Merge remote-tracking branch 'upstream/master' into series-dtype-doc

* upstream/master: (26 commits)
  DOC: Fixing doc upload (no such remote origin) (pandas-dev#24459)
  BLD: for C extension builds on mac, target macOS 10.9 where possible (pandas-dev#24274)
  POC: _eadata (pandas-dev#24394)
  DOC: Correct location (pandas-dev#24456)
  CI: Moving CircleCI build to Travis (pandas-dev#24449)
  BUG: Infer compression by default in read_fwf() (pandas-dev#22200)
  DOC: Fix minor typo in whatsnew (pandas-dev#24453)
  DOC: Add dateutil to intersphinx pandas-dev#24437 (pandas-dev#24443)
  DOC: Adding links to offset classes in timeseries.rst (pandas-dev#24448)
  DOC: Adding offsets to API ref (pandas-dev#24446)
  DOC: fix flake8 issue in groupby.rst (pandas-dev#24363)
  DOC: Fixing more doc warnings (pandas-dev#24438)
  API: Simplify repeat signature (pandas-dev#24447)
  BUG: to_datetime(Timestamp, utc=True) localizes to UTC (pandas-dev#24441)
  CLN: Cython Py2/3 Compatible Imports (pandas-dev#23940)
  DOC: Fixing more doc warnings (pandas-dev#24431)
  DOC: Removing old release.rst (pandas-dev#24427)
  BUG-24408 Series.dt does not maintain own copy of index (pandas-dev#24426)
  DOC: Fixing several doc warnings (pandas-dev#24430)
  ENH: fill_value argument for shift pandas-dev#15486 (pandas-dev#24128)
  ...

Author: thoo

.circleci/config.yml

@@ -43,16 +43,23 @@ matrix:
         apt:
           packages:
           - language-pack-zh-hans
+
     - dist: trusty
       env:
         - JOB="2.7" ENV_FILE="ci/deps/travis-27.yaml" PATTERN="not slow"
       addons:
         apt:
           packages:
           - python-gtk2
+
+    - dist: trusty
+      env:
+        - JOB="3.6, locale" ENV_FILE="ci/deps/travis-36-locale.yaml" PATTERN="not slow and not network" LOCALE_OVERRIDE="zh_CN.UTF-8"
+
     - dist: trusty
       env:
         - JOB="3.6, coverage" ENV_FILE="ci/deps/travis-36.yaml" PATTERN="not slow and not network" PANDAS_TESTING_MODE="deprecate" COVERAGE=true
+
     - dist: trusty
       env:
         - JOB="3.7, NumPy dev" ENV_FILE="ci/deps/travis-37-numpydev.yaml" PATTERN="not slow and not network" TEST_ARGS="-W error" PANDAS_TESTING_MODE="deprecate"

.travis.yml

@@ -45,14 +45,6 @@
     </a>
   </td>
 </tr>
-<tr>
-  <td></td>
-  <td>
-    <a href="https://circleci.com/gh/pandas-dev/pandas">
-    <img src="https://circleci.com/gh/circleci/mongofinil/tree/master.svg?style=shield&circle-token=223d8cafa7b02902c3e150242520af8944e34671" alt="circleci build status" />
-    </a>
-  </td>
-</tr>
 <tr>
   <td></td>
   <td>

README.md

@@ -103,6 +103,7 @@ def setup(self):
         self.df2 = DataFrame(np.random.randn(N * 50, 10))
         self.df3 = DataFrame(np.random.randn(N, 5 * N),
                              columns=['C' + str(c) for c in range(N * 5)])
+        self.df4 = DataFrame(np.random.randn(N * 1000, 10))
 
     def time_iteritems(self):
         # (monitor no-copying behaviour)
@@ -119,10 +120,70 @@ def time_iteritems_indexing(self):
         for col in self.df3:
             self.df3[col]
 
+    def time_itertuples_start(self):
+        self.df4.itertuples()
+
+    def time_itertuples_read_first(self):
+        next(self.df4.itertuples())
+
     def time_itertuples(self):
-        for row in self.df2.itertuples():
+        for row in self.df4.itertuples():
+            pass
+
+    def time_itertuples_to_list(self):
+        list(self.df4.itertuples())
+
+    def mem_itertuples_start(self):
+        return self.df4.itertuples()
+
+    def peakmem_itertuples_start(self):
+        self.df4.itertuples()
+
+    def mem_itertuples_read_first(self):
+        return next(self.df4.itertuples())
+
+    def peakmem_itertuples(self):
+        for row in self.df4.itertuples():
+            pass
+
+    def mem_itertuples_to_list(self):
+        return list(self.df4.itertuples())
+
+    def peakmem_itertuples_to_list(self):
+        list(self.df4.itertuples())
+
+    def time_itertuples_raw_start(self):
+        self.df4.itertuples(index=False, name=None)
+
+    def time_itertuples_raw_read_first(self):
+        next(self.df4.itertuples(index=False, name=None))
+
+    def time_itertuples_raw_tuples(self):
+        for row in self.df4.itertuples(index=False, name=None):
             pass
 
+    def time_itertuples_raw_tuples_to_list(self):
+        list(self.df4.itertuples(index=False, name=None))
+
+    def mem_itertuples_raw_start(self):
+        return self.df4.itertuples(index=False, name=None)
+
+    def peakmem_itertuples_raw_start(self):
+        self.df4.itertuples(index=False, name=None)
+
+    def peakmem_itertuples_raw_read_first(self):
+        next(self.df4.itertuples(index=False, name=None))
+
+    def peakmem_itertuples_raw(self):
+        for row in self.df4.itertuples(index=False, name=None):
+            pass
+
+    def mem_itertuples_raw_to_list(self):
+        return list(self.df4.itertuples(index=False, name=None))
+
+    def peakmem_itertuples_raw_to_list(self):
+        list(self.df4.itertuples(index=False, name=None))
+
     def time_iterrows(self):
         for row in self.df.iterrows():
             pass

asv_bench/benchmarks/frame_methods.py

@@ -45,7 +45,6 @@ if [ "$DOC" ]; then
         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

ci/build_docs.sh

@@ -778,12 +778,12 @@ a ``Categorical`` will return a ``CategoricalIndex``, indexed according to the c
 of the **passed** ``Categorical`` dtype. This allows one to arbitrarily index these even with
 values **not** in the categories, similarly to how you can reindex **any** pandas index.
 
-.. ipython :: python
+.. ipython:: python
 
-   df2.reindex(['a','e'])
-   df2.reindex(['a','e']).index
-   df2.reindex(pd.Categorical(['a','e'],categories=list('abcde')))
-   df2.reindex(pd.Categorical(['a','e'],categories=list('abcde'))).index
+   df2.reindex(['a', 'e'])
+   df2.reindex(['a', 'e']).index
+   df2.reindex(pd.Categorical(['a', 'e'], categories=list('abcde')))
+   df2.reindex(pd.Categorical(['a', 'e'], categories=list('abcde'))).index
 
 .. warning::
 
@@ -1040,7 +1040,8 @@ than integer locations. Therefore, with an integer axis index *only*
 label-based indexing is possible with the standard tools like ``.loc``. The
 following code will generate exceptions:
 
-.. code-block:: python
+.. ipython:: python
+   :okexcept:
 
    s = pd.Series(range(5))
    s[-1]
@@ -1130,7 +1131,7 @@ index can be somewhat complicated. For example, the following does not work:
 
 ::
 
-    s.loc['c':'e'+1]
+    s.loc['c':'e' + 1]
 
 A very common use case is to limit a time series to start and end at two
 specific dates. To enable this, we made the design to make label-based