[SciPy-User] Choosing sub array based on values in a column

Vincent Davis vincent@vincentdavis....
Mon Mar 22 22:00:04 CDT 2010

I feel kinda stupid as I think this must be easier than I am making it.
Below my question you will see an answer I got to a question that I thought
I would be able to complete the last steps my self I was wrong :)

 So if I have an array

Y = np.rec.array([(1.0, 0.0, 3.0, 3.5), (0.0, 0.0, 6.0, 6.5), (1.0, 1.0,
9.0, 9.5)], dtype=[('var1', '<f8'), ('var2', '<f8'), ('var3',
'<f8'), ('var4', '<f8')])

do this works like I would expect


>>>array([(3.0, 3.5), (9.0, 9.5)],

      dtype=[('var3', '<f8'), ('var4', '<f8')])

But I would like to do this,

>>> Y[['var3','var4']][Y['var1']==0 and Y['var2']==0]

Traceback (most recent call last):

  File "<string>", line 1, in <fragment>

ValueError: The truth value of an array with more than one element is
ambiguous. Use a.any() or a.all()

I tried some any() and all() combination but nothing worked. What s the
right way to go about this?



This answer was received on the mail list from Skipper Seabold

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', ''var2','var3'])

You can access the rows like,


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.


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)


Some shortcuts.


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


  *Vincent Davis
720-301-3003 *
 my blog <http://vincentdavis.net> |
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