DOC: pydata/pandas -> pandas-dev/pandas (pandas-dev#14409)

asv_bench/benchmarks/attrs_caching.py

@@ -20,4 +20,4 @@ def setup(self):
         self.cur_index = self.df.index
 
     def time_setattr_dataframe_index(self):
-        self.df.index = self.cur_index
+        self.df.index = self.cur_index

asv_bench/benchmarks/ctors.py

@@ -49,4 +49,4 @@ def setup(self):
         self.s = Series(([Timestamp('20110101'), Timestamp('20120101'), Timestamp('20130101')] * 1000))
 
     def time_index_from_series_ctor(self):
-        Index(self.s)
+        Index(self.s)

asv_bench/benchmarks/frame_ctor.py

@@ -1703,4 +1703,4 @@ def setup(self):
         self.dict_list = [dict(zip(self.columns, row)) for row in self.frame.values]
 
     def time_series_ctor_from_dict(self):
-        Series(self.some_dict)
+        Series(self.some_dict)

asv_bench/benchmarks/hdfstore_bench.py

@@ -348,4 +348,4 @@ def remove(self, f):
         try:
             os.remove(self.f)
         except:
-            pass
+            pass

asv_bench/benchmarks/index_object.py

@@ -344,4 +344,4 @@ def setup(self):
         self.mi = MultiIndex.from_product([self.level1, self.level2])
 
     def time_multiindex_with_datetime_level_sliced(self):
-        self.mi[:10].values
+        self.mi[:10].values

asv_bench/benchmarks/io_sql.py

@@ -212,4 +212,4 @@ def setup(self):
         self.df = DataFrame({'float1': randn(10000), 'float2': randn(10000), 'string1': (['foo'] * 10000), 'bool1': ([True] * 10000), 'int1': np.random.randint(0, 100000, size=10000), }, index=self.index)
 
     def time_sql_write_sqlalchemy(self):
-        self.df.to_sql('test1', self.engine, if_exists='replace')
+        self.df.to_sql('test1', self.engine, if_exists='replace')

asv_bench/benchmarks/panel_ctor.py

@@ -61,4 +61,4 @@ def setup(self):
             self.data_frames[x] = self.df
 
     def time_panel_from_dict_two_different_indexes(self):
-        Panel.from_dict(self.data_frames)
+        Panel.from_dict(self.data_frames)

asv_bench/benchmarks/panel_methods.py

@@ -53,4 +53,4 @@ def setup(self):
         self.panel = Panel(np.random.randn(100, len(self.index), 1000))
 
     def time_panel_shift_minor(self):
-        self.panel.shift(1, axis='minor')
+        self.panel.shift(1, axis='minor')

asv_bench/benchmarks/replace.py

@@ -45,4 +45,4 @@ def setup(self):
         self.ts = Series(np.random.randn(self.N), index=self.rng)
 
     def time_replace_replacena(self):
-        self.ts.replace(np.nan, 0.0, inplace=True)
+        self.ts.replace(np.nan, 0.0, inplace=True)

asv_bench/benchmarks/reshape.py

@@ -73,4 +73,4 @@ def setup(self):
                 break
 
     def time_unstack_sparse_keyspace(self):
-        self.idf.unstack()
+        self.idf.unstack()

asv_bench/benchmarks/stat_ops.py

@@ -258,4 +258,4 @@ def time_rolling_skew(self):
         rolling_skew(self.arr, self.win)
 
     def time_rolling_kurt(self):
-        rolling_kurt(self.arr, self.win)
+        rolling_kurt(self.arr, self.win)

asv_bench/benchmarks/strings.py

@@ -390,4 +390,4 @@ def time_strings_upper(self):
         self.many.str.upper()
 
     def make_series(self, letters, strlen, size):
-        return Series([str(x) for x in np.fromiter(IT.cycle(letters), count=(size * strlen), dtype='|S1').view('|S{}'.format(strlen))])
+        return Series([str(x) for x in np.fromiter(IT.cycle(letters), count=(size * strlen), dtype='|S1').view('|S{}'.format(strlen))])

doc/README.rst

@@ -155,9 +155,9 @@ Where to start?
 ---------------
 
 There are a number of issues listed under `Docs
-<https://github.com/pydata/pandas/issues?labels=Docs&sort=updated&state=open>`_
+<https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open>`_
 and `Good as first PR
-<https://github.com/pydata/pandas/issues?labels=Good+as+first+PR&sort=updated&state=open>`_
+<https://github.com/pandas-dev/pandas/issues?labels=Good+as+first+PR&sort=updated&state=open>`_
 where you could start out.
 
