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DOC: move 'Other API changes' under correct section (pandas-dev#34817)
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‎doc/source/whatsnew/v1.1.0.rst

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@@ -297,116 +297,10 @@ Other enhancements
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.. ---------------------------------------------------------------------------
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Increased minimum versions for dependencies
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Some minimum supported versions of dependencies were updated (:issue:`33718`, :issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
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If installed, we now require:
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+-----------------+-----------------+----------+---------+
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| Package | Minimum Version | Required | Changed |
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+=================+=================+==========+=========+
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| numpy | 1.15.4 | X | X |
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+-----------------+-----------------+----------+---------+
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| pytz | 2015.4 | X | |
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+-----------------+-----------------+----------+---------+
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| python-dateutil | 2.7.3 | X | X |
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+-----------------+-----------------+----------+---------+
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| bottleneck | 1.2.1 | | |
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+-----------------+-----------------+----------+---------+
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| numexpr | 2.6.2 | | |
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+-----------------+-----------------+----------+---------+
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| pytest (dev) | 4.0.2 | | |
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+-----------------+-----------------+----------+---------+
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For `optional libraries <https://dev.pandas.io/docs/install.html#dependencies>`_ the general recommendation is to use the latest version.
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The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
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Optional libraries below the lowest tested version may still work, but are not considered supported.
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+-----------------+-----------------+---------+
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| Package | Minimum Version | Changed |
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+=================+=================+=========+
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| beautifulsoup4 | 4.6.0 | |
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+-----------------+-----------------+---------+
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| fastparquet | 0.3.2 | |
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+-----------------+-----------------+---------+
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| gcsfs | 0.2.2 | |
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+-----------------+-----------------+---------+
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| lxml | 3.8.0 | |
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+-----------------+-----------------+---------+
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| matplotlib | 2.2.2 | |
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+-----------------+-----------------+---------+
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| numba | 0.46.0 | |
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+-----------------+-----------------+---------+
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| openpyxl | 2.5.7 | |
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+-----------------+-----------------+---------+
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| pyarrow | 0.13.0 | |
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+-----------------+-----------------+---------+
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| pymysql | 0.7.1 | |
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+-----------------+-----------------+---------+
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| pytables | 3.4.3 | X |
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+-----------------+-----------------+---------+
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| s3fs | 0.3.0 | |
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+-----------------+-----------------+---------+
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| scipy | 1.2.0 | X |
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+-----------------+-----------------+---------+
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| sqlalchemy | 1.1.4 | |
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+-----------------+-----------------+---------+
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| xarray | 0.8.2 | |
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+-----------------+-----------------+---------+
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| xlrd | 1.1.0 | |
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+-----------------+-----------------+---------+
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| xlsxwriter | 0.9.8 | |
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+-----------------+-----------------+---------+
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| xlwt | 1.2.0 | |
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+-----------------+-----------------+---------+
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| pandas-gbq | 1.2.0 | X |
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+-----------------+-----------------+---------+
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See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for more.
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Development Changes
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^^^^^^^^^^^^^^^^^^^
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- The minimum version of Cython is now the most recent bug-fix version (0.29.16) (:issue:`33334`).
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.. _whatsnew_110.api.other:
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Other API changes
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^^^^^^^^^^^^^^^^^
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- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
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will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
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- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
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- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
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- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
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- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``, ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
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- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
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- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
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.. _whatsnew_110.api:
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Backwards incompatible API changes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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- :meth:`DataFrame.swaplevels` now raises a ``TypeError`` if the axis is not a :class:`MultiIndex`.
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Previously an ``AttributeError`` was raised (:issue:`31126`)
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- :meth:`DataFrame.xs` now raises a ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
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Previously an ``AttributeError`` was raised (:issue:`33610`)
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- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
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now raise a ``TypeError`` if a not-accepted keyword argument is passed into it.
