In this spec, the groupby transform works just fine using any of median
, count
, or average
. When I use sum
, the graph doesn't show. This version should display right.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
using JuMP | |
function localVar(m, name = "", expose = false) | |
x = JuMP.Variable(m, -Inf, Inf, :Cont, name, NaN) | |
if expose | |
JuMP.registervar(m, name, x) | |
end | |
x | |
end |
hello world
# /: comment
aK
\ hello world
.asdf#wer 456
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
importall Base | |
using DataFrames | |
type IX | |
df::AbstractDataFrame | |
end | |
IX(args...) = IX(DataFrame([args...]')) | |
length(x::IX) = 1 | |
type DFVector <: AbstractArray{AbstractDataFrame,1} | |
df::AbstractDataFrame | |
end |
Here is an extension to JLD to try to support reading of DataFrames. Writing seems to be okay.
import HDF5.read, JLD.JldFile, JLD.getrefs
function read{D<:AbstractDataFrame}(obj::HDF5Dataset{JldFile}, ::Type{D})
kv = getrefs(obj, Any)
keys = kv[1]
vals = kv[2]
d = D()
Matthew Dowle is working on a fast CSV reader for data.table. Here is test data case generated in R along with some timings:
require(data.table)
n=1e6
DT = data.table( a=sample(1:1000,n,replace=TRUE),
b=sample(1:1000,n,replace=TRUE),
c=rnorm(n),
d=sample(c("foo","bar","baz","qux","quux"),n,replace=TRUE),
This is code to convert a string to a type based on discussions here:
https://groups.google.com/d/msg/julia-dev/q9lG55PMdlc/C3IRKbKXcpoJ
type UnsupportedType
end
is_valid_type_ex(s::Symbol) = true
is_valid_type_ex(x::Int) = true