Merge pull request #5983 from jreback/panel_dtypes

API: Panel.dtypes to use generic method; add tests for Panel4D for same

Author: jreback

doc/source/api.rst

@@ -249,8 +249,7 @@ Attributes and underlying data
 
    Series.values
    Series.dtype
-   Series.isnull
-   Series.notnull
+   Series.ftype
 
 Conversion
 ~~~~~~~~~~
@@ -519,7 +518,9 @@ Attributes and underlying data
 
    DataFrame.as_matrix
    DataFrame.dtypes
+   DataFrame.ftypes
    DataFrame.get_dtype_counts
+   DataFrame.get_ftype_counts
    DataFrame.values
    DataFrame.axes
    DataFrame.ndim
@@ -786,6 +787,9 @@ Attributes and underlying data
    Panel.ndim
    Panel.shape
    Panel.dtypes
+   Panel.ftypes
+   Panel.get_dtype_counts
+   Panel.get_ftype_counts
 
 Conversion
 ~~~~~~~~~~
@@ -959,6 +963,49 @@ Serialization / IO / Conversion
    Panel.to_frame
    Panel.to_clipboard
 
+.. _api.panel4d:
+
+Panel4D
+-------
+
+Constructor
+~~~~~~~~~~~
+.. autosummary::
+   :toctree: generated/
+
+   Panel4D
+
+Attributes and underlying data
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+**Axes**
+
+  * **labels**: axis 1; each label corresponds to a Panel contained inside
+  * **items**: axis 2; each item corresponds to a DataFrame contained inside
+  * **major_axis**: axis 3; the index (rows) of each of the DataFrames
+  * **minor_axis**: axis 4; the columns of each of the DataFrames
+
+.. autosummary::
+   :toctree: generated/
+
+   Panel4D.values
+   Panel4D.axes
+   Panel4D.ndim
+   Panel4D.shape
+   Panel4D.dtypes
+   Panel4D.ftypes
+   Panel4D.get_dtype_counts
+   Panel4D.get_ftype_counts
+
+Conversion
+~~~~~~~~~~
+.. autosummary::
+   :toctree: generated/
+
+   Panel4D.astype
+   Panel4D.copy
+   Panel4D.isnull
+   Panel4D.notnull
+
 .. _api.index:
 
 Index

doc/source/release.rst

@@ -75,7 +75,7 @@ Improvements to existing features
   - df.info() now honors option max_info_rows, disable null counts for large frames (:issue:`5974`)
   - perf improvements in DataFrame ``count/dropna`` for ``axis=1``
   - Series.str.contains now has a `regex=False` keyword which can be faster for plain (non-regex) string patterns. (:issue:`5879`)
-  - support ``dtypes`` on ``Panel``
+  - support ``dtypes`` property on ``Series/Panel/Panel4D``
   - extend ``Panel.apply`` to allow arbitrary functions (rather than only ufuncs) (:issue:`1148`)
     allow multiple axes to be used to operate on slabs of a ``Panel``
   - The ``ArrayFormatter``s for ``datetime`` and ``timedelta64`` now intelligently

pandas/core/internals.py

@@ -3514,6 +3514,9 @@ def _post_setstate(self):
         self._block = self.blocks[0]
         self._values = self._block.values
 
+    def _get_counts(self, f):
+        return { f(self._block) : 1 }
+
     @property
     def shape(self):
         if getattr(self, '_shape', None) is None:

pandas/core/panel.py

@@ -441,10 +441,6 @@ def as_matrix(self):
         self._consolidate_inplace()
         return self._data.as_matrix()
 
-    @property
-    def dtypes(self):
-        return self.apply(lambda x: x.dtype, axis='items')
-
     #----------------------------------------------------------------------
     # Getting and setting elements
 

pandas/core/series.py

@@ -301,10 +301,20 @@ def flags(self):
     def dtype(self):
         return self._data.dtype
 
+    @property
+    def dtypes(self):
+        """ for compat """
+        return self._data.dtype
+
     @property
     def ftype(self):
         return self._data.ftype
 
+    @property
+    def ftypes(self):
+        """ for compat """
+        return self._data.ftype
+
     @property
     def shape(self):
         return self._data.shape
@@ -2094,7 +2104,7 @@ def isin(self, values):
         ----------
         values : list-like
             The sequence of values to test. Passing in a single string will
-            raise a ``TypeError``. Instead, turn a single string into a 
+            raise a ``TypeError``. Instead, turn a single string into a
             ``list`` of one element.
 
         Returns

pandas/tests/test_panel.py

@@ -6,7 +6,7 @@
 
 import numpy as np
 
-from pandas import DataFrame, Index, isnull, notnull, pivot, MultiIndex
+from pandas import Series, DataFrame, Index, isnull, notnull, pivot, MultiIndex
 from pandas.core.datetools import bday
 from pandas.core.frame import group_agg
 from pandas.core.panel import Panel
@@ -1064,8 +1064,8 @@ def test_convert_objects(self):
     def test_dtypes(self):
 
         result = self.panel.dtypes
-        expected = DataFrame(np.dtype('float64'),index=self.panel.major_axis,columns=self.panel.minor_axis)
-        assert_frame_equal(result, expected)
+        expected = Series(np.dtype('float64'),index=self.panel.items)
+        assert_series_equal(result, expected)
 
     def test_apply(self):
         # GH1148

pandas/tests/test_panel4d.py

@@ -6,7 +6,7 @@
 
 import numpy as np
 
-from pandas import DataFrame, Index, isnull, notnull, pivot, MultiIndex
+from pandas import Series, DataFrame, Index, isnull, notnull, pivot, MultiIndex
 from pandas.core.datetools import bday
 from pandas.core.frame import group_agg
 from pandas.core.panel import Panel
@@ -932,6 +932,12 @@ def test_filter(self):
     def test_apply(self):
         raise nose.SkipTest("skipping for now")
 
+    def test_dtypes(self):
+
+        result = self.panel4d.dtypes
+        expected = Series(np.dtype('float64'),index=self.panel4d.labels)
+        assert_series_equal(result, expected)
+
     def test_compound(self):
         raise nose.SkipTest("skipping for now")
     #    compounded = self.panel.compound()

pandas/tests/test_series.py

@@ -3620,6 +3620,15 @@ def test_count(self):
 
         self.assertEqual(self.ts.count(), np.isfinite(self.ts).sum())
 
+    def test_dtype(self):
+
+        self.assert_(self.ts.dtype == np.dtype('float64'))
+        self.assert_(self.ts.dtypes == np.dtype('float64'))
+        self.assert_(self.ts.ftype == 'float64:dense')
+        self.assert_(self.ts.ftypes == 'float64:dense')
+        assert_series_equal(self.ts.get_dtype_counts(),Series(1,['float64']))
+        assert_series_equal(self.ts.get_ftype_counts(),Series(1,['float64:dense']))
+
     def test_dot(self):
         a = Series(np.random.randn(4), index=['p', 'q', 'r', 's'])
         b = DataFrame(np.random.randn(3, 4), index=['1', '2', '3'],