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Merge remote-tracking branch 'upstream/master' into df_set_index_warn
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.travis.yml

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- dist: trusty
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env:
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- JOB="3.6, coverage" ENV_FILE="ci/travis-36.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate" COVERAGE=true DOCTEST=true
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# In allow_failures
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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# In allow_failures
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- dist: trusty
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env:
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- JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
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addons:
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apt:
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packages:
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- xsel
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# In allow_failures
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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# In allow_failures
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- dist: trusty
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env:
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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- dist: trusty
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env:
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- JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
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addons:
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apt:
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packages:
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- xsel
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- dist: trusty
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- JOB="3.6, doc" ENV_FILE="ci/travis-36-doc.yaml" DOC=true

README.md

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@@ -97,7 +97,7 @@ easy and intuitive. It aims to be the fundamental high-level building block for
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doing practical, **real world** data analysis in Python. Additionally, it has
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the broader goal of becoming **the most powerful and flexible open source data
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analysis / manipulation tool available in any language**. It is already well on
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its way toward this goal.
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its way towards this goal.
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## Main Features
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Here are just a few of the things that pandas does well:

asv_bench/benchmarks/indexing.py

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import numpy as np
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import pandas.util.testing as tm
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from pandas import (Series, DataFrame, MultiIndex, Int64Index, Float64Index,
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IntervalIndex, CategoricalIndex,
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IndexSlice, concat, date_range)
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from .pandas_vb_common import setup, Panel # noqa
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from pandas import (Series, DataFrame, MultiIndex, Panel,
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Int64Index, Float64Index, IntervalIndex,
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CategoricalIndex, IndexSlice, concat, date_range)
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from .pandas_vb_common import setup # noqa
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class NumericSeriesIndexing(object):

asv_bench/benchmarks/join_merge.py

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import numpy as np
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import pandas.util.testing as tm
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from pandas import (DataFrame, Series, MultiIndex, date_range, concat, merge,
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merge_asof)
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from pandas import (DataFrame, Series, Panel, MultiIndex,
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date_range, concat, merge, merge_asof)
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try:
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from pandas import merge_ordered
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except ImportError:
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from pandas import ordered_merge as merge_ordered
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from .pandas_vb_common import Panel, setup # noqa
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from .pandas_vb_common import setup # noqa
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class Append(object):

asv_bench/benchmarks/panel_ctor.py

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import warnings
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from datetime import datetime, timedelta
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from pandas import DataFrame, DatetimeIndex, date_range
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from pandas import DataFrame, Panel, DatetimeIndex, date_range
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from .pandas_vb_common import Panel, setup # noqa
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from .pandas_vb_common import setup # noqa
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class DifferentIndexes(object):

asv_bench/benchmarks/panel_methods.py

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import warnings
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import numpy as np
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from pandas import Panel
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from .pandas_vb_common import Panel, setup # noqa
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from .pandas_vb_common import setup # noqa
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class PanelMethods(object):

ci/travis-36-doc.yaml

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- html5lib
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- hypothesis>=3.58.0
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- ipykernel
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- ipython
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- ipython==6.5.0
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- ipywidgets
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- lxml
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- matplotlib

doc/source/contributing.rst

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.. code-block:: python
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with tm.assert_prodcues_warning(FutureWarning):
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with tm.assert_produces_warning(FutureWarning):
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df.some_operation()
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We prefer this to the ``pytest.warns`` context manager because ours checks that the warning's

doc/source/whatsnew/v0.24.0.txt

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Backwards incompatible API changes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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- A newly constructed empty :class:`DataFrame` with integer as the ``dtype`` will now only be cast to ``float64`` if ``index`` is specified (:issue:`22858`)
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- :meth:`Series.astype` and :meth:`DataFrame.astype` now dispatch to :meth:`ExtensionArray.astype` (:issue:`21185:`).
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- Slicing a single row of a ``DataFrame`` with multiple ExtensionArrays of the same type now preserves the dtype, rather than coercing to object (:issue:`22784`)
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- Added :meth:`pandas.api.types.register_extension_dtype` to register an extension type with pandas (:issue:`22664`)
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- Updated the ``.type`` attribute for ``PeriodDtype``, ``DatetimeTZDtype``, and ``IntervalDtype`` to be instances of the dtype (``Period``, ``Timestamp``, and ``Interval`` respectively) (:issue:`22938`)
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- Bug in :meth:`DataFrame.drop_duplicates` for empty ``DataFrame`` which incorrectly raises an error (:issue:`20516`)
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- Bug in :func:`pandas.wide_to_long` when a string is passed to the stubnames argument and a column name is a substring of that stubname (:issue:`22468`)
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- Bug in :func:`merge` when merging ``datetime64[ns, tz]`` data that contained a DST transition (:issue:`18885`)
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- Bug in :func:`merge_asof` when merging on float values within defined tolerance (:issue:`22981`)
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Build Changes
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^^^^^^^^^^^^^

pandas/_libs/algos_common_helper.pxi.in

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Template for each `dtype` helper function using 1-d template
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# 1-d template
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- map_indices
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- pad
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- pad_1d
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- pad_2d

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