BUG: resample fixes

make sure .resample(...).plot() warns and returns a correct plotting
object  make sure that .groupby(...).resample(....) is hitting
warnings when appropriate    closes #12448

Author: Jeff Reback <jeff@reback.net>

Closes #12449 from jreback/resample and squashes the following commits:

4a49f1b [Jeff Reback] BUG: resample fixes

Author: jreback

doc/source/whatsnew/v0.18.0.txt

@@ -705,7 +705,7 @@ other anchored offsets like ``MonthBegin`` and ``YearBegin``.
 Resample API
 ^^^^^^^^^^^^
 
-Like the change in the window functions API :ref:`above <whatsnew_0180.enhancements.moments>`, ``.resample(...)`` is changing to have a more groupby-like API. (:issue:`11732`, :issue:`12702`, :issue:`12202`, :issue:`12332`, :issue:`12334`, :issue:`12348`).
+Like the change in the window functions API :ref:`above <whatsnew_0180.enhancements.moments>`, ``.resample(...)`` is changing to have a more groupby-like API. (:issue:`11732`, :issue:`12702`, :issue:`12202`, :issue:`12332`, :issue:`12334`, :issue:`12348`, :issue:`12448`).
 
 .. ipython:: python
 
@@ -774,6 +774,29 @@ You could also specify a ``how`` directly
             use .resample(...).mean() instead of .resample(...)
             assignment will have no effect as you are working on a copy
 
+   There is a situation where the new API can not perform all the operations when using original code.
+   This code is intending to resample every 2s, take the ``mean`` AND then take the ``min` of those results.
+
+   .. code-block:: python
+
+      In [4]: df.resample('2s').min()
+      Out[4]:
+      A    0.433985
+      B    0.314582
+      C    0.357096
+      D    0.531096
+      dtype: float64
+
+   The new API will:
+
+   .. ipython: python
+
+      df.resample('2s').min()
+
+   Good news is the return dimensions will differ (between the new API and the old API), so this should loudly raise
+   an exception.
+
+
 **New API**:
 
 Now, you can write ``.resample`` as a 2-stage operation like groupby, which

pandas/core/generic.py

@@ -3932,57 +3932,18 @@ def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
         Freq: 3T, dtype: int64
 
         """
-        from pandas.tseries.resample import resample
+        from pandas.tseries.resample import (resample,
+                                             _maybe_process_deprecations)
 
         axis = self._get_axis_number(axis)
         r = resample(self, freq=rule, label=label, closed=closed,
                      axis=axis, kind=kind, loffset=loffset,
-                     fill_method=fill_method, convention=convention,
-                     limit=limit, base=base)
-
-        # deprecation warnings
-        # but call methods anyhow
-
-        if how is not None:
-
-            # .resample(..., how='sum')
-            if isinstance(how, compat.string_types):
-                method = "{0}()".format(how)
-
-            # .resample(..., how=lambda x: ....)
-            else:
-                method = ".apply(<func>)"
-
-            # if we have both a how and fill_method, then show
-            # the following warning
-            if fill_method is None:
-                warnings.warn("how in .resample() is deprecated\n"
-                              "the new syntax is "
-                              ".resample(...).{method}".format(
-                                  method=method),
-                              FutureWarning, stacklevel=2)
-            r = r.aggregate(how)
-
-        if fill_method is not None:
-
-            # show the prior function call
-            method = '.' + method if how is not None else ''
-
-            args = "limit={0}".format(limit) if limit is not None else ""
-            warnings.warn("fill_method is deprecated to .resample()\n"
-                          "the new syntax is .resample(...){method}"
-                          ".{fill_method}({args})".format(
-                              method=method,
-                              fill_method=fill_method,
-                              args=args),
-                          FutureWarning, stacklevel=2)
-
-            if how is not None:
-                r = getattr(r, fill_method)(limit=limit)
-            else:
-                r = r.aggregate(fill_method, limit=limit)
-
-        return r
+                     convention=convention,
+                     base=base)
+        return _maybe_process_deprecations(r,
+                                           how=how,
+                                           fill_method=fill_method,
+                                           limit=limit)
 
     def first(self, offset):
         """

pandas/core/groupby.py

@@ -1044,27 +1044,71 @@ def ohlc(self):
 
