Merge pull request #4864 from dalejung/panel-tshift-4853

Panel tshift 4853

Author: jreback

doc/source/release.rst

@@ -428,6 +428,7 @@ Bug Fixes
     single column and passing a list for ``ascending``, the argument for
     ``ascending`` was being interpreted as ``True`` (:issue:`4839`,
     :issue:`4846`)
+  - Fixed ``Panel.tshift`` not working. Added `freq` support to ``Panel.shift`` (:issue:`4853`)
 
 pandas 0.12.0
 -------------

pandas/core/datetools.py

@@ -35,3 +35,23 @@
 isBusinessDay = BDay().onOffset
 isMonthEnd = MonthEnd().onOffset
 isBMonthEnd = BMonthEnd().onOffset
+
+def _resolve_offset(freq, kwds):
+    if 'timeRule' in kwds or 'offset' in kwds:
+        offset = kwds.get('offset', None)
+        offset = kwds.get('timeRule', offset)
+        if isinstance(offset, compat.string_types):
+            offset = getOffset(offset)
+        warn = True
+    else:
+        offset = freq
+        warn = False
+
+    if warn:
+        import warnings
+        warnings.warn("'timeRule' and 'offset' parameters are deprecated,"
+                      " please use 'freq' instead",
+                      FutureWarning)
+
+    return offset
+

pandas/core/frame.py

@@ -3497,55 +3497,6 @@ def diff(self, periods=1):
         new_data = self._data.diff(periods)
         return self._constructor(new_data)
 
-    def shift(self, periods=1, freq=None, **kwds):
-        """
-        Shift the index of the DataFrame by desired number of periods with an
-        optional time freq
-
-        Parameters
-        ----------
-        periods : int
-            Number of periods to move, can be positive or negative
-        freq : DateOffset, timedelta, or time rule string, optional
-            Increment to use from datetools module or time rule (e.g. 'EOM')
-
-        Notes
-        -----
-        If freq is specified then the index values are shifted but the data
-        if not realigned
-
-        Returns
-        -------
-        shifted : DataFrame
-        """
-        from pandas.core.series import _resolve_offset
-
-        if periods == 0:
-            return self
-
-        offset = _resolve_offset(freq, kwds)
-
-        if isinstance(offset, compat.string_types):
-            offset = datetools.to_offset(offset)
-
-        if offset is None:
-            indexer = com._shift_indexer(len(self), periods)
-            new_data = self._data.shift(indexer, periods)
-        elif isinstance(self.index, PeriodIndex):
-            orig_offset = datetools.to_offset(self.index.freq)
-            if offset == orig_offset:
-                new_data = self._data.copy()
-                new_data.axes[1] = self.index.shift(periods)
-            else:
-                msg = ('Given freq %s does not match PeriodIndex freq %s' %
-                       (offset.rule_code, orig_offset.rule_code))
-                raise ValueError(msg)
-        else:
-            new_data = self._data.copy()
-            new_data.axes[1] = self.index.shift(periods, offset)
-
-        return self._constructor(new_data)
-
     #----------------------------------------------------------------------
     # Function application
 

pandas/core/generic.py

@@ -11,8 +11,10 @@
 import pandas.core.indexing as indexing
 from pandas.core.indexing import _maybe_convert_indices
 from pandas.tseries.index import DatetimeIndex
+from pandas.tseries.period import PeriodIndex
 from pandas.core.internals import BlockManager
 import pandas.core.common as com
+import pandas.core.datetools as datetools
 from pandas import compat, _np_version_under1p7
 from pandas.compat import map, zip, lrange
 from pandas.core.common import (isnull, notnull, is_list_like,
@@ -2667,7 +2669,40 @@ def cummin(self, axis=None, skipna=True):
             result = np.minimum.accumulate(y, axis)
         return self._wrap_array(result, self.axes, copy=False)
 
-    def tshift(self, periods=1, freq=None, **kwds):
+    def shift(self, periods=1, freq=None, axis=0, **kwds):
+        """
+        Shift the index of the DataFrame by desired number of periods with an
+        optional time freq
+
+        Parameters
+        ----------
+        periods : int
+            Number of periods to move, can be positive or negative
+        freq : DateOffset, timedelta, or time rule string, optional
+            Increment to use from datetools module or time rule (e.g. 'EOM')
+
+        Notes
+        -----
+        If freq is specified then the index values are shifted but the data
+        if not realigned
+
+        Returns
+        -------
+        shifted : DataFrame
+        """
+        if periods == 0:
+            return self
+
+        if freq is None and not len(kwds):
+            block_axis = self._get_block_manager_axis(axis)
+            indexer = com._shift_indexer(len(self), periods)
+            new_data = self._data.shift(indexer, periods, axis=block_axis)
+        else:
+            return self.tshift(periods, freq, **kwds)
+
+        return self._constructor(new_data)
+
+    def tshift(self, periods=1, freq=None, axis=0, **kwds):
         """
         Shift the time index, using the index's frequency if available
 
