Module ImportFrom alias alias alias ImportFrom alias alias ImportFrom alias alias alias ImportFrom alias FunctionDef arguments args NameParam defaults body Import alias identifier Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad Call NameLoad NameLoad NameLoad Assign NameStore Call NameLoad NameLoad Assign NameStore AttributeLoad Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad attr Assign AttributeStore NameLoad attr NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Import alias identifier If CompareIs NameLoad NameLoad body Assign NameStore Call NameLoad NameLoad orelse If Call NameLoad NameLoad NameLoad body Assign NameStore ListComp Call AttributeLoad NameLoad attr comprehension NameStore Call AttributeLoad NameLoad attr Str Assign NameStore ListComp TupleLoad NameLoad NameLoad comprehension TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad orelse If BoolOpAnd Call NameLoad NameLoad NameLoad BoolOpOr CompareNotIn Str NameLoad CompareNotIn Str NameLoad body Assign NameStore Call NameLoad NameLoad Assign NameStore Dict Str Str ListLoad ListLoad For NameStore NameLoad body Expr Call AttributeLoad SubscriptLoad NameLoad Index Str attr NameLoad If BoolOpAnd CompareIn NameLoad NameLoad Call NameLoad SubscriptLoad NameLoad Index NameLoad NameLoad body Expr Call AttributeLoad SubscriptLoad NameLoad Index Str attr SubscriptLoad SubscriptLoad NameLoad Index NameLoad Index Num orelse If CompareNotIn NameLoad NameLoad body Assign NameStore Call AttributeLoad NameLoad attr SubscriptLoad NameLoad Index NameLoad Expr Call AttributeLoad SubscriptLoad NameLoad Index Str attr AttributeLoad NameLoad attr orelse Expr Call AttributeLoad SubscriptLoad NameLoad Index Str attr SubscriptLoad NameLoad Index NameLoad Assign NameStore NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults NameLoad Num Num body Expr Str Import alias identifier Assign NameStore Call NameLoad NameLoad Assign TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad Call NameLoad NameLoad NameLoad Assign NameStore Call NameLoad NameLoad NameLoad NameLoad Assign NameStore GeneratorExp Call NameLoad NameLoad comprehension NameStore NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword NameLoad keyword NameLoad Return NameLoad decorator_list Assign AttributeStore NameLoad attr NameLoad FunctionDef arguments args defaults vararg kwarg body Expr Str Import alias identifier Return Call AttributeLoad Call NameLoad NameLoad NameLoad attr AttributeLoad NameLoad attr decorator_list Assign AttributeStore NameLoad attr NameLoad FunctionDef arguments args NameParam defaults body Expr Str Return Call NameLoad NameLoad decorator_list ClassDef bases NameLoad body FunctionDef arguments args NameParam NameParam defaults body Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam defaults body Expr Yield Call NameLoad AttributeLoad AttributeLoad AttributeLoad NameLoad attr attr attr For NameStore AttributeLoad NameLoad attr body Expr Yield Call NameLoad NameLoad decorator_list decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults NameLoad Num Num body Expr Str Import alias identifier Assign NameStore Call NameLoad NameLoad If CompareIs NameLoad NameLoad body Assign TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad Assign NameStore AttributeLoad Call AttributeLoad NameLoad attr NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword NameLoad keyword NameLoad Return NameLoad decorator_list Assign AttributeStore NameLoad attr NameLoad Assign AttributeStore NameLoad attr NameLoad
N/A __future__ division print_function absolute_import petl.compat next string_types petl.util.base iterpeek ValuesView Table petl.util.materialise columns infer_dtype N/A N/A table N/A N/A N/A numpy np N/A it N/A iter table N/A hdr N/A next it N/A flds N/A list N/A map str hdr N/A rows N/A tuple it N/A dtype N/A N/A N/A N/A np rec array rows dtype N/A N/A dtype names flds N/A dtype N/A construct_dtype N/A N/A flds peek dtype N/A N/A N/A numpy np N/A N/A dtype None N/A N/A dtype N/A infer_dtype peek N/A N/A N/A isinstance dtype string_types N/A N/A typestrings N/A N/A N/A s strip N/A s N/A N/A dtype split , N/A dtype N/A N/A f t N/A N/A f t N/A zip flds typestrings N/A N/A N/A N/A isinstance dtype dict N/A N/A names dtype N/A formats dtype N/A N/A cols N/A columns peek N/A newdtype N/A names formats N/A N/A N/A f flds N/A N/A N/A N/A N/A newdtype N/A names append f N/A N/A N/A f dtype N/A isinstance N/A dtype N/A f tuple N/A N/A N/A N/A N/A newdtype N/A formats append N/A N/A dtype N/A f N/A 0 N/A N/A N/A f dtype N/A N/A a N/A N/A np array N/A cols N/A f N/A N/A N/A N/A newdtype N/A formats append N/A a dtype N/A N/A N/A N/A N/A newdtype N/A formats append N/A dtype N/A f N/A dtype newdtype N/A dtype N/A toarray N/A N/A table dtype count sample N/A None -1 1000 N/A N/A 
    Load data from the given `table` into a
    `numpy <http://www.numpy.org/>`_ structured array. E.g.::