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Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
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- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
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- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
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- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
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- Combining a ``Categorical`` with integer categories and which contains missing values
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with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
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will now result in a float column instead of an object dtyped column (:issue:`33607`)
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- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
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- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
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- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
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- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
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(previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
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- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
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- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
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- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)
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``MultiIndex.get_indexer`` interprets `method` argument differently
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -733,6 +627,115 @@ apply and applymap on ``DataFrame`` evaluates first row/column only once
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df.apply(func, axis=1)
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.. _whatsnew_110.api.other:
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Other API changes
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^^^^^^^^^^^^^^^^^
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- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
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will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
637+
- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
638+
- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
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- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
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- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``, ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
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- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
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- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
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- :meth:`DataFrame.swaplevels` now raises a ``TypeError`` if the axis is not a :class:`MultiIndex`.
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Previously an ``AttributeError`` was raised (:issue:`31126`)
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- :meth:`DataFrame.xs` now raises a ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
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Previously an ``AttributeError`` was raised (:issue:`33610`)
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- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
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now raise a ``TypeError`` if a not-accepted keyword argument is passed into it.
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Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
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- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
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- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
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- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
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- Combining a ``Categorical`` with integer categories and which contains missing values
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with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
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will now result in a float column instead of an object dtyped column (:issue:`33607`)
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- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
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- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
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- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
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- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
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(previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
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- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
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- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
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- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)
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Increased minimum versions for dependencies
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Some minimum supported versions of dependencies were updated (:issue:`33718`, :issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
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If installed, we now require:
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+-----------------+-----------------+----------+---------+
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| Package | Minimum Version | Required | Changed |
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+=================+=================+==========+=========+
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| numpy | 1.15.4 | X | X |
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+-----------------+-----------------+----------+---------+
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| pytz | 2015.4 | X | |
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+-----------------+-----------------+----------+---------+
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| python-dateutil | 2.7.3 | X | X |
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+-----------------+-----------------+----------+---------+
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| bottleneck | 1.2.1 | | |
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+-----------------+-----------------+----------+---------+
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| numexpr | 2.6.2 | | |
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+-----------------+-----------------+----------+---------+
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| pytest (dev) | 4.0.2 | | |
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+-----------------+-----------------+----------+---------+
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For `optional libraries <https://dev.pandas.io/docs/install.html#dependencies>`_ the general recommendation is to use the latest version.
689+
The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
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Optional libraries below the lowest tested version may still work, but are not considered supported.
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+-----------------+-----------------+---------+
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| Package | Minimum Version | Changed |
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+=================+=================+=========+
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| beautifulsoup4 | 4.6.0 | |
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+-----------------+-----------------+---------+
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| fastparquet | 0.3.2 | |
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+-----------------+-----------------+---------+
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| gcsfs | 0.2.2 | |
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+-----------------+-----------------+---------+
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| lxml | 3.8.0 | |
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+-----------------+-----------------+---------+
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| matplotlib | 2.2.2 | |
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+-----------------+-----------------+---------+
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| numba | 0.46.0 | |
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+-----------------+-----------------+---------+
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| openpyxl | 2.5.7 | |
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+-----------------+-----------------+---------+
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| pyarrow | 0.13.0 | |
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+-----------------+-----------------+---------+
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| pymysql | 0.7.1 | |
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+-----------------+-----------------+---------+
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| pytables | 3.4.3 | X |
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+-----------------+-----------------+---------+
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| s3fs | 0.3.0 | |
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+-----------------+-----------------+---------+
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| scipy | 1.2.0 | X |
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+-----------------+-----------------+---------+
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| sqlalchemy | 1.1.4 | |
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+-----------------+-----------------+---------+
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| xarray | 0.8.2 | |
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+-----------------+-----------------+---------+
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| xlrd | 1.1.0 | |
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+-----------------+-----------------+---------+
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| xlsxwriter | 0.9.8 | |
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+-----------------+-----------------+---------+
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| xlwt | 1.2.0 | |
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+-----------------+-----------------+---------+
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| pandas-gbq | 1.2.0 | X |
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+-----------------+-----------------+---------+
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See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for more.
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Development Changes
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^^^^^^^^^^^^^^^^^^^
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- The minimum version of Cython is now the most recent bug-fix version (0.29.16) (:issue:`33334`).
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.. _whatsnew_110.deprecations:
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