@@ -2677,6 +2712,8 @@ def tshift(self, periods=1, freq=None, **kwds):
             Number of periods to move, can be positive or negative
         freq : DateOffset, timedelta, or time rule string, default None
             Increment to use from datetools module or time rule (e.g. 'EOM')
+        axis : int or basestring
+            Corresponds to the axis that contains the Index
 
         Notes
         -----
@@ -2686,19 +2723,45 @@ def tshift(self, periods=1, freq=None, **kwds):
 
         Returns
         -------
-        shifted : Series
+        shifted : NDFrame
         """
+        from pandas.core.datetools import _resolve_offset
+
+        index = self._get_axis(axis)
         if freq is None:
-            freq = getattr(self.index, 'freq', None)
+            freq = getattr(index, 'freq', None)
 
         if freq is None:
-            freq = getattr(self.index, 'inferred_freq', None)
+            freq = getattr(index, 'inferred_freq', None)
 
         if freq is None:
             msg = 'Freq was not given and was not set in the index'
             raise ValueError(msg)
 
-        return self.shift(periods, freq, **kwds)
+
+        if periods == 0:
+            return self
+
+        offset = _resolve_offset(freq, kwds)
+
+        if isinstance(offset, compat.string_types):
+            offset = datetools.to_offset(offset)
+
+        block_axis = self._get_block_manager_axis(axis)
+        if isinstance(index, PeriodIndex):
+            orig_offset = datetools.to_offset(index.freq)
+            if offset == orig_offset:
+                new_data = self._data.copy()
+                new_data.axes[block_axis] = index.shift(periods)
+            else:
+                msg = ('Given freq %s does not match PeriodIndex freq %s' %
+                       (offset.rule_code, orig_offset.rule_code))
+                raise ValueError(msg)
+        else:
+            new_data = self._data.copy()
+            new_data.axes[block_axis] = index.shift(periods, offset)
+
+        return self._constructor(new_data)
 
     def truncate(self, before=None, after=None, copy=True):
         """Function truncate a sorted DataFrame / Series before and/or after

pandas/core/internals.py

@@ -758,17 +758,27 @@ def diff(self, n):
         new_values = com.diff(self.values, n, axis=1)
         return [make_block(new_values, self.items, self.ref_items, ndim=self.ndim, fastpath=True)]
 
-    def shift(self, indexer, periods):
+    def shift(self, indexer, periods, axis=0):
         """ shift the block by periods, possibly upcast """
 
-        new_values = self.values.take(indexer, axis=1)
+        new_values = self.values.take(indexer, axis=axis)
         # convert integer to float if necessary. need to do a lot more than
         # that, handle boolean etc also
         new_values, fill_value = com._maybe_upcast(new_values)
-        if periods > 0:
-            new_values[:, :periods] = fill_value
+
+        # 1-d
+        if self.ndim == 1:
+            if periods > 0:
+                new_values[:periods] = fill_value
+            else:
+                new_values[periods:] = fill_value
+
+        # 2-d
         else:
-            new_values[:, periods:] = fill_value
+            if periods > 0:
+                new_values[:, :periods] = fill_value
+            else:
+                new_values[:, periods:] = fill_value
         return [make_block(new_values, self.items, self.ref_items, ndim=self.ndim, fastpath=True)]
 
     def eval(self, func, other, raise_on_error=True, try_cast=False):
@@ -1547,7 +1557,7 @@ def fillna(self, value, inplace=False, downcast=None):
         values = self.values if inplace else self.values.copy()
         return [ self.make_block(values.get_values(value), fill_value=value) ]
 
-    def shift(self, indexer, periods):
+    def shift(self, indexer, periods, axis=0):
         """ shift the block by periods """
 
         new_values = self.values.to_dense().take(indexer)

pandas/core/panel.py

@@ -1017,7 +1017,7 @@ def count(self, axis='major'):
 
         return self._wrap_result(result, axis)
 
