Merge branch 'master' of https://github.com/pandas-dev/pandas into Series.searchsorted_api

Author: topper-123

.github/CONTRIBUTING.md

@@ -1,24 +1,23 @@
-Contributing to pandas
-======================
+# Contributing to pandas
 
 Whether you are a novice or experienced software developer, all contributions and suggestions are welcome!
 
-Our main contribution docs can be found [here](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst), but if you do not want to read it in its entirety, we will summarize the main ways in which you can contribute and point to relevant places in the docs for further information.
+Our main contributing guide can be found [in this repo](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst) or [on the website](https://pandas-docs.github.io/pandas-docs-travis/contributing.html). If you do not want to read it in its entirety, we will summarize the main ways in which you can contribute and point to relevant sections of that document for further information.
+
+## Getting Started
 
-Getting Started
----------------
 If you are looking to contribute to the *pandas* codebase, the best place to start is the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues). This is also a great place for filing bug reports and making suggestions for ways in which we can improve the code and documentation.
 
-If you have additional questions, feel free to ask them on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Gitter](https://gitter.im/pydata/pandas). Further information can also be found in our [Getting Started](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#where-to-start) section of our main contribution doc.
+If you have additional questions, feel free to ask them on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Gitter](https://gitter.im/pydata/pandas). Further information can also be found in the "[Where to start?](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#where-to-start)" section.
+
+## Filing Issues
+
+If you notice a bug in the code or documentation, or have suggestions for how we can improve either, feel free to create an issue on the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) using [GitHub's "issue" form](https://github.com/pandas-dev/pandas/issues/new). The form contains some questions that will help us best address your issue. For more information regarding how to file issues against *pandas*, please refer to the "[Bug reports and enhancement requests](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#bug-reports-and-enhancement-requests)" section.
 
-Filing Issues
--------------
-If you notice a bug in the code or in docs or have suggestions for how we can improve either, feel free to create an issue on the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) using [GitHub's "issue" form](https://github.com/pandas-dev/pandas/issues/new). The form contains some questions that will help us best address your issue. For more information regarding how to file issues against *pandas*, please refer to the [Bug reports and enhancement requests](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#bug-reports-and-enhancement-requests) section of our main contribution doc.
+## Contributing to the Codebase
 
-Contributing to the Codebase
-----------------------------
-The code is hosted on [GitHub](https://www.github.com/pandas-dev/pandas), so you will need to use [Git](http://git-scm.com/) to clone the project and make changes to the codebase. Once you have obtained a copy of the code, you should create a development environment that is separate from your existing Python environment so that you can make and test changes without compromising your own work environment. For more information, please refer to our [Working with the code](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#working-with-the-code) section of our main contribution docs.
+The code is hosted on [GitHub](https://www.github.com/pandas-dev/pandas), so you will need to use [Git](http://git-scm.com/) to clone the project and make changes to the codebase. Once you have obtained a copy of the code, you should create a development environment that is separate from your existing Python environment so that you can make and test changes without compromising your own work environment. For more information, please refer to the "[Working with the code](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#working-with-the-code)" section.
 
-Before submitting your changes for review, make sure to check that your changes do not break any tests. You can find more information about our test suites can be found [here](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#test-driven-development-code-writing). We also have guidelines regarding coding style that will be enforced during testing. Details about coding style can be found [here](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#code-standards).
+Before submitting your changes for review, make sure to check that your changes do not break any tests. You can find more information about our test suites in the "[Test-driven development/code writing](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#test-driven-development-code-writing)" section. We also have guidelines regarding coding style that will be enforced during testing, which can be found in the "[Code standards](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#code-standards)" section.
 
-Once your changes are ready to be submitted, make sure to push your changes to GitHub before creating a pull request. Details about how to do that can be found in the [Contributing your changes to pandas](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#contributing-your-changes-to-pandas) section of our main contribution docs. We will review your changes, and you will most likely be asked to make additional changes before it is finally ready to merge. However, once it's ready, we will merge it, and you will have successfully contributed to the codebase!
+Once your changes are ready to be submitted, make sure to push your changes to GitHub before creating a pull request. Details about how to do that can be found in the "[Contributing your changes to pandas](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#contributing-your-changes-to-pandas)" section. We will review your changes, and you will most likely be asked to make additional changes before it is finally ready to merge. However, once it's ready, we will merge it, and you will have successfully contributed to the codebase!

