Fixed now
On Saturday, January 18, 2014 6:54:08 PM UTC-5, Iain Dunning wrote:
>
> I'm getting a strange problem, starting from empty .julia
>
> julia> Pkg.add("DataFrames")
> INFO: Initializing package repository /home/idunning/.julia
> INFO: Cloning METADATA from git://github.com/JuliaLang/METADATA.jl
> INFO: Cloning cache of Blocks from git://github.com/tanmaykm/Blocks.jl.git
> INFO: Cloning cache of DataFrames from git://
> github.com/JuliaStats/DataFrames.jl.git
> INFO: Cloning cache of GZip from git://github.com/kmsquire/GZip.jl.git
> INFO: Cloning cache of SortingAlgorithms from git://
> github.com/JuliaLang/SortingAlgorithms.jl.git
> INFO: Cloning cache of StatsBase from git://
> github.com/JuliaStats/StatsBase.jl.git
> INFO: Installing Blocks v0.0.1
> *INFO: Installing DataFrames v0.3.16*
> INFO: Installing GZip v0.2.5
> INFO: Installing SortingAlgorithms v0.0.1
> INFO: Installing StatsBase v0.3.5
> INFO: Package database updated
>
> julia> using DataFrames
> ERROR: Stats not found
> in require at loading.jl:39
> in include at boot.jl:240
> while loading /home/idunning/.julia/DataFrames/src/DataFrames.jl, in
> expression starting on line 5
>
> Key part is its installing an old version of DataFrames but not Stats,
> instead its install StatsBase.
>
>
> On Saturday, January 18, 2014 3:00:37 PM UTC-5, John Myles White wrote:
>>
>> As a consequence of renaming Stats to StatsBase, I’ve had to update
>> DataFrames and DataArrays.
>>
>> This means that everyone working with those libraries is now in sync with
>> master again. That brings with it a lot of changes that may break some
>> code.
>>
>> To help minimize breakage, here are the most obvious changes that might
>> affect you.
>>
>> (1) We now offer @data / @pdata macros to write out literal DataArrays
>> and PooledDataArrays. They need a little bit more refinement to deal with
>> edge cases, but they’re a big improvement over the previous system.
>> Examples of usage below:
>>
>> @data [1, 2, NA, 4]
>> @data [1 2; NA 4]
>>
>> @pdata [1, 2, NA, 4]
>> @pdata [1 2; NA 4]
>>
>> You can also do this with variables (as long as they’re not NA’s):
>>
>> a, b, c, d = 1, 2, 3, 4
>> @data [a, b, c, d]
>> @data [a b; c d]
>>
>> The unfortunate edge case is that the following will fail:
>>
>> a, b, c, d = 1, 2, 3, NA
>> @data [a, b, c, d]
>> @data [a b; c d]
>>
>> (2) To convert other AbstractArrays to DataArrays / DataFrames, please
>> use the data and pdata functions:
>>
>> data([1, 2, 3, 4])
>> data(1:3)
>>
>> pdata([1, 2, 3, 4])
>> pdata(1:3)
>>
>> We’ve removed a lot of the constructors for DataArrays and
>> PooledDataArray’s that had no parallel to anything in Base, where there are
>> very few valid constructors for Array’s. If you use things like
>> DataArray(1:10), it will be broken now. Please switch to using the data()
>> function.
>>
>> — John
>>
>>