-    def shift(self, lags, axis='major'):
+    def shift(self, lags, freq=None, axis='major'):
         """
         Shift major or minor axis by specified number of leads/lags. Drops
         periods right now compared with DataFrame.shift
@@ -1036,6 +1036,9 @@ def shift(self, lags, axis='major'):
         major_axis = self.major_axis
         minor_axis = self.minor_axis
 
+        if freq:
+            return self.tshift(lags, freq, axis=axis)
+
         if lags > 0:
             vslicer = slice(None, -lags)
             islicer = slice(lags, None)
@@ -1058,6 +1061,9 @@ def shift(self, lags, axis='major'):
         return self._constructor(values, items=items, major_axis=major_axis,
                                  minor_axis=minor_axis)
 
+    def tshift(self, periods=1, freq=None, axis='major', **kwds):
+        return super(Panel, self).tshift(periods, freq, axis, **kwds)
+
     def truncate(self, before=None, after=None, axis='major'):
         """Function truncates a sorted Panel before and/or after some
         particular values on the requested axis

pandas/core/series.py

@@ -59,8 +59,6 @@
 _np_version_under1p6 = LooseVersion(_np_version) < '1.6'
 _np_version_under1p7 = LooseVersion(_np_version) < '1.7'
 
-_SHOW_WARNINGS = True
-
 class _TimeOp(object):
     """
     Wrapper around Series datetime/time/timedelta arithmetic operations.
@@ -2917,62 +2915,6 @@ def last_valid_index(self):
     #----------------------------------------------------------------------
     # Time series-oriented methods
 
-    def shift(self, periods=1, freq=None, copy=True, **kwds):
-        """
-        Shift the index of the Series by desired number of periods with an
-        optional time offset
-
-        Parameters
-        ----------
-        periods : int
-            Number of periods to move, can be positive or negative
-        freq : DateOffset, timedelta, or offset alias string, optional
-            Increment to use from datetools module or time rule (e.g. 'EOM')
-
-        Returns
-        -------
-        shifted : Series
-        """
-        if periods == 0:
-            return self.copy()
-
-        offset = _resolve_offset(freq, kwds)
-
-        if isinstance(offset, compat.string_types):
-            offset = datetools.to_offset(offset)
-
-        def _get_values():
-            values = self.values
-            if copy:
-                values = values.copy()
-            return values
-
-        if offset is None:
-            dtype, fill_value = _maybe_promote(self.dtype)
-            new_values = pa.empty(len(self), dtype=dtype)
-
-            if periods > 0:
-                new_values[periods:] = self.values[:-periods]
-                new_values[:periods] = fill_value
-            elif periods < 0:
-                new_values[:periods] = self.values[-periods:]
-                new_values[periods:] = fill_value
-
-            return self._constructor(new_values, index=self.index, name=self.name)
-        elif isinstance(self.index, PeriodIndex):
-            orig_offset = datetools.to_offset(self.index.freq)
-            if orig_offset == offset:
-                return self._constructor(
-                    _get_values(), self.index.shift(periods),
-                    name=self.name)
-            msg = ('Given freq %s does not match PeriodIndex freq %s' %
-                   (offset.rule_code, orig_offset.rule_code))
-            raise ValueError(msg)
-        else:
-            return self._constructor(_get_values(),
-                                     index=self.index.shift(periods, offset),
-                                     name=self.name)
-
     def asof(self, where):
         """
         Return last good (non-NaN) value in TimeSeries if value is NaN for
@@ -3317,26 +3259,6 @@ def _try_cast(arr, take_fast_path):
 
     return subarr
 
-def _resolve_offset(freq, kwds):
-    if 'timeRule' in kwds or 'offset' in kwds:
-        offset = kwds.get('offset', None)
-        offset = kwds.get('timeRule', offset)
-        if isinstance(offset, compat.string_types):
-            offset = datetools.getOffset(offset)
-        warn = True
-    else:
-        offset = freq
-        warn = False
-
-    if warn and _SHOW_WARNINGS:  # pragma: no cover
-        import warnings
-        warnings.warn("'timeRule' and 'offset' parameters are deprecated,"
-                      " please use 'freq' instead",
-                      FutureWarning)
-
-    return offset
-
-
 # backwards compatiblity
 TimeSeries = Series
 

pandas/sparse/series.py

@@ -605,7 +605,7 @@ def shift(self, periods, freq=None, **kwds):
         """
         Analogous to Series.shift
         """
-        from pandas.core.series import _resolve_offset
+        from pandas.core.datetools import _resolve_offset
 
         offset = _resolve_offset(freq, kwds)