Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

API: remove the table keyword, replaced by fmt='s|t' #4645

Merged
merged 3 commits into from
Aug 26, 2013
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 3 additions & 2 deletions doc/source/io.rst
Original file line number Diff line number Diff line change
Expand Up @@ -1803,6 +1803,7 @@ The examples above show storing using ``put``, which write the HDF5 to ``PyTable
the ``storer`` format. These types of stores are are **not** appendable once written (though you can simply
remove them and rewrite). Nor are they **queryable**; they must be
retrieved in their entirety. These offer very fast writing and slightly faster reading than ``table`` stores.
This format is specified by default when using ``put`` or by ``fmt='s'``

.. warning::

Expand All @@ -1826,7 +1827,7 @@ Table Format
format. Conceptually a ``table`` is shaped very much like a DataFrame,
with rows and columns. A ``table`` may be appended to in the same or
other sessions. In addition, delete & query type operations are
supported.
supported. This format is specified by ``fmt='t'`` to ``append`` or ``put``.

.. ipython:: python
:suppress:
Expand All @@ -1853,7 +1854,7 @@ supported.

.. note::

You can also create a ``table`` by passing ``table=True`` to a ``put`` operation.
You can also create a ``table`` by passing ``fmt='t'`` to a ``put`` operation.

.. _io.hdf5-keys:

Expand Down
2 changes: 2 additions & 0 deletions doc/source/release.rst
Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,7 @@ pandas 0.13
- removed the ``warn`` argument from ``open``. Instead a ``PossibleDataLossError`` exception will
be raised if you try to use ``mode='w'`` with an OPEN file handle (:issue:`4367`)
- allow a passed locations array or mask as a ``where`` condition (:issue:`4467`)
- the ``fmt`` keyword now replaces the ``table`` keyword; allowed values are ``s|t``
- ``JSON``

- added ``date_unit`` parameter to specify resolution of timestamps. Options
Expand Down Expand Up @@ -200,6 +201,7 @@ See :ref:`Internal Refactoring<whatsnew_0130.refactoring>`
with a different block ordering (:issue:`4096`)
- ``read_hdf`` was not respecting as passed ``mode`` (:issue:`4504`)
- appending a 0-len table will work correctly (:issue:`4273`)
- ``to_hdf`` was raising when passing both arguments ``append`` and ``table`` (:issue:`4584`)
- Fixed bug in tslib.tz_convert(vals, tz1, tz2): it could raise IndexError exception while
trying to access trans[pos + 1] (:issue:`4496`)
- The ``by`` argument now works correctly with the ``layout`` argument
Expand Down
20 changes: 20 additions & 0 deletions doc/source/v0.13.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -66,13 +66,33 @@ API changes
store2.close()
store2

.. ipython:: python
:suppress:

import os
os.remove(path)

- removed the ``_quiet`` attribute, replace by a ``DuplicateWarning`` if retrieving
duplicate rows from a table (:issue:`4367`)
- removed the ``warn`` argument from ``open``. Instead a ``PossibleDataLossError`` exception will
be raised if you try to use ``mode='w'`` with an OPEN file handle (:issue:`4367`)
- allow a passed locations array or mask as a ``where`` condition (:issue:`4467`).
See :ref:`here<io.hdf5-where_mask>` for an example.

- the ``fmt`` keyword now replaces the ``table`` keyword; allowed values are ``s|t``
the same defaults as prior < 0.13.0 remain, e.g. ``put`` implies 's' (Storer) format
and ``append`` imples 't' (Table) format

.. ipython:: python

path = 'test.h5'
df = DataFrame(randn(10,2))
df.to_hdf(path,'df_table',fmt='t')
df.to_hdf(path,'df_table2',append=True)
df.to_hdf(path,'df_storer')
with get_store(path) as store:
print store

.. ipython:: python
:suppress:

Expand Down
Loading