Merge remote-tracking branch 'upstream/master' into remove-frame-or-series-check

Author: Swanand01

.github/workflows/ci.yml

@@ -7,6 +7,7 @@ on:
     branches:
       - master
       - 1.2.x
+      - 1.3.x
 
 env:
   ENV_FILE: environment.yml

.github/workflows/database.yml

@@ -7,6 +7,9 @@ on:
     branches:
       - master
       - 1.2.x
+      - 1.3.x
+    paths-ignore:
+      - "doc/**"
 
 env:
   PYTEST_WORKERS: "auto"

.github/workflows/posix.yml

@@ -7,6 +7,9 @@ on:
     branches:
       - master
       - 1.2.x
+      - 1.3.x
+    paths-ignore:
+      - "doc/**"
 
 env:
   PYTEST_WORKERS: "auto"

.github/workflows/python-dev.yml

@@ -7,6 +7,8 @@ on:
   pull_request:
     branches:
       - master
+    paths-ignore:
+      - "doc/**"
 
 jobs:
   build:

MANIFEST.in

@@ -17,18 +17,19 @@ global-exclude *.h5
 global-exclude *.html
 global-exclude *.json
 global-exclude *.jsonl
+global-exclude *.msgpack
 global-exclude *.pdf
 global-exclude *.pickle
 global-exclude *.png
 global-exclude *.pptx
-global-exclude *.pyc
-global-exclude *.pyd
 global-exclude *.ods
 global-exclude *.odt
+global-exclude *.orc
 global-exclude *.sas7bdat
 global-exclude *.sav
 global-exclude *.so
 global-exclude *.xls
+global-exclude *.xlsb
 global-exclude *.xlsm
 global-exclude *.xlsx
 global-exclude *.xpt
@@ -39,6 +40,13 @@ global-exclude .DS_Store
 global-exclude .git*
 global-exclude \#*
 
+global-exclude *.c
+global-exclude *.cpp
+global-exclude *.h
+
+global-exclude *.py[ocd]
+global-exclude *.pxi
+
 # GH 39321
 # csv_dir_path fixture checks the existence of the directory
 # exclude the whole directory to avoid running related tests in sdist
@@ -47,3 +55,6 @@ prune pandas/tests/io/parser/data
 include versioneer.py
 include pandas/_version.py
 include pandas/io/formats/templates/*.tpl
+
+graft pandas/_libs/src
+graft pandas/_libs/tslibs/src

azure-pipelines.yml

@@ -1,11 +1,18 @@
 # Adapted from https://github.com/numba/numba/blob/master/azure-pipelines.yml
 trigger:
-- master
-- 1.2.x
+  branches:
+    include:
+    - master
+    - 1.2.x
+    - 1.3.x
+  paths:
+    exclude:
+    - 'doc/*'
 
 pr:
 - master
 - 1.2.x
+- 1.3.x
 
 variables:
   PYTEST_WORKERS: auto

ci/deps/azure-macos-37.yaml

@@ -22,7 +22,7 @@ dependencies:
   - numexpr
   - numpy=1.17.3
   - openpyxl
-  - pyarrow=0.17.0
+  - pyarrow=0.17
   - pytables
   - python-dateutil==2.7.3
   - pytz

doc/source/user_guide/window.rst

@@ -37,14 +37,14 @@ pandas supports 4 types of windowing operations:
 #. Expanding window: Accumulating window over the values.
 #. Exponentially Weighted window: Accumulating and exponentially weighted window over the values.
 