     @Substitution(name='groupby')
     @Appender(_doc_template)
-    def resample(self, rule, **kwargs):
+    def resample(self, rule, how=None, fill_method=None, limit=None, **kwargs):
         """
         Provide resampling when using a TimeGrouper
         Return a new grouper with our resampler appended
         """
-        from pandas.tseries.resample import TimeGrouper
+        from pandas.tseries.resample import (TimeGrouper,
+                                             _maybe_process_deprecations)
         gpr = TimeGrouper(axis=self.axis, freq=rule, **kwargs)
 
         # we by definition have at least 1 key as we are already a grouper
         groupings = list(self.grouper.groupings)
         groupings.append(gpr)
 
-        return self.__class__(self.obj,
-                              keys=groupings,
-                              axis=self.axis,
-                              level=self.level,
-                              as_index=self.as_index,
-                              sort=self.sort,
-                              group_keys=self.group_keys,
-                              squeeze=self.squeeze,
-                              selection=self._selection)
+        result = self.__class__(self.obj,
+                                keys=groupings,
+                                axis=self.axis,
+                                level=self.level,
+                                as_index=self.as_index,
+                                sort=self.sort,
+                                group_keys=self.group_keys,
+                                squeeze=self.squeeze,
+                                selection=self._selection)
+
+        return _maybe_process_deprecations(result,
+                                           how=how,
+                                           fill_method=fill_method,
+                                           limit=limit)
+
+    @Substitution(name='groupby')
+    @Appender(_doc_template)
+    def pad(self, limit=None):
+        """
+        Forward fill the values
+
+        Parameters
+        ----------
+        limit : integer, optional
+            limit of how many values to fill
+
+        See Also
+        --------
+        Series.fillna
+        DataFrame.fillna
+        """
+        return self.apply(lambda x: x.ffill(limit=limit))
+    ffill = pad
+
+    @Substitution(name='groupby')
+    @Appender(_doc_template)
+    def backfill(self, limit=None):
+        """
+        Backward fill the values
+
+        Parameters
+        ----------
+        limit : integer, optional
+            limit of how many values to fill
+
+        See Also
+        --------
+        Series.fillna
+        DataFrame.fillna
+        """
+        return self.apply(lambda x: x.bfill(limit=limit))
+    bfill = backfill
 
     @Substitution(name='groupby')
     @Appender(_doc_template)

pandas/tests/test_graphics.py

@@ -17,7 +17,9 @@
 from pandas.util.decorators import cache_readonly
 import pandas.core.common as com
 import pandas.util.testing as tm
-from pandas.util.testing import ensure_clean
+from pandas.util.testing import (ensure_clean,
+                                 assert_is_valid_plot_return_object)
+
 from pandas.core.config import set_option
 
 import numpy as np
@@ -3916,21 +3918,6 @@ def test_plot_kwargs(self):
         self.assertEqual(len(res['a'].collections), 1)
 
 
-def assert_is_valid_plot_return_object(objs):
-    import matplotlib.pyplot as plt
-    if isinstance(objs, np.ndarray):
-        for el in objs.flat:
-            assert isinstance(el, plt.Axes), ('one of \'objs\' is not a '
-                                              'matplotlib Axes instance, '
-                                              'type encountered {0!r}'
-                                              ''.format(el.__class__.__name__))
-    else:
-        assert isinstance(objs, (plt.Artist, tuple, dict)), \
-            ('objs is neither an ndarray of Artist instances nor a '
-             'single Artist instance, tuple, or dict, "objs" is a {0!r} '
-             ''.format(objs.__class__.__name__))
-
-
 def _check_plot_works(f, filterwarnings='always', **kwargs):
     import matplotlib.pyplot as plt
     ret = None

