Merge branch 'between-time-axis' of https://github.com/yrhooke/pandas into between-time-axis

Author: yrhooke

ci/appveyor-27.yaml

@@ -24,7 +24,7 @@ dependencies:
   - xlsxwriter
   - xlwt
   # universal
-  - cython
+  - cython>=0.28.2
   - pytest
   - pytest-xdist
   - moto

ci/appveyor-36.yaml

@@ -22,6 +22,6 @@ dependencies:
   - xlsxwriter
   - xlwt
   # universal
-  - cython
+  - cython>=0.28.2
   - pytest
   - pytest-xdist

ci/circle-27-compat.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - bottleneck=1.0.0
-  - cython=0.24
+  - cython=0.28.2
   - jinja2=2.8
   - numexpr=2.4.4 # we test that we correctly don't use an unsupported numexpr
   - numpy=1.9.2

ci/circle-35-ascii.yaml

@@ -2,7 +2,7 @@ name: pandas
 channels:
   - defaults
 dependencies:
-  - cython
+  - cython>=0.28.2
   - nomkl
   - numpy
   - python-dateutil

ci/circle-36-locale.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - beautifulsoup4
-  - cython
+  - cython>=0.28.2
   - html5lib
   - ipython
   - jinja2

ci/circle-36-locale_slow.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - beautifulsoup4
-  - cython
+  - cython>=0.28.2
   - gcsfs
   - html5lib
   - ipython

ci/environment-dev.yaml

@@ -3,7 +3,7 @@ channels:
   - defaults
   - conda-forge
 dependencies:
-  - Cython
+  - Cython>=0.28.2
   - NumPy
   - flake8
   - moto

ci/travis-27-locale.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - bottleneck=1.0.0
-  - cython=0.24
+  - cython=0.28.2
   - lxml
   - matplotlib=1.4.3
   - numpy=1.9.2

ci/travis-27.yaml

@@ -5,7 +5,7 @@ channels:
 dependencies:
   - beautifulsoup4
   - bottleneck
-  - cython=0.24
+  - cython=0.28.2
   - fastparquet
   - feather-format
   - flake8=3.4.1

ci/travis-35-osx.yaml

@@ -4,7 +4,7 @@ channels:
 dependencies:
   - beautifulsoup4
   - bottleneck
-  - cython
+  - cython>=0.28.2
   - html5lib
   - jinja2
   - lxml

ci/travis-36-doc.yaml

@@ -6,7 +6,7 @@ channels:
 dependencies:
   - beautifulsoup4
   - bottleneck
-  - cython
+  - cython>=0.28.2
   - fastparquet
   - feather-format
   - html5lib

ci/travis-36-numpydev.yaml

@@ -4,7 +4,7 @@ channels:
 dependencies:
   - python=3.6*
   - pytz
-  - Cython
+  - Cython>=0.28.2
   # universal
   - pytest
   - pytest-xdist

ci/travis-36-slow.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - beautifulsoup4
-  - cython
+  - cython>=0.28.2
   - html5lib
   - lxml
   - matplotlib

ci/travis-36.yaml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - beautifulsoup4
-  - cython
+  - cython>=0.28.2
   - dask
   - fastparquet
   - feather-format

ci/travis-37.yaml

@@ -5,7 +5,7 @@ channels:
   - c3i_test
 dependencies:
   - python=3.7
-  - cython
+  - cython>=0.28.2
   - numpy
   - python-dateutil
   - nomkl

conda.recipe/meta.yaml

@@ -12,16 +12,19 @@ source:
 
 requirements:
   build:
+    - {{ compiler('c') }}
+    - {{ compiler('cxx') }}
+  host:
     - python
+    - pip
     - cython
-    - numpy 1.11.*
+    - numpy
     - setuptools >=3.3
     - python-dateutil >=2.5.0
     - pytz
-
   run:
-    - python
-    - numpy >=1.11.*
+    - python {{ python }}
+    - {{ pin_compatible('numpy') }}
     - python-dateutil >=2.5.0
     - pytz
 

doc/source/api.rst

@@ -435,7 +435,6 @@ Computations / Descriptive Stats
    Series.value_counts
    Series.compound
    Series.nonzero
-   Series.ptp
 
 
 Reindexing / Selection / Label manipulation

doc/source/basics.rst

@@ -1924,11 +1924,24 @@ untouched. If the data is modified, it is because you did so explicitly.
 dtypes
 ------
 
-The main types stored in pandas objects are ``float``, ``int``, ``bool``,
-``datetime64[ns]`` and ``datetime64[ns, tz]``, ``timedelta[ns]``,
-``category`` and ``object``. In addition these dtypes have item sizes, e.g.
-``int64`` and ``int32``. See :ref:`Series with TZ <timeseries.timezone_series>`
-for more detail on ``datetime64[ns, tz]`` dtypes.
+For the most part, pandas uses NumPy arrays and dtypes for Series or individual
+columns of a DataFrame. The main types allowed in pandas objects are ``float``,
+``int``, ``bool``, and ``datetime64[ns]`` (note that NumPy does not support
+timezone-aware datetimes).
+
+In addition to NumPy's types, pandas :ref:`extends <extending.extension-types>`
+NumPy's type-system for a few cases.
+
+* :ref:`Categorical <categorical>`
+* :ref:`Datetime with Timezone <timeseries.timezone_series>`
+* :ref:`Period <timeseries.periods>`
+* :ref:`Interval <advanced.indexing.intervallindex>`
+
+Pandas uses the ``object`` dtype for storing strings.
+
+Finally, arbitrary objects may be stored using the ``object`` dtype, but should
+be avoided to the extent possible (for performance and interoperability with
+other libraries and methods. See :ref:`basics.object_conversion`).
 
 A convenient :attr:`~DataFrame.dtypes` attribute for DataFrame returns a Series
 with the data type of each column.