 Or maybe you have an idea of your own, by using pandas, looking for something

doc/_templates/autosummary/accessor_attribute.rst

@@ -3,4 +3,4 @@
 
 .. currentmodule:: {{ module.split('.')[0] }}
 
-.. autoaccessorattribute:: {{ [module.split('.')[1], objname]|join('.') }}
+.. autoaccessorattribute:: {{ [module.split('.')[1], objname]|join('.') }}

doc/_templates/autosummary/accessor_method.rst

@@ -3,4 +3,4 @@
 
 .. currentmodule:: {{ module.split('.')[0] }}
 
-.. autoaccessormethod:: {{ [module.split('.')[1], objname]|join('.') }}
+.. autoaccessormethod:: {{ [module.split('.')[1], objname]|join('.') }}

doc/source/categorical.rst

@@ -973,7 +973,7 @@ are not numeric data (even in the case that ``.categories`` is numeric).
          print("TypeError: " + str(e))
 
 .. note::
-    If such a function works, please file a bug at https://github.com/pydata/pandas!
+    If such a function works, please file a bug at https://github.com/pandas-dev/pandas!
 
 dtype in apply
 ~~~~~~~~~~~~~~

doc/source/comparison_with_sas.rst

@@ -116,7 +116,7 @@ Reading External Data
 
 Like SAS, pandas provides utilities for reading in data from
 many formats.  The ``tips`` dataset, found within the pandas
-tests (`csv <https://raw.github.com/pydata/pandas/master/pandas/tests/data/tips.csv>`_)
+tests (`csv <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv>`_)
 will be used in many of the following examples.
 
 SAS provides ``PROC IMPORT`` to read csv data into a data set.
@@ -131,7 +131,7 @@ The pandas method is :func:`read_csv`, which works similarly.
 
 .. ipython:: python
 
-   url = 'https://raw.github.com/pydata/pandas/master/pandas/tests/data/tips.csv'
+   url = 'https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv'
    tips = pd.read_csv(url)
    tips.head()
 

doc/source/comparison_with_sql.rst

@@ -23,7 +23,7 @@ structure.
 
 .. ipython:: python
 
-    url = 'https://raw.github.com/pydata/pandas/master/pandas/tests/data/tips.csv'
+    url = 'https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv'
     tips = pd.read_csv(url)
     tips.head()
 

doc/source/conf.py

@@ -301,9 +301,9 @@
 autosummary_generate = glob.glob("*.rst")
 
 # extlinks alias
-extlinks = {'issue': ('https://github.com/pydata/pandas/issues/%s',
+extlinks = {'issue': ('https://github.com/pandas-dev/pandas/issues/%s',
                       'GH'),
-            'wiki': ('https://github.com/pydata/pandas/wiki/%s',
+            'wiki': ('https://github.com/pandas-dev/pandas/wiki/%s',
                      'wiki ')}
 
 ipython_exec_lines = [
@@ -468,10 +468,10 @@ def linkcode_resolve(domain, info):
     fn = os.path.relpath(fn, start=os.path.dirname(pandas.__file__))
 
     if '+' in pandas.__version__:
-        return "http://github.com/pydata/pandas/blob/master/pandas/%s%s" % (
+        return "http://github.com/pandas-dev/pandas/blob/master/pandas/%s%s" % (
             fn, linespec)
     else:
-        return "http://github.com/pydata/pandas/blob/v%s/pandas/%s%s" % (
+        return "http://github.com/pandas-dev/pandas/blob/v%s/pandas/%s%s" % (
             pandas.__version__, fn, linespec)
 
 

doc/source/contributing.rst

@@ -14,11 +14,11 @@ All contributions, bug reports, bug fixes, documentation improvements,
 enhancements and ideas are welcome.
 
 If you are simply looking to start working with the *pandas* codebase, navigate to the
-`GitHub "issues" tab <https://github.com/pydata/pandas/issues>`_ and start looking through
+`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/pydata/pandas/issues?labels=Docs&sort=updated&state=open>`_
