Merge branch 'master' into ndarray_tolerance

Author: buntwo

appveyor.yml

@@ -74,12 +74,18 @@ install:
   # create our env
   - cmd: conda create -n pandas python=%PYTHON_VERSION% cython pytest>=3.1.0 pytest-xdist
   - cmd: activate pandas
+  - cmd: pip install moto
   - SET REQ=ci\requirements-%PYTHON_VERSION%_WIN.run
   - cmd: echo "installing requirements from %REQ%"
   - cmd: conda install -n pandas --file=%REQ%
   - cmd: conda list -n pandas
   - cmd: echo "installing requirements from %REQ% - done"
 
+  # add some pip only reqs to the env
+  - SET REQ=ci\requirements-%PYTHON_VERSION%_WIN.pip
+  - cmd: echo "installing requirements from %REQ%"
+  - cmd: pip install -Ur %REQ%
+
   # build em using the local source checkout in the correct windows env
   - cmd: '%CMD_IN_ENV% python setup.py build_ext --inplace'
 

asv_bench/benchmarks/categoricals.py

@@ -67,6 +67,9 @@ def time_value_counts_dropna(self):
     def time_rendering(self):
         str(self.sel)
 
+    def time_set_categories(self):
+        self.ts.cat.set_categories(self.ts.cat.categories[::2])
+
 
 class Categoricals3(object):
     goal_time = 0.2

asv_bench/benchmarks/period.py

@@ -2,6 +2,35 @@
 from pandas import Series, Period, PeriodIndex, date_range
 
 
+class PeriodProperties(object):
+    def setup(self):
+        self.per = Period('2012-06-01', freq='M')
+
+    def time_year(self):
+        self.per.year
+
+    def time_month(self):
+        self.per.month
+
+    def time_quarter(self):
+        self.per.quarter
+
+    def time_day(self):
+        self.per.day
+
+    def time_hour(self):
+        self.per.hour
+
+    def time_minute(self):
+        self.per.second
+
+    def time_second(self):
+        self.per.second
+
+    def time_leap_year(self):
+        self.per.is_leapyear
+
+
 class Constructor(object):
     goal_time = 0.2
 
@@ -49,6 +78,65 @@ def time_value_counts_pindex(self):
         self.i.value_counts()
 
 
+class Properties(object):
+    def setup(self):
+        self.per = Period('2017-09-06 08:28', freq='min')
+
+    def time_year(self):
+        self.per.year
+
+    def time_month(self):
+        self.per.month
+
+    def time_day(self):
+        self.per.day
+
+    def time_hour(self):
+        self.per.hour
+
+    def time_minute(self):
+        self.per.minute
+
+    def time_second(self):
+        self.per.second
+
+    def time_is_leap_year(self):
+        self.per.is_leap_year
+
+    def time_quarter(self):
+        self.per.quarter
+
+    def time_qyear(self):
+        self.per.qyear
+
+    def time_week(self):
+        self.per.week
+
+    def time_daysinmonth(self):
+        self.per.daysinmonth
+
+    def time_dayofweek(self):
+        self.per.dayofweek
+
+    def time_dayofyear(self):
+        self.per.dayofyear
+
+    def time_start_time(self):
+        self.per.start_time
+
+    def time_end_time(self):
+        self.per.end_time
+
+    def time_to_timestamp():
+        self.per.to_timestamp()
+
+    def time_now():
+        self.per.now()
+
+    def time_asfreq():
+        self.per.asfreq('A')
+
+
 class period_standard_indexing(object):
     goal_time = 0.2
 