        >>> import petl as etl
        >>> table = [('foo', 'bar', 'baz'),
        ...          ('apples', 1, 2.5),
        ...          ('oranges', 3, 4.4),
        ...          ('pears', 7, .1)]
        >>> a = etl.toarray(table)
        >>> a
        array([('apples', 1, 2.5), ('oranges', 3, 4.4), ('pears', 7, 0.1)],
              dtype=(numpy.record, [('foo', '<U7'), ('bar', '<i8'), ('baz', '<f8')]))
        >>> # the dtype can be specified as a string
        ... a = etl.toarray(table, dtype='a4, i2, f4')
        >>> a
        array([(b'appl', 1, 2.5), (b'oran', 3, 4.400000095367432),
               (b'pear', 7, 0.10000000149011612)],
              dtype=[('foo', 'S4'), ('bar', '<i2'), ('baz', '<f4')])
        >>> # the dtype can also be partially specified
        ... a = etl.toarray(table, dtype={'foo': 'a4'})
        >>> a
        array([(b'appl', 1, 2.5), (b'oran', 3, 4.4), (b'pear', 7, 0.1)],
              dtype=[('foo', 'S4'), ('bar', '<i8'), ('baz', '<f8')])

    If the dtype is not completely specified, `sample` rows will be
    examined to infer an appropriate dtype.

     N/A numpy np N/A it N/A iter table N/A N/A peek it N/A iterpeek it sample N/A hdr N/A next it N/A flds N/A list N/A map str hdr N/A dtype N/A construct_dtype flds peek dtype N/A it N/A N/A tuple row N/A row it N/A sa N/A N/A np fromiter it dtype dtype count count N/A sa N/A N/A N/A Table toarray toarray torecarray N/A N/A N/A args kwargs N/A N/A 
    Convenient shorthand for ``toarray(*args, **kwargs).view(np.recarray)``.

     N/A numpy np N/A N/A N/A N/A toarray args kwargs view N/A np recarray N/A N/A N/A Table torecarray torecarray fromarray N/A N/A a N/A N/A N/A 
    Extract a table from a `numpy <http://www.numpy.org/>`_ structured array,
    e.g.::

        >>> import petl as etl
        >>> import numpy as np
        >>> a = np.array([('apples', 1, 2.5),
        ...               ('oranges', 3, 4.4),
        ...               ('pears', 7, 0.1)],
        ...              dtype='U8, i4,f4')
        >>> table = etl.fromarray(a)
        >>> table
        +-----------+----+-----------+
        | f0        | f1 | f2        |
        +===========+====+===========+
        | 'apples'  | 1  | 2.5       |
        +-----------+----+-----------+
        | 'oranges' | 3  | 4.4000001 |
        +-----------+----+-----------+
        | 'pears'   | 7  | 0.1       |
        +-----------+----+-----------+
    
     N/A N/A ArrayView a N/A ArrayView N/A Table N/A __init__ N/A N/A self a N/A N/A N/A N/A self a a N/A __iter__ N/A N/A self N/A N/A N/A N/A N/A tuple N/A N/A N/A self a dtype names N/A row N/A self a N/A N/A N/A N/A tuple row N/A N/A valuestoarray N/A N/A vals dtype count sample N/A None -1 1000 N/A N/A 
    Load values from a table column into a `numpy <http://www.numpy.org/>`_
    array, e.g.::

        >>> import petl as etl
        >>> table = [('foo', 'bar', 'baz'),
        ...          ('apples', 1, 2.5),
        ...          ('oranges', 3, 4.4),
        ...          ('pears', 7, .1)]
        >>> table = etl.wrap(table)
        >>> table.values('bar').array()
        array([1, 3, 7])
        >>> # specify dtype
        ... table.values('bar').array(dtype='i4')
        array([1, 3, 7], dtype=int32)

     N/A numpy np N/A it N/A iter vals N/A N/A dtype None N/A N/A N/A peek it N/A iterpeek it sample N/A dtype N/A N/A N/A np array peek dtype N/A a N/A N/A np fromiter it dtype dtype count count N/A a N/A N/A N/A ValuesView toarray valuestoarray N/A N/A ValuesView array valuestoarray