+<https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open>`_
 and `Difficulty Novice
-<https://github.com/pydata/pandas/issues?q=is%3Aopen+is%3Aissue+label%3A%22Difficulty+Novice%22>`_
+<https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3Aissue+label%3A%22Difficulty+Novice%22>`_
 where you could start out.
 
 Or maybe through using *pandas* you have an idea of your own or are looking for something
@@ -27,7 +27,7 @@ about it!
 
 Feel free to ask questions on the `mailing list
 <https://groups.google.com/forum/?fromgroups#!forum/pydata>`_ or on `Gitter
-<https://gitter.im/pydata/pandas>`_.
+<https://gitter.im/pandas-dev/pandas>`_.
 
 Bug reports and enhancement requests
 ====================================
@@ -79,7 +79,7 @@ It can very quickly become overwhelming, but sticking to the guidelines below wi
 straightforward and mostly trouble free.  As always, if you are having difficulties please
 feel free to ask for help.
 
-The code is hosted on `GitHub <https://www.github.com/pydata/pandas>`_. To
+The code is hosted on `GitHub <https://www.github.com/pandas-dev/pandas>`_. To
 contribute you will need to sign up for a `free GitHub account
 <https://github.com/signup/free>`_. We use `Git <http://git-scm.com/>`_ for
 version control to allow many people to work together on the project.
@@ -103,12 +103,12 @@ Forking
 -------
 
 You will need your own fork to work on the code. Go to the `pandas project
-page <https://github.com/pydata/pandas>`_ and hit the ``Fork`` button. You will
+page <https://github.com/pandas-dev/pandas>`_ and hit the ``Fork`` button. You will
 want to clone your fork to your machine::
 
     git clone git@github.com:your-user-name/pandas.git pandas-yourname
     cd pandas-yourname
-    git remote add upstream git://github.com/pydata/pandas.git
+    git remote add upstream git://github.com/pandas-dev/pandas.git
 
 This creates the directory `pandas-yourname` and connects your repository to
 the upstream (main project) *pandas* repository.
@@ -467,7 +467,7 @@ and make these changes with::
     pep8radius master --diff --in-place
 
 Additional standards are outlined on the `code style wiki
-page <https://github.com/pydata/pandas/wiki/Code-Style-and-Conventions>`_.
+page <https://github.com/pandas-dev/pandas/wiki/Code-Style-and-Conventions>`_.
 
 Please try to maintain backward compatibility. *pandas* has lots of users with lots of
 existing code, so don't break it if at all possible.  If you think breakage is required,
@@ -501,7 +501,7 @@ All tests should go into the ``tests`` subdirectory of the specific package.
 This folder contains many current examples of tests, and we suggest looking to these for
 inspiration.  If your test requires working with files or
 network connectivity, there is more information on the `testing page
-<https://github.com/pydata/pandas/wiki/Testing>`_ of the wiki.
+<https://github.com/pandas-dev/pandas/wiki/Testing>`_ of the wiki.
 
 The ``pandas.util.testing`` module has many special ``assert`` functions that
 make it easier to make statements about whether Series or DataFrame objects are
@@ -639,7 +639,7 @@ on Travis-CI. The first step is to create a `service account
 Integration tests for ``pandas.io.gbq`` are skipped in pull requests because
 the credentials that are required for running Google BigQuery integration
 tests are `encrypted <https://docs.travis-ci.com/user/encrypting-files/>`__
-on Travis-CI and are only accessible from the pydata/pandas repository. The
+on Travis-CI and are only accessible from the pandas-dev/pandas repository. The
 credentials won't be available on forks of pandas. Here are the steps to run