asv_bench/benchmarks/timestamp.py

@@ -0,0 +1,83 @@
+from .pandas_vb_common import *
+from pandas import to_timedelta, Timestamp
+import pytz
+import datetime
+
+
+class TimestampProperties(object):
+    goal_time = 0.2
+
+    def setup(self):
+        self.ts = Timestamp('2017-08-25 08:16:14')
+
+    def time_tz(self):
+        self.ts.tz
+
+    def time_offset(self):
+        self.ts.offset
+
+    def time_dayofweek(self):
+        self.ts.dayofweek
+
+    def time_weekday_name(self):
+        self.ts.weekday_name
+
+    def time_dayofyear(self):
+        self.ts.dayofyear
+
+    def time_week(self):
+        self.ts.week
+
+    def time_quarter(self):
+        self.ts.quarter
+
+    def time_days_in_month(self):
+        self.ts.days_in_month
+
+    def time_freqstr(self):
+        self.ts.freqstr
+
+    def time_is_month_start(self):
+        self.ts.is_month_start
+
+    def time_is_month_end(self):
+        self.ts.is_month_end
+
+    def time_is_quarter_start(self):
+        self.ts.is_quarter_start
+
+    def time_is_quarter_end(self):
+        self.ts.is_quarter_end
+
+    def time_is_year_start(self):
+        self.ts.is_quarter_end
+
+    def time_is_year_end(self):
+        self.ts.is_quarter_end
+
+    def time_is_leap_year(self):
+        self.ts.is_quarter_end
+
+    def time_microsecond(self):
+        self.ts.microsecond
+
+
+class TimestampOps(object):
+    goal_time = 0.2
+
+    def setup(self):
+        self.ts = Timestamp('2017-08-25 08:16:14')
+        self.ts_tz = Timestamp('2017-08-25 08:16:14', tz='US/Eastern')
+
+        dt = datetime.datetime(2016, 3, 27, 1)
+        self.tzinfo = pytz.timezone('CET').localize(dt, is_dst=False).tzinfo
+        self.ts2 = Timestamp(dt)
+
+    def time_replace_tz(self):
+        self.ts.replace(tzinfo=pytz.timezone('US/Eastern'))
+
+    def time_replace_across_dst(self):
+        self.ts2.replace(tzinfo=self.tzinfo)
+
+    def time_replace_None(self):
+        self.ts_tz.replace(tzinfo=None)

ci/install_circle.sh

@@ -67,6 +67,7 @@ time conda create -n pandas -q --file=${REQ_BUILD} || exit 1
 time conda install -n pandas pytest>=3.1.0 || exit 1
 
 source activate pandas
+time pip install moto || exit 1
 
 # build but don't install
 echo "[build em]"

ci/install_travis.sh

@@ -104,7 +104,7 @@ if [ -e ${REQ} ]; then
 fi
 
 time conda install -n pandas pytest>=3.1.0
-time pip install pytest-xdist
+time pip install pytest-xdist moto
 
 if [ "$LINT" ]; then
    conda install flake8

ci/requirements-2.7_WIN.pip

@@ -8,4 +8,4 @@ echo "install 35"
 conda remove -n pandas python-dateutil --force
 pip install python-dateutil
 
-conda install -n pandas -c conda-forge feather-format pyarrow=0.4.1
+conda install -n pandas -c conda-forge feather-format pyarrow=0.5.0

ci/requirements-3.5.sh

@@ -8,7 +8,6 @@ xlrd
 xlwt
 scipy
 feather-format
-pyarrow
 numexpr
 pytables
 matplotlib

ci/requirements-3.6_NUMPY_DEV.pip

@@ -5,3 +5,4 @@ cython
 pytest>=3.1.0
 pytest-cov
 flake8
+moto

ci/requirements-3.6_WIN.pip

@@ -3,9 +3,11 @@
 Contributing to the documentation
 =================================
 
-If you're not the developer type, contributing to the documentation is still
-of huge value. You don't even have to be an expert on
-*pandas* to do so! Something as simple as rewriting small passages for clarity
+Whether you are someone who loves writing, teaching, or development,
+contributing to the documentation is a huge value. If you don't see yourself
+as a developer type, please don't stress and know that we want you to
+contribute. You don't even have to be an expert on *pandas* to do so!
+Something as simple as rewriting small passages for clarity
 as you reference the docs is a simple but effective way to contribute. The
 next person to read that passage will be in your debt!
 

ci/requirements-3.6_WIN.run

@@ -655,7 +655,7 @@ the quarter end:
 Categoricals
 ------------
 
-Since version 0.15, pandas can include categorical data in a ``DataFrame``. For full docs, see the
+pandas can include categorical data in a ``DataFrame``. For full docs, see the
 :ref:`categorical introduction <categorical>` and the :ref:`API documentation <api.categorical>`.
 
 .. ipython:: python