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numpy.recarray
class numpy.recarray[source]-
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 asarr['x']andarr['y']. Record arrays allow the fields to be accessed as members of the array, usingarr.xandarr.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,alignedandbyteorder. -
formats : list of data-types, optional -
A list containing the data-types for the different columns, e.g.
['i4', 'f8', 'i4'].formatsdoes not support the new convention of using types directly, i.e.(int, float, int). Note thatformatsmust be a list, not a tuple. Given thatformatsis somewhat limited, we recommend specifyingdtypeinstead. -
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
bufis specified and is an object exposing the buffer interface, the array will use the memory from the existing buffer. In this case, theoffsetandstrideskeywords 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
nameswere('x', 'y', 'z')andtitlesis('x_coordinate', 'y_coordinate', 'z_coordinate'), thenarr['x']is equivalent to botharr.xandarr.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 (C-style) or column-major (Fortran-style) 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
bufkeyword. - Use
np.rec.fromrecords.
Examples
Create an array with two fields,
xandy:>>> x = np.array([(1.0, 2), (3.0, 4)], dtype=[('x', '<f8'), ('y', '<i8')]) >>> x array([(1., 2), (3., 4)], dtype=[('x', '<f8'), ('y', '<i8')])>>> 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)]) #doctest: +SKIP rec.array([(-1073741821, 1.2249118382103472e-301, 24547520), (3471280, 1.2134086255804012e-316, 0)], dtype=[('x', '<i4'), ('y', '<f8'), ('z', '<i4')])Attributes: -
T -
The transposed array.
-
base -
Base object if memory is from some other object.
-
ctypes -
An object to simplify the interaction of the array with the ctypes module.
-
data -
Python buffer object pointing to the start of the array’s data.
-
dtype -
Data-type of the array’s elements.
-
flags -
Information about the memory layout of the array.
-
flat -
A 1-D iterator over the array.
-
imag -
The imaginary part of the array.
-
itemsize -
Length of one array element in bytes.
-
nbytes -
Total bytes consumed by the elements of the array.
-
ndim -
Number of array dimensions.
-
real -
The real part of the array.
-
shape -
Tuple of array dimensions.
-
size -
Number of elements in the array.
-
strides -
Tuple of bytes to step in each dimension when traversing an array.
Methods
all([axis, out, keepdims])Returns True if all elements evaluate to True. any([axis, out, keepdims])Returns True if any of the elements of aevaluate to True.argmax([axis, out])Return indices of the maximum values along the given axis. argmin([axis, out])Return indices of the minimum values along the given axis of a.argpartition(kth[, axis, kind, order])Returns the indices that would partition this array. argsort([axis, kind, order])Returns the indices that would sort this array. astype(dtype[, order, casting, subok, copy])Copy of the array, cast to a specified type. byteswap([inplace])Swap the bytes of the array elements choose(choices[, out, mode])Use an index array to construct a new array from a set of choices. clip([min, max, out])Return an array whose values are limited to [min, max].compress(condition[, axis, out])Return selected slices of this array along given axis. conj()Complex-conjugate all elements. conjugate()Return the complex conjugate, element-wise. copy([order])Return a copy of the array. cumprod([axis, dtype, out])Return the cumulative product of the elements along the given axis. cumsum([axis, dtype, out])Return the cumulative sum of the elements along the given axis. diagonal([offset, axis1, axis2])Return specified diagonals. dot(b[, out])Dot product of two arrays. dump(file)Dump a pickle of the array to the specified file. dumps()Returns the pickle of the array as a string. fill(value)Fill the array with a scalar value. flatten([order])Return a copy of the array collapsed into one dimension. getfield(dtype[, offset])Returns a field of the given array as a certain type. item(*args)Copy an element of an array to a standard Python scalar and return it. itemset(*args)Insert scalar into an array (scalar is cast to array’s dtype, if possible) max([axis, out, keepdims, initial, where])Return the maximum along a given axis. mean([axis, dtype, out, keepdims])Returns the average of the array elements along given axis. min([axis, out, keepdims, initial, where])Return the minimum along a given axis. newbyteorder([new_order])Return the array with the same data viewed with a different byte order. nonzero()Return the indices of the elements that are non-zero. partition(kth[, axis, kind, order])Rearranges the elements in the array in such a way that the value of the element in kth position is in the position it would be in a sorted array. prod([axis, dtype, out, keepdims, initial, …])Return the product of the array elements over the given axis ptp([axis, out, keepdims])Peak to peak (maximum - minimum) value along a given axis. put(indices, values[, mode])Set a.flat[n] = values[n]for allnin indices.ravel([order])Return a flattened array. repeat(repeats[, axis])Repeat elements of an array. reshape(shape[, order])Returns an array containing the same data with a new shape. resize(new_shape[, refcheck])Change shape and size of array in-place. round([decimals, out])Return awith each element rounded to the given number of decimals.searchsorted(v[, side, sorter])Find indices where elements of v should be inserted in a to maintain order. setfield(val, dtype[, offset])Put a value into a specified place in a field defined by a data-type. setflags([write, align, uic])Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY), respectively. sort([axis, kind, order])Sort an array in-place. squeeze([axis])Remove single-dimensional entries from the shape of a.std([axis, dtype, out, ddof, keepdims])Returns the standard deviation of the array elements along given axis. sum([axis, dtype, out, keepdims, initial, where])Return the sum of the array elements over the given axis. swapaxes(axis1, axis2)Return a view of the array with axis1andaxis2interchanged.take(indices[, axis, out, mode])Return an array formed from the elements of aat the given indices.tobytes([order])Construct Python bytes containing the raw data bytes in the array. tofile(fid[, sep, format])Write array to a file as text or binary (default). tolist()Return the array as an a.ndim-levels deep nested list of Python scalars.tostring([order])Construct Python bytes containing the raw data bytes in the array. trace([offset, axis1, axis2, dtype, out])Return the sum along diagonals of the array. transpose(*axes)Returns a view of the array with axes transposed. var([axis, dtype, out, ddof, keepdims])Returns the variance of the array elements, along given axis. view([dtype, type])New view of array with the same data. field -
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.recarray.html