 gbq integration tests on a forked repository:
 
@@ -688,7 +688,7 @@ performance regressions.
 
 You can run specific benchmarks using the ``-r`` flag, which takes a regular expression.
 
-See the `performance testing wiki <https://github.com/pydata/pandas/wiki/Performance-Testing>`_ for information
+See the `performance testing wiki <https://github.com/pandas-dev/pandas/wiki/Performance-Testing>`_ for information
 on how to write a benchmark.
 
 Documenting your code
@@ -712,8 +712,8 @@ directive is used. The sphinx syntax for that is:
 
 This will put the text *New in version 0.17.0* wherever you put the sphinx
 directive. This should also be put in the docstring when adding a new function
-or method (`example <https://github.com/pydata/pandas/blob/v0.16.2/pandas/core/generic.py#L1959>`__)
-or a new keyword argument (`example <https://github.com/pydata/pandas/blob/v0.16.2/pandas/core/frame.py#L1171>`__).
+or method (`example <https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/generic.py#L1959>`__)
+or a new keyword argument (`example <https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/frame.py#L1171>`__).
 
 Contributing your changes to *pandas*
 =====================================
@@ -806,8 +806,8 @@ like::
 
     origin  git@github.com:yourname/pandas.git (fetch)
     origin  git@github.com:yourname/pandas.git (push)
-    upstream        git://github.com/pydata/pandas.git (fetch)
-    upstream        git://github.com/pydata/pandas.git (push)
+    upstream        git://github.com/pandas-dev/pandas.git (fetch)
+    upstream        git://github.com/pandas-dev/pandas.git (push)
 
 Now your code is on GitHub, but it is not yet a part of the *pandas* project.  For that to
 happen, a pull request needs to be submitted on GitHub.

doc/source/cookbook.rst

@@ -200,7 +200,7 @@ The :ref:`indexing <indexing>` docs.
    df[(df.AAA <= 6) & (df.index.isin([0,2,4]))]
 
 `Use loc for label-oriented slicing and iloc positional slicing
-<https://github.com/pydata/pandas/issues/2904>`__
+<https://github.com/pandas-dev/pandas/issues/2904>`__
 
 .. ipython:: python
 
@@ -410,7 +410,7 @@ Sorting
    df.sort_values(by=('Labs', 'II'), ascending=False)
 
 `Partial Selection, the need for sortedness;
-<https://github.com/pydata/pandas/issues/2995>`__
+<https://github.com/pandas-dev/pandas/issues/2995>`__
 
 Levels
 ******
@@ -787,7 +787,7 @@ The :ref:`Resample <timeseries.resampling>` docs.
 <http://stackoverflow.com/questions/14569223/timegrouper-pandas>`__
 
 `Using TimeGrouper and another grouping to create subgroups, then apply a custom function
-<https://github.com/pydata/pandas/issues/3791>`__
+<https://github.com/pandas-dev/pandas/issues/3791>`__
 
 `Resampling with custom periods
 <http://stackoverflow.com/questions/15408156/resampling-with-custom-periods>`__
@@ -823,7 +823,7 @@ ignore_index is needed in pandas < v0.13, and depending on df construction
    df = df1.append(df2,ignore_index=True); df
 
 `Self Join of a DataFrame
-<https://github.com/pydata/pandas/issues/2996>`__
+<https://github.com/pandas-dev/pandas/issues/2996>`__
 
 .. ipython:: python
 
@@ -936,7 +936,7 @@ using that handle to read.
 <http://stackoverflow.com/questions/15555005/get-inferred-dataframe-types-iteratively-using-chunksize>`__
 
 `Dealing with bad lines
-<http://github.com/pydata/pandas/issues/2886>`__
+<http://github.com/pandas-dev/pandas/issues/2886>`__
 
 `Dealing with bad lines II
 <http://nipunbatra.github.io/2013/06/reading-unclean-data-csv-using-pandas/>`__
@@ -1075,7 +1075,7 @@ The :ref:`HDFStores <io.hdf5>` docs
