Merge branch 'master' into iss24919_df_iloc_support_zero_dim_np_array

Author: tamuhey

.github/CONTRIBUTING.md

@@ -8,16 +8,16 @@ Our main contributing guide can be found [in this repo](https://github.com/panda
 
 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 the "[Where to start?](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#where-to-start)" section.
+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/development/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.
+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/development/contributing.rst#bug-reports-and-enhancement-requests)" section.
 
 ## 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 the "[Working with the code](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#working-with-the-code)" section.
+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/development/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 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.
+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/development/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. 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/development/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!

.gitignore

@@ -101,14 +101,14 @@ asv_bench/pandas/
 # Documentation generated files #
 #################################
 doc/source/generated
-doc/source/api/generated
+doc/source/user_guide/styled.xlsx
+doc/source/reference/api
 doc/source/_static
 doc/source/vbench
 doc/source/vbench.rst
 doc/source/index.rst
 doc/build/html/index.html
 # Windows specific leftover:
 doc/tmp.sv
-doc/source/styled.xlsx
 env/
 doc/source/savefig/

asv_bench/benchmarks/algorithms.py

@@ -5,7 +5,6 @@
 import pandas as pd
 from pandas.util import testing as tm
 
-
 for imp in ['pandas.util', 'pandas.tools.hashing']:
     try:
         hashing = import_module(imp)
@@ -142,4 +141,4 @@ def time_quantile(self, quantile, interpolation, dtype):
         self.idx.quantile(quantile, interpolation=interpolation)
 
 
-from .pandas_vb_common import setup  # noqa: F401
+from .pandas_vb_common import setup  # noqa: F401 isort:skip

asv_bench/benchmarks/categoricals.py

@@ -223,12 +223,19 @@ class CategoricalSlicing(object):
 
     def setup(self, index):
         N = 10**6
-        values = list('a' * N + 'b' * N + 'c' * N)
-        indices = {
-            'monotonic_incr': pd.Categorical(values),
-            'monotonic_decr': pd.Categorical(reversed(values)),
-            'non_monotonic': pd.Categorical(list('abc' * N))}
-        self.data = indices[index]
+        categories = ['a', 'b', 'c']
+        values = [0] * N + [1] * N + [2] * N
+        if index == 'monotonic_incr':
+            self.data = pd.Categorical.from_codes(values,
+                                                  categories=categories)
+        elif index == 'monotonic_decr':
+            self.data = pd.Categorical.from_codes(list(reversed(values)),
+                                                  categories=categories)
+        elif index == 'non_monotonic':
+            self.data = pd.Categorical.from_codes([0, 1, 2] * N,
+                                                  categories=categories)
+        else:
+            raise ValueError('Invalid index param: {}'.format(index))
 
         self.scalar = 10000
         self.list = list(range(10000))

asv_bench/benchmarks/strings.py

@@ -102,10 +102,10 @@ def setup(self, repeats):
         N = 10**5
         self.s = Series(tm.makeStringIndex(N))
         repeat = {'int': 1, 'array': np.random.randint(1, 3, N)}
-        self.repeat = repeat[repeats]
+        self.values = repeat[repeats]
 
     def time_repeat(self, repeats):
-        self.s.str.repeat(self.repeat)
+        self.s.str.repeat(self.values)
 
 
 class Cat(object):

doc/make.py

@@ -53,7 +53,7 @@ def __init__(self, num_jobs=0, include_api=True, single_doc=None,
         if single_doc and single_doc.endswith('.rst'):
             self.single_doc_html = os.path.splitext(single_doc)[0] + '.html'
         elif single_doc:
-            self.single_doc_html = 'api/generated/pandas.{}.html'.format(
+            self.single_doc_html = 'reference/api/pandas.{}.html'.format(
                 single_doc)
 
     def _process_single_doc(self, single_doc):
@@ -63,7 +63,7 @@ def _process_single_doc(self, single_doc):
 
         For example, categorial.rst or pandas.DataFrame.head. For the latter,
         return the corresponding file path
-        (e.g. generated/pandas.DataFrame.head.rst).
+        (e.g. reference/api/pandas.DataFrame.head.rst).
         """
         base_name, extension = os.path.splitext(single_doc)
         if extension in ('.rst', '.ipynb'):
@@ -258,7 +258,7 @@ def clean():
         Clean documentation generated files.
         """
         shutil.rmtree(BUILD_PATH, ignore_errors=True)
-        shutil.rmtree(os.path.join(SOURCE_PATH, 'api', 'generated'),
+        shutil.rmtree(os.path.join(SOURCE_PATH, 'reference', 'api'),
                       ignore_errors=True)
 
     def zip_html(self):