numpy.recarray¶
- class numpy.recarray¶
Construct an ndarray that allows field access using attributes.
Arrays may have a data-types containing fields, analogous to columns in a spread sheet. An example is [(x, int), (y, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['x'] and arr['y']. Record arrays allow the fields to be accessed as members of the array, using arr.x and arr.y.
Parameters : shape : tuple
Shape of output array.
dtype : data-type, optional
The desired data-type. By default, the data-type is determined from formats, names, titles, aligned and byteorder.
formats : list of data-types, optional
A list containing the data-types for the different columns, e.g. ['i4', 'f8', 'i4']. formats does not support the new convention of using types directly, i.e. (int, float, int). Note that formats must be a list, not a tuple. Given that formats is somewhat limited, we recommend specifying dtype instead.
names : tuple of str, optional
The name of each column, e.g. ('x', 'y', 'z').
buf : buffer, optional
By default, a new array is created of the given shape and data-type. If buf is specified and is an object exposing the buffer interface, the array will use the memory from the existing buffer. In this case, the offset and strides keywords are available.
Returns : rec : recarray
Empty array of the given shape and type.
Other Parameters: titles : tuple of str, optional
Aliases for column names. For example, if names were ('x', 'y', 'z') and titles is ('x_coordinate', 'y_coordinate', 'z_coordinate'), then arr['x'] is equivalent to both arr.x and arr.x_coordinate.
byteorder : {‘<’, ‘>’, ‘=’}, optional
Byte-order for all fields.
aligned : bool, optional
Align the fields in memory as the C-compiler would.
strides : tuple of ints, optional
Buffer (buf) is interpreted according to these strides (strides define how many bytes each array element, row, column, etc. occupy in memory).
offset : int, optional
Start reading buffer (buf) from this offset onwards.
order : {‘C’, ‘F’}, optional
Row-major or column-major order.
See also
- rec.fromrecords
- Construct a record array from data.
- record
- fundamental data-type for recarray.
- format_parser
- determine a data-type from formats, names, titles.
Notes
This constructor can be compared to empty: it creates a new record array but does not fill it with data. To create a record array from data, use one of the following methods:
- Create a standard ndarray and convert it to a record array, using arr.view(np.recarray)
- Use the buf keyword.
- Use np.rec.fromrecords.
Examples
Create an array with two fields, x and y:
>>> x = np.array([(1.0, 2), (3.0, 4)], dtype=[('x', float), ('y', int)]) >>> x array([(1.0, 2), (3.0, 4)], dtype=[('x', '<f8'), ('y', '<i4')])
>>> x['x'] array([ 1., 3.])
View the array as a record array:
>>> x = x.view(np.recarray)
>>> x.x array([ 1., 3.])
>>> x.y array([2, 4])
Create a new, empty record array:
>>> np.recarray((2,), ... dtype=[('x', int), ('y', float), ('z', int)]) rec.array([(-1073741821, 1.2249118382103472e-301, 24547520), (3471280, 1.2134086255804012e-316, 0)], dtype=[('x', '<i4'), ('y', '<f8'), ('z', '<i4')])
Methods
all any argmax argmin argsort astype byteswap choose clip compress conj() Return the complex conjugate, element-wise. conjugate() Return the complex conjugate, element-wise. copy cumprod cumsum diagonal dot dump dumps field fill flatten getfield item itemset max mean min newbyteorder nonzero prod ptp put ravel repeat reshape resize round searchsorted setasflat setfield setflags sort squeeze std sum swapaxes take tofile tolist tostring trace transpose var view
