Make *_range functions consistent (pandas-dev#17482)

doc/source/api.rst

@@ -218,10 +218,19 @@ Top-level dealing with datetimelike
    to_timedelta
    date_range
    bdate_range
+   cdate_range
    period_range
    timedelta_range
    infer_freq
 
+Top-level dealing with intervals
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autosummary::
+   :toctree: generated/
+
+   interval_range
+
 Top-level evaluation
 ~~~~~~~~~~~~~~~~~~~~
 

doc/source/timeseries.rst

@@ -1705,6 +1705,15 @@ has multiplied span.
 
    pd.PeriodIndex(start='2014-01', freq='3M', periods=4)
 
+If ``start`` or ``end`` are ``Period`` objects, they will be used as anchor
+endpoints for a ``PeriodIndex`` with frequency matching that of the
+``PeriodIndex`` constructor.
+
+.. ipython:: python
+
+   pd.PeriodIndex(start=pd.Period('2017Q1', freq='Q'),
+                  end=pd.Period('2017Q2', freq='Q'), freq='M')
+
 Just like ``DatetimeIndex``, a ``PeriodIndex`` can also be used to index pandas
 objects:
 

doc/source/whatsnew/v0.21.0.txt

@@ -218,7 +218,7 @@ Furthermore this will now correctly box the results of iteration for :func:`Data
 .. ipython:: ipython
 
    d = {'a':[1], 'b':['b']}
-   df = pd,DataFrame(d)
+   df = pd.DataFrame(d)
 
 Previously:
 
@@ -358,6 +358,59 @@ Previously, :func:`to_datetime` did not localize datetime ``Series`` data when `
 
 Additionally, DataFrames with datetime columns that were parsed by :func:`read_sql_table` and :func:`read_sql_query` will also be localized to UTC only if the original SQL columns were timezone aware datetime columns.
 
+.. _whatsnew_0210.api.consistency_of_range_functions:
+
+Consistency of Range Functions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+In previous versions, there were some inconsistencies between the various range functions: func:`date_range`, func:`bdate_range`, func:`cdate_range`, func:`period_range`, func:`timedelta_range`, and func:`interval_range`. (:issue:`17471`).
+
+One of the inconsistent behaviors occurred when the ``start``, ``end`` and ``period`` parameters were all specified, potentially leading to ambiguous ranges.  When all three parameters were passed, ``interval_range`` ignored the ``period`` parameter, ``period_range`` ignored the ``end`` parameter, and the other range functions raised.  To promote consistency among the range functions, and avoid potentially ambiguous ranges, ``interval_range`` and ``period_range`` will now raise when all three parameters are passed.
+
+Previous Behavior:
+
+.. code-block:: ipython
+
+  In [2]: pd.interval_range(start=0, end=4, periods=6)
+  Out[2]:
+  IntervalIndex([(0, 1], (1, 2], (2, 3]]
+                closed='right',
+                dtype='interval[int64]')
+
+  In [3]: pd.period_range(start='2017Q1', end='2017Q4', periods=6, freq='Q')
+  Out[3]: PeriodIndex(['2017Q1', '2017Q2', '2017Q3', '2017Q4', '2018Q1', '2018Q2'], dtype='period[Q-DEC]', freq='Q-DEC')
+
+New Behavior:
+
+.. code-block:: ipython
+
+  In [2]: pd.interval_range(start=0, end=4, periods=6)
+  ---------------------------------------------------------------------------
+  ValueError: Of the three parameters: start, end, and periods, exactly two must be specified
+
+  In [3]: pd.period_range(start='2017Q1', end='2017Q4', periods=6, freq='Q')  
+  ---------------------------------------------------------------------------
+  ValueError: Of the three parameters: start, end, and periods, exactly two must be specified
+
+Additionally, the endpoint parameter ``end`` was not included in the intervals produced by ``interval_range``.  However, all other range functions include ``end`` in their output.  To promote consistency among the range functions, ``interval_range`` will now include ``end`` as the right endpoint of the final interval, except if ``freq`` is specified in a way which skips ``end``.
+
+Previous Behavior:
+
+.. code-block:: ipython
+
+  In [4]: pd.interval_range(start=0, end=4)
+  Out[4]:
+  IntervalIndex([(0, 1], (1, 2], (2, 3]]
+                closed='right',
+                dtype='interval[int64]')
+
+
+New Behavior:
+
+  .. ipython:: python
+
+     pd.interval_range(start=0, end=4)
+
 .. _whatsnew_0210.api:
 
 Other API Changes

pandas/core/indexes/datetimes.py

@@ -292,8 +292,8 @@ def __new__(cls, data=None,
             if is_float(periods):
                 periods = int(periods)
             elif not is_integer(periods):
-                raise ValueError('Periods must be a number, got %s' %
-                                 str(periods))
+                msg = 'periods must be a number, got {periods}'
+                raise TypeError(msg.format(periods=periods))
 
         if data is None and freq is None:
             raise ValueError("Must provide freq argument if no data is "
@@ -412,7 +412,8 @@ def __new__(cls, data=None,
     def _generate(cls, start, end, periods, name, offset,
                   tz=None, normalize=False, ambiguous='raise', closed=None):
         if com._count_not_none(start, end, periods) != 2:
-            raise ValueError('Must specify two of start, end, or periods')
+            raise ValueError('Of the three parameters: start, end, and '
+                             'periods, exactly two must be specified')
 
         _normalized = True
 
@@ -2004,7 +2005,7 @@ def _generate_regular_range(start, end, periods, offset):
 def date_range(start=None, end=None, periods=None, freq='D', tz=None,
                normalize=False, name=None, closed=None, **kwargs):
     """
-    Return a fixed frequency datetime index, with day (calendar) as the default