-=============================   =================  ===========================   ===========================  ========================  ===================================
-Concept                         Method             Returned Object               Supports time-based windows  Supports chained groupby  Supports table method
-=============================   =================  ===========================   ===========================  ========================  ===================================
-Rolling window                  ``rolling``        ``Rolling``                   Yes                          Yes                       Yes (as of version 1.3)
-Weighted window                 ``rolling``        ``Window``                    No                           No                        No
-Expanding window                ``expanding``      ``Expanding``                 No                           Yes                       Yes (as of version 1.3)
-Exponentially Weighted window   ``ewm``            ``ExponentialMovingWindow``   No                           Yes (as of version 1.2)   No
-=============================   =================  ===========================   ===========================  ========================  ===================================
+=============================   =================  ===========================   ===========================  ========================  ===================================  ===========================
+Concept                         Method             Returned Object               Supports time-based windows  Supports chained groupby  Supports table method                Supports online operations
+=============================   =================  ===========================   ===========================  ========================  ===================================  ===========================
+Rolling window                  ``rolling``        ``Rolling``                   Yes                          Yes                       Yes (as of version 1.3)              No
+Weighted window                 ``rolling``        ``Window``                    No                           No                        No                                   No
+Expanding window                ``expanding``      ``Expanding``                 No                           Yes                       Yes (as of version 1.3)              No
+Exponentially Weighted window   ``ewm``            ``ExponentialMovingWindow``   No                           Yes (as of version 1.2)   No                                   Yes (as of version 1.3)
+=============================   =================  ===========================   ===========================  ========================  ===================================  ===========================
 
 As noted above, some operations support specifying a window based on a time offset:
 
@@ -98,6 +98,26 @@ be calculated with :meth:`~Rolling.apply` by specifying a separate column of wei
    df = pd.DataFrame([[1, 2, 0.6], [2, 3, 0.4], [3, 4, 0.2], [4, 5, 0.7]])
    df.rolling(2, method="table", min_periods=0).apply(weighted_mean, raw=True, engine="numba")  # noqa:E501
 
+.. versionadded:: 1.3
+
+Some windowing operations also support an ``online`` method after constructing a windowing object
+which returns a new object that supports passing in new :class:`DataFrame` or :class:`Series` objects
+to continue the windowing calculation with the new values (i.e. online calculations).
+
+The methods on this new windowing objects must call the aggregation method first to "prime" the initial
+state of the online calculation. Then, new :class:`DataFrame` or :class:`Series` objects can be passed in
+the ``update`` argument to continue the windowing calculation.
+
+.. ipython:: python
+
+   df = pd.DataFrame([[1, 2, 0.6], [2, 3, 0.4], [3, 4, 0.2], [4, 5, 0.7]])
+   df.ewm(0.5).mean()
+
+.. ipython:: python
+
+   online_ewm = df.head(2).ewm(0.5).online()
+   online_ewm.mean()
+   online_ewm.mean(update=df.tail(1))
 
 All windowing operations support a ``min_periods`` argument that dictates the minimum amount of
 non-``np.nan`` values a window must have; otherwise, the resulting value is ``np.nan``.

doc/source/whatsnew/index.rst

@@ -10,6 +10,14 @@ This is the list of changes to pandas between each release. For full details,
 see the `commit logs <https://github.com/pandas-dev/pandas/commits/>`_. For install and
 upgrade instructions, see :ref:`install`.
 
+Version 1.4
+-----------
+
+.. toctree::
+   :maxdepth: 2
+
+   v1.4.0
+
 Version 1.3
 -----------
 

doc/source/whatsnew/v1.3.0.rst

@@ -239,7 +239,8 @@ For example:
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
 
-- :meth:`DataFrame.rolling`, :meth:`Series.rolling`, :meth:`DataFrame.expanding`, and :meth:`Series.expanding` now support a ``method`` argument with a ``'table'`` option that performs the windowing operation over an entire DataFrame. See :ref:`Window Overview <window.overview>` for performance and functional benefits (:issue:`15095`, :issue:`38995`)
+- :meth:`DataFrame.rolling`, :meth:`Series.rolling`, :meth:`DataFrame.expanding`, and :meth:`Series.expanding` now support a ``method`` argument with a ``'table'`` option that performs the windowing operation over an entire :class:`DataFrame`. See :ref:`Window Overview <window.overview>` for performance and functional benefits (:issue:`15095`, :issue:`38995`)
+- :class:`.ExponentialMovingWindow` now support a ``online`` method that can perform ``mean`` calculations in an online fashion. See :ref:`Window Overview <window.overview>` (:issue:`41673`)
 - Added :meth:`MultiIndex.dtypes` (:issue:`37062`)
 - Added ``end`` and ``end_day`` options for the ``origin`` argument in :meth:`DataFrame.resample` (:issue:`37804`)
 - Improved error message when ``usecols`` and ``names`` do not match for :func:`read_csv` and ``engine="c"`` (:issue:`29042`)