On Sun, Dec 5, 2010 at 10:44 PM, Wai Yip Tung <tungwaiyip@yahoo.com> wrote:

I'm trying to use numpy to manipulate CSV file. I'm looking for feature similar to relational database. So I come across a class recarray that seems to meet my need. And then I see other references of structured array. Are these just different name of the same feature?

Also I encounter a problem trying to access an field by attribute name. I have

In [303]: arr = np.array([    .....:     (1, 2.2, 0.0),    .....:     (3, 4.5, 0.0)    .....:     ],    .....:     dtype=[    .....:         ('unit',int),    .....:         ('price',float),    .....:         ('amount',float),    .....:     ]    .....: )

In [304]: data0 = arr.view(recarray)

In [305]: data0.price[0] Out[305]: 2.2000000000000002

You don't have to take a view as a recarray if you don't want to. You lose attribute lookup but gain some speed. In [14]: arr['price'] Out[14]: array([ 2.2, 4.5])

It works fine when I get a price vector and pick the first element of it. But if instead I select the first row and try to access its price attribute, it wouldn't work

I'm not sure why this doesn't work. It looks like taking a view of the structured array as a recarray does not cast the structs to records Is this a bug? Note that you can do In [19]: arr[0]['price'] Out[19]: 2.2000000000000002 In [20]: data0[0]['price'] Out[20]: 2.2000000000000002 also slicing seems to work In [27]: data0[0:1].price Out[27]: array([ 2.2]) Skipper

In [306]: data0[0].price --------------------------------------------------------------------------- AttributeError                            Traceback (most recent call last)

c:\Python26\Lib\site-packages\numpy\<ipython console> in <module>()

AttributeError: 'numpy.void' object has no attribute 'price'

Then I come across an alternative way to build a recarray. In that case both usage work fine.

In [307]: data1 = np.rec.fromarrays(    .....:     [[1,3],[2.2,4.5],[0.0,0.0]],    .....:     names='unit,price,amount')

In [309]: data1.price[0] Out[309]: 2.2000000000000002

In [310]: data1[0].price Out[310]: 2.2000000000000002

What's going on here?

Wai Yip

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