ENH: gb.is_monotonic_increasing pandas-dev#17015 fix rebase conflicts

Author: No-Stream

doc/source/whatsnew/v0.21.0.txt

@@ -309,11 +309,21 @@ New keywords
 - :func:`read_feather` has gained the ``nthreads`` parameter for multi-threaded operations (:issue:`16359`)
 - :func:`DataFrame.clip()` and :func:`Series.clip()` have gained an ``inplace`` argument. (:issue:`15388`)
 - :func:`crosstab` has gained a ``margins_name`` parameter to define the name of the row / column that will contain the totals when ``margins=True``. (:issue:`15972`)
+<<<<<<< HEAD
 - :func:`read_json` now accepts a ``chunksize`` parameter that can be used when ``lines=True``. If ``chunksize`` is passed, read_json now returns an iterator which reads in ``chunksize`` lines with each iteration. (:issue:`17048`)
 - :func:`read_json` and :func:`~DataFrame.to_json` now accept a ``compression`` argument which allows them to transparently handle compressed files. (:issue:`17798`)
 
 Various enhancements
 """"""""""""""""""""
+=======
+- :func:`DataFrame.select_dtypes` now accepts scalar values for include/exclude as well as list-like. (:issue:`16855`)
+- :func:`date_range` now accepts 'YS' in addition to 'AS' as an alias for start of year (:issue:`9313`)
+- :func:`date_range` now accepts 'Y' in addition to 'A' as an alias for end of year (:issue:`9313`)
+- Integration with `Apache Parquet <https://parquet.apache.org/>`__, including a new top-level :func:`read_parquet` and :func:`DataFrame.to_parquet` method, see :ref:`here <io.parquet>`.
+- :func:`DataFrame.add_prefix` and :func:`DataFrame.add_suffix` now accept strings containing the '%' character. (:issue:`17151`)
+- `read_*` methods can now infer compression from non-string paths, such as ``pathlib.Path`` objects (:issue:`17206`).
+- :func:`pd.read_sas()` now recognizes much more of the most frequently used date (datetime) formats in SAS7BDAT files (:issue:`15871`).
+- :func:`DataFrame.items` and :func:`Series.items` is now present in both Python 2 and 3 and is lazy in all cases (:issue:`13918`, :issue:`17213`)
 
 - Improved the import time of pandas by about 2.25x.  (:issue:`16764`)
 - Support for `PEP 519 -- Adding a file system path protocol

doc/source/whatsnew/v0.21.1.txt

@@ -22,7 +22,7 @@ Other Enhancements
 ^^^^^^^^^^^^^^^^^^
 
 - :meth:`Timestamp.timestamp` is now available in Python 2.7. (:issue:`17329`)
--
+- :func: groupby.is_monotonic_increasing and .is_monotonic_decreasing extend Series.is_monotonic_increasing to groups, returning whether each group is monotonically increasing or decreasing, respectively. (:issue:`17015`)
 -
 
 .. _whatsnew_0211.deprecations:

pandas/core/groupby.py

@@ -1743,6 +1743,55 @@ def pipe(self, func, *args, **kwargs):
         """
         return _pipe(self, func, *args, **kwargs)
 
+    @Substitution(name='groupby')
+    @Appender(_doc_template)
+    def is_monotonic_increasing(self):
+        """
+        Returns whether each group is monotonically increasing.
+
+        Equivalent to ``.apply(lambda x: x.is_monotonic_increasing)``.
+
+        Examples
+        --------
+        >>> source_dict = {
+        ...    'A': ['this', 'col', 'is', 'entirely', 'irrelevant', '.'],
+        ...    'B': ['cat_a', 'cat_a', 'cat_a', 'cat_b', 'cat_b', 'cat_b'],
+        ...    'C': [1, 2, 3, 2, 2, 0]}
+
+        >>> df = pd.DataFrame(source_dict)
+        ...    df.groupby(['B']).C.is_monotonic_increasing()
+        B
+        cat_a    True
+        cat_b    False
+        Name: C, dtype: bool
+
+        """
+        return self.apply(lambda x: x.is_monotonic_increasing)
+
+    @Substitution(name='groupby')
+    @Appender(_doc_template)
+    def is_monotonic_decreasing(self):
+        """
+        Returns whether each group is monotonically decreasing.
+
+        Equivalent to ``.apply(lambda x: x.is_monotonic_decreasing)``.
+
+        Examples
+        --------
+        >>> source_dict = {
+        ...    'A': ['this', 'col', 'is', 'entirely', 'irrelevant', '.'],
+        ...    'B': ['cat_a', 'cat_a', 'cat_a', 'cat_b', 'cat_b', 'cat_b'],
+        ...    'C': [1, 2, 3, 2, 2, 0]}
+
+        >>> df = pd.DataFrame(source_dict)
+        ...    df.groupby(['B']).C.is_monotonic_decreasing()
+        B
+        cat_a    False
+        cat_b    True
+        Name: C, dtype: bool
+        """
+        return self.apply(lambda x: x.is_monotonic_decreasing)
+
 
 GroupBy._add_numeric_operations()
 

pandas/tests/groupby/test_whitelist.py

@@ -239,17 +239,18 @@ def test_groupby_blacklist(df_letters):
 def test_tab_completion(mframe):
     grp = mframe.groupby(level='second')
     results = set([v for v in dir(grp) if not v.startswith('_')])
-    expected = {
-        'A', 'B', 'C', 'agg', 'aggregate', 'apply', 'boxplot', 'filter',
-        'first', 'get_group', 'groups', 'hist', 'indices', 'last', 'max',
-        'mean', 'median', 'min', 'ngroups', 'nth', 'ohlc', 'plot',
-        'prod', 'size', 'std', 'sum', 'transform', 'var', 'sem', 'count',
-        'nunique', 'head', 'describe', 'cummax', 'quantile',
-        'rank', 'cumprod', 'tail', 'resample', 'cummin', 'fillna',
-        'cumsum', 'cumcount', 'ngroup', 'all', 'shift', 'skew',
-        'take', 'tshift', 'pct_change', 'any', 'mad', 'corr', 'corrwith',
-        'cov', 'dtypes', 'ndim', 'diff', 'idxmax', 'idxmin',
-        'ffill', 'bfill', 'pad', 'backfill', 'rolling', 'expanding', 'pipe'}
+    expected = set(
+        ['A', 'B', 'C', 'agg', 'aggregate', 'apply', 'boxplot', 'filter',
+         'first', 'get_group', 'groups', 'hist', 'indices', 'last', 'max',
+         'mean', 'median', 'min', 'ngroups', 'nth', 'ohlc', 'plot',
+         'prod', 'size', 'std', 'sum', 'transform', 'var', 'sem', 'count',
+         'nunique', 'head', 'describe', 'cummax', 'quantile',
+         'rank', 'cumprod', 'tail', 'resample', 'cummin', 'fillna',
+         'cumsum', 'cumcount', 'ngroup', 'all', 'shift', 'skew',
+         'take', 'tshift', 'pct_change', 'any', 'mad', 'corr', 'corrwith',
+         'cov', 'dtypes', 'ndim', 'diff', 'idxmax', 'idxmin',
+         'ffill', 'bfill', 'pad', 'backfill', 'rolling', 'expanding', 'pipe',
+         'is_monotonic_increasing', 'is_monotonic_decreasing'])
     assert results == expected