
I am looking for a way to aggregate my data like Query.jl. Usually, I would run something like:
```julia
test_df = DataFrame(A = [1,1,2,2], B = [missing, 1, missing, 2])
df_agg = test_df |>
@groupby(_.A) |>
@map({key = key(_),
B = first(_.B),
B_last = last(_.B),
B_mean = mean(skipmissing(_.B))}) |> DataFrame
```
But since Query.jl does not support missing values, mean(skipmissing(…)) will return always missing, as long there are some missing values in a specific period. I tripped over this one too many times with no obvious solution within Query.jl itself.
Of course, I can generate the mean myself and then do first(\_.B\_mean), but I wanted to know whether there is a viable alternative.
Thank you very much!
---
### Author:  [@tbeason](https://discourse.julialang.org/u/tbeason)
#### Post date: [August 8, 2022, 6:32pm UTC](https://discourse.julialang.org/t/alternatives-to-query-jl-for-aggregation/85496/2 "2022-08-08T18:32:42Z")
regular DataFrames.jl will work
```julia
combine(groupby(test_df,"A"), "B" .=> [first,last,mean ∘ skipmissing])
```