README.md

@@ -231,9 +231,9 @@ Most development discussion is taking place on github in this repo. Further, the
 
 All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.
 
-A detailed overview on how to contribute can be found in the **[contributing guide.](https://pandas.pydata.org/pandas-docs/stable/contributing.html)**
+A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas-docs.github.io/pandas-docs-travis/contributing.html)**. There is also an [overview](.github/CONTRIBUTING.md) on GitHub.
 
-If you are simply looking to start working with the pandas codebase, navigate to the [GitHub “issues” tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.
+If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.
 
 You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).
 

ci/build_docs.sh

@@ -25,28 +25,33 @@ if [ "$DOC" ]; then
     echo # Create and send docs #
     echo ########################
 
-    cd build/html
-    git config --global user.email "[email protected]"
-    git config --global user.name "pandas-docs-bot"
-
-    # create the repo
-    git init
-
-    touch README
-    git add README
-    git commit -m "Initial commit" --allow-empty
-    git branch gh-pages
-    git checkout gh-pages
-    touch .nojekyll
-    git add --all .
-    git commit -m "Version" --allow-empty
-
-    git remote remove origin
-    git remote add origin "https://${PANDAS_GH_TOKEN}@github.com/pandas-dev/pandas-docs-travis.git"
-    git fetch origin
-    git remote -v
-
-    git push origin gh-pages -f
+    echo "Only uploading docs when TRAVIS_PULL_REQUEST is 'false'"
+    echo "TRAVIS_PULL_REQUEST: ${TRAVIS_PULL_REQUEST}"
+
+    if [ "${TRAVIS_PULL_REQUEST}" == "false" ]; then
+        cd build/html
+        git config --global user.email "[email protected]"
+        git config --global user.name "pandas-docs-bot"
+
+        # create the repo
+        git init
+
+        touch README
+        git add README
+        git commit -m "Initial commit" --allow-empty
+        git branch gh-pages
+        git checkout gh-pages
+        touch .nojekyll
+        git add --all .
+        git commit -m "Version" --allow-empty
+
+        git remote remove origin
+        git remote add origin "https://${PANDAS_GH_TOKEN}@github.com/pandas-dev/pandas-docs-travis.git"
+        git fetch origin
+        git remote -v
+
+        git push origin gh-pages -f
+    fi
 fi
 
 exit 0

doc/README.rst

@@ -1 +1 @@
-See `contributing.rst <https://pandas.pydata.org/pandas-docs/stable/contributing.html>`_ in this repo.
+See `contributing.rst <https://pandas-docs.github.io/pandas-docs-travis/contributing.html>`_ in this repo.

doc/source/api.rst

@@ -113,6 +113,7 @@ HDFStore: PyTables (HDF5)
    HDFStore.select
    HDFStore.info
    HDFStore.keys
+   HDFStore.groups
    HDFStore.walk
 
 Feather
@@ -611,6 +612,16 @@ These can be accessed like ``Series.dt.<property>``.
    Series.dt.month_name
    Series.dt.day_name
 
+**Period Properties**
+
+.. autosummary::
+   :toctree: generated/
+   :template: autosummary/accessor_attribute.rst
+
+   Series.dt.qyear
+   Series.dt.start_time
+   Series.dt.end_time
+
 **Timedelta Properties**
 
 .. autosummary::
@@ -1648,7 +1659,14 @@ Categorical Components
    CategoricalIndex.set_categories
    CategoricalIndex.as_ordered
    CategoricalIndex.as_unordered
+
+Modifying and Computations
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: generated/
+
    CategoricalIndex.map
+   CategoricalIndex.equals
 
 .. _api.intervalindex:
 
@@ -1741,7 +1759,6 @@ MultiIndex Components
    MultiIndex.swaplevel
    MultiIndex.reorder_levels
    MultiIndex.remove_unused_levels
-   MultiIndex.unique
 
