[SciPy-User] accessing a set of columns from a recarray

Vincent Davis vincent@vincentdavis....
Sun Mar 21 23:18:03 CDT 2010


I am a little puzzeled by this
>>> data2[list(typeallnames)][0][0]
171.0
>>> data2[list(typeallnames)][0][0]=0
>>> data2[list(typeallnames)][0][0]
171.0

How do I change the value?

  *Vincent Davis
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vincent@vincentdavis.net
 my blog <http://vincentdavis.net> |
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On Sun, Mar 21, 2010 at 8:33 PM, Skipper Seabold <jsseabold@gmail.com>wrote:

> On Sun, Mar 21, 2010 at 10:20 PM, Vincent Davis
> <vincent@vincentdavis.net> wrote:
> >
> > To many distractions let me try to write that a little better.
> > I have a record array and a list of columns for which I would like to get
> the row means. My current solution is to iterate though the list of column
> names and make a new "normal" array. then calculate the row means. I would
> like to do something like np.mean(A['x','y','z']) where x,y,z are the tiles
> of the columns
> >
>
> If you have a rec array
>
> Y = np.rec.array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0), (7.0, 8.0, 9.0)],
>      dtype=[('var1', '<f8'), ('var2', '<f8'), ('var3', '<f8')])
>
> You can access the rows like,
>
> Y[['var1','var2','var3']]
>
> Note the list within [].
>
> If you want a "normal" array, I like this way that Pierre recently
> pointed out.  3 is the number of columns, and it fills in the number
> of rows.
>
> Y[['var1','var2','var3']].view((float,3))
>
> note the tuple for the view, if they're all floats.  Taking a view
> might not work if var# have different types, like ints and floats.
>
> If you want the mean of the rows (mean over the columns axis = 1)
>
> Y[['var1','var2','var3']].view((float,3)).mean(1)
>
> Some shortcuts.
>
> Y[list(Y.dtype.names)].view((float,len(Y.dtype))).mean(1)
>
> Also, for now, the columns will given back to you in the order they're
> in in the array no matter which way you ask for them.  A patch has
> been submitted for returning the order you ask that I hope gets picked
> up...
>
> Skipper
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