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numarray
User's Manual |
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numarray over Numeric is its
support for record arrays, i.e. arrays with heterogeneous data types:
for example, tabulated data where each field (or column) has the
same data type but different fields may not.
Each record array is a RecArray object in the
numarray.records module. Most of
the time, the easiest way to construct a record array is to use the
array() function in the numarray.records module. For example:
>>> import numarray.records as rec
>>> r = rec.array([('Smith', 1234),\
('Johnson', 1001),\
('Williams', 1357),\
('Miller', 2468)], \
names='Last_name, phone_number')
names argument.
When using this longhand input, the data types (formats) are
automatically determined from the data. In this case the first field is a
string of 8 characters (since the longest name is 8 characters long) and
the second field is an integer.
The record array is just like an array in numarray, except that now each
element is a Record. We can do the usual indexing and slicing:
>>> print r[0]
('Smith', 1234)
>>> print r[:2]
RecArray[
('Smith', 1234),
('Johnson', 1001)
]
field() method:
>>> print r.field(0)
['Smith', 'Johnson', 'Williams', 'Miller']
>>> print r.field('Last_name')
['Smith', 'Johnson', 'Williams', 'Miller']
field method can accept either the
numeric index or the field name.
Since each field is simply a numarray of numbers or strings, all functionalities of numarray are available to them. The record array is one single object which allows the user to have either field-wise or row-wise access. The following example:
>>> r.field('phone_number')[1]=9999
>>> print r[:2]
RecArray[
('Smith', 1234),
('Johnson', 9999)
]
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numarray
User's Manual |
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