On Saturday, 21 November 2015 at 14:16:26 UTC, Laeeth Isharc
wrote:
Not sure it is a great idea to use a variant as the basic
option when very often you will know that every cell in a
particular column will be of the same type.
I'm reading today about an n-dim extension to pandas named
On Thursday, 19 November 2015 at 22:14:01 UTC, ZombineDev wrote:
On Thursday, 19 November 2015 at 06:33:06 UTC, Jay Norwood
wrote:
On Wednesday, 18 November 2015 at 22:46:01 UTC, jmh530 wrote:
My sense is that any data frame implementation should try to
build on the work that's being done with
On Thursday, 19 November 2015 at 06:33:06 UTC, Jay Norwood wrote:
Maybe the nd slices could be applied if you considered each row
to be the same structure, and slice by rows rather than
operating on columns. Pandas supports a multi-dimension panel.
Maybe this would be the application for
On Thursday, 19 November 2015 at 06:33:06 UTC, Jay Norwood wrote:
On Wednesday, 18 November 2015 at 22:46:01 UTC, jmh530 wrote:
My sense is that any data frame implementation should try to
build on the work that's being done with n-dimensional slices.
I've been watching that development, but
On Thursday, 19 November 2015 at 06:33:06 UTC, Jay Norwood wrote:
On Wednesday, 18 November 2015 at 22:46:01 UTC, jmh530 wrote:
My sense is that any data frame implementation should try to
build on the work that's being done with n-dimensional slices.
I've been watching that development, but
On Monday, 2 November 2015 at 13:54:09 UTC, Jay Norwood wrote:
I was reading about the Julia dataframe implementation
yesterday, trying to understand their decisions and how D might
implement.
From my notes,
1. they are currently using a dictionary of column vectors.
2. for NA (not available)
On Tuesday, 17 November 2015 at 13:56:14 UTC, Jay Norwood wrote:
I looked through the dataframe code and a couple of comments...
I had thought perhaps an app could read in the header info and
type info from hdf5, and generate D struct definitions with
column headers as symbol names. That
On Wednesday, 18 November 2015 at 17:15:38 UTC, Laeeth Isharc
wrote:
What do you think about the use of NaN for missing floats? In
theory I could imagine wanting to distinguish between an NaN in
the source file and a missing value, but in my world I never
felt the need for this. For integers
On Wednesday, 18 November 2015 at 18:04:30 UTC, Jay Norwood wrote:
vector. I'll try to find the discussions and post the link.
Here are the two discussions I recall on the julia NA
implementation.
http://wizardmac.tumblr.com/post/104019606584/whats-wrong-with-statistics-in-julia-a-reply
On Wednesday, 18 November 2015 at 22:46:01 UTC, jmh530 wrote:
My sense is that any data frame implementation should try to
build on the work that's being done with n-dimensional slices.
I've been watching that development, but I don't have a feel for
where it could be applied in this case,
On Monday, 2 November 2015 at 13:54:09 UTC, Jay Norwood wrote:
I saw someone posting that they were working on DataFrame
implementation here, but haven't been able to locate any code
in github, and was wondering what implementation decisions are
being made here. Thanks.
My sense is that
One more discussion link on the NA subject. This one on the R
implementation of NA using a single encoding of NaN, as well as
their treatment of a selected integer value as a NA.
http://rsnippets.blogspot.com/2013/12/gnu-r-vs-julia-is-it-only-matter-of.html
I looked through the dataframe code and a couple of comments...
I had thought perhaps an app could read in the header info and
type info from hdf5, and generate D struct definitions with
column headers as symbol names. That would enable faster
processing than with the associative arrays, as
I was reading about the Julia dataframe implementation yesterday,
trying to understand their decisions and how D might implement.
From my notes,
1. they are currently using a dictionary of column vectors.
2. for NA (not available) they are currently using an array of
bytes, effectively as a
On Monday, 2 November 2015 at 13:54:09 UTC, Jay Norwood wrote:
I was reading about the Julia dataframe implementation
yesterday, trying to understand their decisions and how D might
implement.
From my notes,
1. they are currently using a dictionary of column vectors.
2. for NA (not available)
On Monday, 2 November 2015 at 15:33:34 UTC, Laeeth Isharc wrote:
Hi Jay.
That may have been me. I have implemented something very
basic, but you can read and write my proto dataframe to/from
CSV and HDF5. The code is up here:
https://github.com/Laeeth/d_dataframes
yes, thanks. I
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