+    Return a fixed frequency DatetimeIndex, with day (calendar) as the default
     frequency
 
     Parameters
@@ -2013,24 +2014,25 @@ def date_range(start=None, end=None, periods=None, freq='D', tz=None,
         Left bound for generating dates
     end : string or datetime-like, default None
         Right bound for generating dates
-    periods : integer or None, default None
-        If None, must specify start and end
+    periods : integer, default None
+        Number of periods to generate
     freq : string or DateOffset, default 'D' (calendar daily)
         Frequency strings can have multiples, e.g. '5H'
-    tz : string or None
+    tz : string, default None
         Time zone name for returning localized DatetimeIndex, for example
         Asia/Hong_Kong
     normalize : bool, default False
         Normalize start/end dates to midnight before generating date range
-    name : str, default None
-        Name of the resulting index
-    closed : string or None, default None
+    name : string, default None
+        Name of the resulting DatetimeIndex
+    closed : string, default None
         Make the interval closed with respect to the given frequency to
         the 'left', 'right', or both sides (None)
 
     Notes
     -----
-    2 of start, end, or periods must be specified
+    Of the three parameters: ``start``, ``end``, and ``periods``, exactly two
+    must be specified.
 
     To learn more about the frequency strings, please see `this link
     <http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.
@@ -2047,7 +2049,7 @@ def date_range(start=None, end=None, periods=None, freq='D', tz=None,
 def bdate_range(start=None, end=None, periods=None, freq='B', tz=None,
                 normalize=True, name=None, closed=None, **kwargs):
     """
-    Return a fixed frequency datetime index, with business day as the default
+    Return a fixed frequency DatetimeIndex, with business day as the default
     frequency
 
     Parameters
@@ -2056,24 +2058,25 @@ def bdate_range(start=None, end=None, periods=None, freq='B', tz=None,
         Left bound for generating dates
     end : string or datetime-like, default None
         Right bound for generating dates
-    periods : integer or None, default None
-        If None, must specify start and end
+    periods : integer, default None
+        Number of periods to generate
     freq : string or DateOffset, default 'B' (business daily)
         Frequency strings can have multiples, e.g. '5H'
     tz : string or None
         Time zone name for returning localized DatetimeIndex, for example
         Asia/Beijing
     normalize : bool, default False
         Normalize start/end dates to midnight before generating date range
-    name : str, default None
-        Name for the resulting index
-    closed : string or None, default None
+    name : string, default None
+        Name of the resulting DatetimeIndex
+    closed : string, default None
         Make the interval closed with respect to the given frequency to
         the 'left', 'right', or both sides (None)
 
     Notes
     -----
-    2 of start, end, or periods must be specified
+    Of the three parameters: ``start``, ``end``, and ``periods``, exactly two
+    must be specified.
 
     To learn more about the frequency strings, please see `this link
     <http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.
@@ -2091,7 +2094,7 @@ def bdate_range(start=None, end=None, periods=None, freq='B', tz=None,
 def cdate_range(start=None, end=None, periods=None, freq='C', tz=None,
                 normalize=True, name=None, closed=None, **kwargs):
     """
-    **EXPERIMENTAL** Return a fixed frequency datetime index, with
+    **EXPERIMENTAL** Return a fixed frequency DatetimeIndex, with
     CustomBusinessDay as the default frequency
 
     .. warning:: EXPERIMENTAL
@@ -2105,29 +2108,30 @@ def cdate_range(start=None, end=None, periods=None, freq='C', tz=None,
         Left bound for generating dates
     end : string or datetime-like, default None
         Right bound for generating dates
-    periods : integer or None, default None
-        If None, must specify start and end
+    periods : integer, default None
+        Number of periods to generate
     freq : string or DateOffset, default 'C' (CustomBusinessDay)
         Frequency strings can have multiples, e.g. '5H'
-    tz : string or None
+    tz : string, default None
         Time zone name for returning localized DatetimeIndex, for example
         Asia/Beijing
     normalize : bool, default False
         Normalize start/end dates to midnight before generating date range
-    name : str, default None
-        Name for the resulting index
-    weekmask : str, Default 'Mon Tue Wed Thu Fri'
+    name : string, default None
+        Name of the resulting DatetimeIndex
+    weekmask : string, Default 'Mon Tue Wed Thu Fri'
         weekmask of valid business days, passed to ``numpy.busdaycalendar``
     holidays : list
         list/array of dates to exclude from the set of valid business days,
         passed to ``numpy.busdaycalendar``
-    closed : string or None, default None
+    closed : string, default None
         Make the interval closed with respect to the given frequency to
         the 'left', 'right', or both sides (None)
 
     Notes
     -----
-    2 of start, end, or periods must be specified
+    Of the three parameters: ``start``, ``end``, and ``periods``, exactly two
+    must be specified.
 
     To learn more about the frequency strings, please see `this link
     <http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.