pandas/tests/test_groupby.py

@@ -5610,7 +5610,8 @@ def test_tab_completion(self):
              'cumprod', 'tail', 'resample', 'cummin', 'fillna', 'cumsum',
              'cumcount', 'all', 'shift', 'skew', 'bfill', 'ffill', 'take',
              'tshift', 'pct_change', 'any', 'mad', 'corr', 'corrwith', 'cov',
-             'dtypes', 'ndim', 'diff', 'idxmax', 'idxmin'])
+             'dtypes', 'ndim', 'diff', 'idxmax', 'idxmin',
+             'ffill', 'bfill', 'pad', 'backfill'])
         self.assertEqual(results, expected)
 
     def test_lexsort_indexer(self):

pandas/tseries/resample.py

@@ -102,7 +102,7 @@ def _typ(self):
     def _deprecated(self):
         warnings.warn(".resample() is now a deferred operation\n"
                       "use .resample(...).mean() instead of .resample(...)",
-                      FutureWarning, stacklevel=2)
+                      FutureWarning, stacklevel=3)
         return self.mean()
 
     def _make_deprecated_binop(op):
@@ -154,9 +154,7 @@ def __getattr__(self, attr):
         if attr in self._deprecated_invalids:
             raise ValueError(".resample() is now a deferred operation\n"
                              "\tuse .resample(...).mean() instead of "
-                             ".resample(...)\n"
-                             "\tassignment will have no effect as you "
-                             "are working on a copy")
+                             ".resample(...)")
         if attr not in self._deprecated_valids:
             self = self._deprecated()
         return object.__getattribute__(self, attr)
@@ -167,6 +165,17 @@ def __setattr__(self, attr, value):
                 self.__class__.__name__))
         object.__setattr__(self, attr, value)
 
+    def __getitem__(self, key):
+        try:
+            return super(Resampler, self).__getitem__(key)
+        except (KeyError, com.AbstractMethodError):
+
+            # compat for deprecated
+            if isinstance(self.obj, com.ABCSeries):
+                return self._deprecated()[key]
+
+            raise
+
     def __setitem__(self, attr, value):
         raise ValueError("cannot set items on {0}".format(
             self.__class__.__name__))
@@ -208,6 +217,11 @@ def _assure_grouper(self):
         """ make sure that we are creating our binner & grouper """
         self._set_binner()
 
+    def plot(self, *args, **kwargs):
+        # for compat with prior versions, we want to
+        # have the warnings shown here and just have this work
+        return self._deprecated().plot(*args, **kwargs)
+
     def aggregate(self, arg, *args, **kwargs):
         """
         Apply aggregation function or functions to resampled groups, yielding
@@ -468,6 +482,52 @@ def f(self, _method=method):
     setattr(Resampler, method, f)
 
 
+def _maybe_process_deprecations(r, how=None, fill_method=None, limit=None):
+    """ potentially we might have a deprecation warning, show it
+    but call the appropriate methods anyhow """
+
+    if how is not None:
+
+        # .resample(..., how='sum')
+        if isinstance(how, compat.string_types):
+            method = "{0}()".format(how)
+
+            # .resample(..., how=lambda x: ....)
+        else:
+            method = ".apply(<func>)"
+
+        # if we have both a how and fill_method, then show
+        # the following warning
+        if fill_method is None:
+            warnings.warn("how in .resample() is deprecated\n"
+                          "the new syntax is "
+                          ".resample(...).{method}".format(
+                              method=method),
+                          FutureWarning, stacklevel=3)
+        r = r.aggregate(how)
+
+    if fill_method is not None:
+
+        # show the prior function call
+        method = '.' + method if how is not None else ''
+
+        args = "limit={0}".format(limit) if limit is not None else ""
+        warnings.warn("fill_method is deprecated to .resample()\n"
+                      "the new syntax is .resample(...){method}"
+                      ".{fill_method}({args})".format(
+                          method=method,
+                          fill_method=fill_method,
+                          args=args),
+                      FutureWarning, stacklevel=3)
+
+        if how is not None:
+            r = getattr(r, fill_method)(limit=limit)
+        else:
+            r = r.aggregate(fill_method, limit=limit)
+
+    return r
+
+
 class DatetimeIndexResampler(Resampler):
 
     def _get_binner_for_time(self):