[Numpy-discussion] datarray -- a couple of questions

[Wes McKinney]

On Sun, May 22, 2011 at 10:49 AM, Ben Walsh <ben_w_123 at yahoo.co.uk> wrote:
> Hi
>
> I've been looking at various labelled-array packages, including Pandas
> (https://github.com/wesm/pandas) and datarray
> (https://github.com/fperez/datarray).
>
> I was quite interested in the design discussion for datarray, and I had
> a couple of questions:
>
> 1) Is this mailing list the correct place to ask about this?
>
> 2) Pandas supports mixed data types (eg. one column of floats, another
> column of strings). Does the datarray prototype support this? Is it
> simply a case of using a numpy.ndarray with dtype='object'?
>
> Cheers
>
> Ben
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>

hi Ben,

others can comment, but I think the answer to 1) is yes (if you have
more specific usage questions about pandas feel free to ask on
pystatsmodels, too).

2) datarray as currently conceived as a homogeneously typed object. So
you could use dtype=object but occasionally have computational snafus.
pandas tries to avoid these problems by segregating the floating point
and non-floating point data. In recent discussions I do not think
datarray is intended to be a step-in replacement for something like
pandas, which is geared toward solving a bit more domain-specific set
of problems (e.g. R-like data manipulations, time series / finance
work, etc.). Rather, a future version of pandas will use datarray as
its "base layer". So if you're looking for an (R) data.frame - like
container, pandas.{DataFrame, DataMatrix} is probably your best bet
for now

larry is also worth looking at. But like datarray is also does not
"do" mixed-type data.

cheers,
Wes