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Diffstat (limited to 'doc/source/reference/arrays.indexing.rst')
| -rw-r--r-- | doc/source/reference/arrays.indexing.rst | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/doc/source/reference/arrays.indexing.rst b/doc/source/reference/arrays.indexing.rst index ef0180e0f..2eb07c4e0 100644 --- a/doc/source/reference/arrays.indexing.rst +++ b/doc/source/reference/arrays.indexing.rst @@ -11,7 +11,7 @@ Indexing :class:`ndarrays <ndarray>` can be indexed using the standard Python ``x[obj]`` syntax, where *x* is the array and *obj* the selection. -There are three kinds of indexing available: record access, basic +There are three kinds of indexing available: field access, basic slicing, advanced indexing. Which one occurs depends on *obj*. .. note:: @@ -489,25 +489,25 @@ indexing (in no particular order): view on the data. This *must* be done if the subclasses ``__getitem__`` does not return views. -.. _arrays.indexing.rec: +.. _arrays.indexing.fields: -Record Access +Field Access ------------- .. seealso:: :ref:`arrays.dtypes`, :ref:`arrays.scalars` -If the :class:`ndarray` object is a record array, *i.e.* its data type -is a :term:`record` data type, the :term:`fields <field>` of the array -can be accessed by indexing the array with strings, dictionary-like. +If the :class:`ndarray` object is a structured array the :term:`fields <field>` +of the array can be accessed by indexing the array with strings, +dictionary-like. Indexing ``x['field-name']`` returns a new :term:`view` to the array, which is of the same shape as *x* (except when the field is a sub-array) but of data type ``x.dtype['field-name']`` and contains -only the part of the data in the specified field. Also record array -scalars can be "indexed" this way. +only the part of the data in the specified field. Also +:ref:`record array <arrays.classes.rec>` scalars can be "indexed" this way. -Indexing into a record array can also be done with a list of field names, +Indexing into a structured array can also be done with a list of field names, *e.g.* ``x[['field-name1','field-name2']]``. Currently this returns a new array containing a copy of the values in the fields specified in the list. As of NumPy 1.7, returning a copy is being deprecated in favor of returning |