ts3 = @from i in df3 begin
@select {i.timestamp, i.NMerged}
@collect TimeArray
end
I get
MethodError: no method matching TimeSeries.TimeArray(::Array{Any,1}, ::Array{Int64,2}, ::Array{String,1})
Closest candidates are:
TimeSeries.TimeArray(::AbstractArray{D<:Base.Dates.TimeType,1}, ::AbstractArray{T,N}, ::Array{S<:AbstractString,1}, ::Any) where {T, N, D<:Base.Dates.TimeType, S<:AbstractString} at /home/juser/.julia/v0.6/TimeSeries/src/timearray.jl:41
TimeSeries.TimeArray(::D<:Base.Dates.TimeType, ::AbstractArray{T,N}, ::Array{S<:AbstractString,1}, ::Any) where {T, N, D<:Base.Dates.TimeType, S<:AbstractString} at /home/juser/.julia/v0.6/TimeSeries/src/timearray.jl:44
TimeSeries.TimeArray(::AbstractArray{D<:Base.Dates.TimeType,1}, ::AbstractArray, ::Any) where D<:Base.Dates.TimeType at /home/juser/.julia/v0.6/TimeSeries/src/timearray.jl:55
...
this is because timestamp has Any type, even though all the elements are DateTime. Inserting a df3[:timestamp] = map(identity, df3[:timestamp]) fixes the element type of the column and the error goes away, but I'd like IterableTables to do so by itself (and give a nice error if the timestamp is not of time type).
In code like:
I get
this is because timestamp has
Any
type, even though all the elements are DateTime. Inserting adf3[:timestamp] = map(identity, df3[:timestamp])
fixes the element type of the column and the error goes away, but I'd like IterableTables to do so by itself (and give a nice error if the timestamp is not of time type).