parsing tab separated data efficiently into numpy/pylab arrays

[mapb81 at googlemail.com]

You could take a look/use the very handy csv2rec function in
matplotlib.mlab, which creates numpy struct arrays.

Marco

On Mar 13, 10:19 pm, per <perfr... at gmail.com> wrote:
> hi all,
>
> what's the most efficient / preferred python way ofparsingtab
> separated data intoarrays? for example if i have a file containing
> two columns one corresponding to names the other numbers:
>
> col1    \t     col 2
> joe    \t  12.3
> jane   \t 155.0
>
> i'd like to parse into an array() such that i can do: mydata[:, 0] and
> mydata[:, 1] to easily access all the columns.
>
> right now i can iterate through the file, parse it manually using the
> split('\t') command and construct a list out of it, then convert it toarrays. but there must be a better way?
>
> also, my first column is just a name, and so it is variable in length
> -- is there still a way to store it as an array so i can access: mydata
> [:, 0] to get all the names (as a list)?
>
> thank you.