 <http://stackoverflow.com/questions/13926089/selecting-columns-from-pandas-hdfstore-table>`__
 
 `Managing heterogeneous data using a linked multiple table hierarchy
-<http://github.com/pydata/pandas/issues/3032>`__
+<http://github.com/pandas-dev/pandas/issues/3032>`__
 
 `Merging on-disk tables with millions of rows
 <http://stackoverflow.com/questions/14614512/merging-two-tables-with-millions-of-rows-in-python/14617925#14617925>`__
@@ -1216,7 +1216,7 @@ Timedeltas
 The :ref:`Timedeltas <timedeltas.timedeltas>` docs.
 
 `Using timedeltas
-<http://github.com/pydata/pandas/pull/2899>`__
+<http://github.com/pandas-dev/pandas/pull/2899>`__
 
 .. ipython:: python
 

doc/source/ecosystem.rst

@@ -143,7 +143,7 @@ both "column wise min/max and global min/max coloring."
 API
 -----
 
-`pandas-datareader <https://github.com/pydata/pandas-datareader>`__
+`pandas-datareader <https://github.com/pandas-dev/pandas-datareader>`__
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 ``pandas-datareader`` is a remote data access library for pandas. ``pandas.io`` from pandas < 0.17.0 is now refactored/split-off to and importable from ``pandas_datareader`` (PyPI:``pandas-datareader``). Many/most of the supported APIs have at least a documentation paragraph in the `pandas-datareader docs <https://pandas-datareader.readthedocs.io/en/latest/>`_:
 

doc/source/gotchas.rst

@@ -391,7 +391,7 @@ This is because ``reindex_like`` silently inserts ``NaNs`` and the ``dtype``
 changes accordingly.  This can cause some issues when using ``numpy`` ``ufuncs``
 such as ``numpy.logical_and``.
 
-See the `this old issue <https://github.com/pydata/pandas/issues/2388>`__ for a more
+See the `this old issue <https://github.com/pandas-dev/pandas/issues/2388>`__ for a more
 detailed discussion.
 
 Parsing Dates from Text Files

doc/source/install.rst

@@ -13,7 +13,7 @@ This is the recommended installation method for most users.
 
 Instructions for installing from source,
 `PyPI <http://pypi.python.org/pypi/pandas>`__, various Linux distributions, or a
-`development version <http://github.com/pydata/pandas>`__ are also provided.
+`development version <http://github.com/pandas-dev/pandas>`__ are also provided.
 
 Python version support
 ----------------------

doc/source/io.rst

@@ -2035,7 +2035,7 @@ You can even pass in an instance of ``StringIO`` if you so desire
    that having so many network-accessing functions slows down the documentation
    build. If you spot an error or an example that doesn't run, please do not
    hesitate to report it over on `pandas GitHub issues page
-   <http://www.github.com/pydata/pandas/issues>`__.
+   <http://www.github.com/pandas-dev/pandas/issues>`__.
 
 
 Read a URL and match a table that contains specific text

doc/source/overview.rst

@@ -81,7 +81,7 @@ Getting Support
 ---------------
 
 The first stop for pandas issues and ideas is the `Github Issue Tracker
-<https://github.com/pydata/pandas/issues>`__. If you have a general question,
+<https://github.com/pandas-dev/pandas/issues>`__. If you have a general question,
 pandas community experts can answer through `Stack Overflow
 <http://stackoverflow.com/questions/tagged/pandas>`__.
 
@@ -103,7 +103,7 @@ training, and consulting for pandas.
 
 pandas is only made possible by a group of people around the world like you
 who have contributed new code, bug reports, fixes, comments and ideas. A
-complete list can be found `on Github <http://www.github.com/pydata/pandas/contributors>`__.
+complete list can be found `on Github <http://www.github.com/pandas-dev/pandas/contributors>`__.
 
 Development Team
 ----------------