 MultiIndex Selecting
 ~~~~~~~~~~~~~~~~~~~~
@@ -1750,6 +1767,7 @@ MultiIndex Selecting
    :toctree: generated/
 
    MultiIndex.get_loc
+   MultiIndex.get_loc_level
    MultiIndex.get_indexer
    MultiIndex.get_level_values
 
@@ -2292,6 +2310,7 @@ Function application
    :toctree: generated/
 
    GroupBy.apply
+   GroupBy.agg
    GroupBy.aggregate
    GroupBy.transform
    GroupBy.pipe
@@ -2336,7 +2355,6 @@ application to columns of a specific data type.
 .. autosummary::
    :toctree: generated/
 
-   DataFrameGroupBy.agg
    DataFrameGroupBy.all
    DataFrameGroupBy.any
    DataFrameGroupBy.bfill

doc/source/basics.rst

@@ -88,7 +88,7 @@ may involve copying data and coercing values.
 
 Getting the "raw data" inside a :class:`DataFrame` is possibly a bit more
 complex. When your ``DataFrame`` only has a single data type for all the
-columns, :atr:`DataFrame.to_numpy` will return the underlying data:
+columns, :attr:`DataFrame.to_numpy` will return the underlying data:
 
 .. ipython:: python
 
@@ -1931,7 +1931,7 @@ Categorical         :class:`CategoricalDtype` (none)             :class:`Categor
 period (time spans) :class:`PeriodDtype`      :class:`Period`    :class:`arrays.PeriodArray`   :ref:`timeseries.periods`
 sparse              :class:`SparseDtype`      (none)             :class:`arrays.SparseArray`   :ref:`sparse`
 intervals           :class:`IntervalDtype`    :class:`Interval`  :class:`arrays.IntervalArray` :ref:`advanced.intervalindex`
-nullable integer    :clsas:`Int64Dtype`, ...  (none)             :class:`arrays.IntegerArray`  :ref:`integer_na`
+nullable integer    :class:`Int64Dtype`, ...  (none)             :class:`arrays.IntegerArray`  :ref:`integer_na`
 =================== ========================= ================== ============================= =============================
 
 Pandas uses the ``object`` dtype for storing strings.
@@ -2324,4 +2324,4 @@ All NumPy dtypes are subclasses of ``numpy.generic``:
 .. note::
 
     Pandas also defines the types ``category``, and ``datetime64[ns, tz]``, which are not integrated into the normal
-    NumPy hierarchy and won't show up with the above function.
+    NumPy hierarchy and won't show up with the above function.

doc/source/conf.py

@@ -369,7 +369,7 @@
 
 intersphinx_mapping = {
     'statsmodels': ('http://www.statsmodels.org/devel/', None),
-    'matplotlib': ('http://matplotlib.org/', None),
+    'matplotlib': ('https://matplotlib.org/', None),
     'pandas-gbq': ('https://pandas-gbq.readthedocs.io/en/latest/', None),
     'python': ('https://docs.python.org/3/', None),
     'numpy': ('https://docs.scipy.org/doc/numpy/', None),

doc/source/ecosystem.rst

@@ -142,7 +142,7 @@ which are utilized by Jupyter Notebook for displaying
 (Note: HTML tables may or may not be
 compatible with non-HTML Jupyter output formats.)
 
-See :ref:`Options and Settings <options>` and :ref:`options.available`
+See :ref:`Options and Settings <options>` and :ref:`<options.available>`
 for pandas ``display.`` settings.
 
 `quantopian/qgrid <https://github.com/quantopian/qgrid>`__

doc/source/install.rst

@@ -193,7 +193,7 @@ methods described above.
 Installing from source
 ~~~~~~~~~~~~~~~~~~~~~~
 
-See the :ref:`contributing documentation <contributing>` for complete instructions on building from the git source tree. Further, see :ref:`creating a development environment <contributing.dev_env>` if you wish to create a *pandas* development environment.
+See the :ref:`contributing guide <contributing>` for complete instructions on building from the git source tree. Further, see :ref:`creating a development environment <contributing.dev_env>` if you wish to create a *pandas* development environment.
 
 Running the test suite
 ----------------------

doc/source/io.rst

@@ -1863,7 +1863,9 @@ Writing to a file, with a date index and a date column:
    dfj2['bools'] = True
    dfj2.index = pd.date_range('20130101', periods=5)
    dfj2.to_json('test.json')
-   open('test.json').read()
+
+   with open('test.json') as fh:
+       print(fh.read())
 
 Fallback Behavior
 +++++++++++++++++
@@ -2321,6 +2323,11 @@ indicate missing values and the subsequent read cannot distinguish the intent.
    new_df = pd.read_json('test.json', orient='table')
    print(new_df.index.name)
 
+.. ipython:: python
+   :suppress:
+
+   os.remove('test.json')
+
 .. _Table Schema: https://specs.frictionlessdata.io/json-table-schema/
 
 HTML
@@ -4766,6 +4773,11 @@ this file into a ``DataFrame``.
 Passing ``index=True`` will *always* write the index, even if that's not the
 underlying engine's default behavior.
 
+.. ipython:: python
+   :suppress:
+
+   os.remove('test.parquet')
+
 
 Partitioning Parquet files
 ''''''''''''''''''''''''''

doc/source/overview.rst

@@ -91,8 +91,7 @@ pandas is actively supported today by a community of like-minded individuals aro
 the world who contribute their valuable time and energy to help make open source
 pandas possible. Thanks to `all of our contributors <https://github.com/pandas-dev/pandas/graphs/contributors>`__.
 
-If you're interested in contributing, please
-visit `Contributing to pandas webpage <https://pandas.pydata.org/pandas-docs/stable/contributing.html>`__.
+If you're interested in contributing, please visit the :ref:`contributing guide <contributing>`.
 
 pandas is a `NumFOCUS <https://www.numfocus.org/open-source-projects/>`__ sponsored project.
 This will help ensure the success of development of pandas as a world-class open-source

doc/source/timeseries.rst

@@ -1084,7 +1084,7 @@ in the usual way.
     dt + bmth_us
 
     # Define date index with custom offset
-    pd.DatetimeIndex(start='20100101', end='20120101', freq=bmth_us)
+    pd.date_range(start='20100101', end='20120101', freq=bmth_us)
 
 .. note::
 
@@ -1438,8 +1438,8 @@ or ``Timestamp`` objects.
 
 .. ipython:: python
 
-    pd.DatetimeIndex(start='7/1/2012', end='7/10/2012',
-                     freq=pd.offsets.CDay(calendar=cal)).to_pydatetime()
+    pd.date_range(start='7/1/2012', end='7/10/2012',
+                  freq=pd.offsets.CDay(calendar=cal)).to_pydatetime()
     offset = pd.offsets.CustomBusinessDay(calendar=cal)
     datetime.datetime(2012, 5, 25) + offset
     datetime.datetime(2012, 7, 3) + offset
@@ -2300,8 +2300,8 @@ To remove timezone from tz-aware ``DatetimeIndex``, use ``tz_localize(None)`` or
 
 .. ipython:: python
 
-   didx = pd.DatetimeIndex(start='2014-08-01 09:00', freq='H',
-                           periods=10, tz='US/Eastern')
+   didx = pd.date_range(start='2014-08-01 09:00', freq='H',
+                        periods=10, tz='US/Eastern')
    didx
    didx.tz_localize(None)
    didx.tz_convert(None)
@@ -2354,8 +2354,8 @@ constructor as well as ``tz_localize``.
    rng_hourly.tz_localize('US/Eastern', ambiguous=rng_hourly_dst).to_list()
    rng_hourly.tz_localize('US/Eastern', ambiguous='NaT').to_list()
 
-   didx = pd.DatetimeIndex(start='2014-08-01 09:00', freq='H',
-                           periods=10, tz='US/Eastern')
+   didx = pd.date_range(start='2014-08-01 09:00', freq='H',
+                        periods=10, tz='US/Eastern')
    didx
    didx.tz_localize(None)
    didx.tz_convert(None)

doc/source/tutorials.rst

@@ -86,6 +86,14 @@ Video Tutorials
 * `Pandas: .head() to .tail() <https://www.youtube.com/watch?v=7vuO9QXDN50>`_
   (2016) (1:26)
   `GitHub repo <https://github.com/TomAugspurger/pydata-chi-h2t>`__
+* `Data analysis in Python with pandas <https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y>`_
+  (2016-2018)
+  `GitHub repo <https://github.com/justmarkham/pandas-videos>`_ and
+  `Jupyter Notebook <http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb>`_
+* `Best practices with pandas <https://www.youtube.com/playlist?list=PL5-da3qGB5IBITZj_dYSFqnd_15JgqwA6>`_
+  (2018)
+  `GitHub repo <https://github.com/justmarkham/pycon-2018-tutorial>`_ and
+  `Jupyter Notebook <http://nbviewer.jupyter.org/github/justmarkham/pycon-2018-tutorial/blob/master/tutorial.ipynb>`_
 
 
 Various Tutorials