TST: Test to_native_types for Period/DatetimeIndex

Author: gfyoung

pandas/indexes/base.py

@@ -1820,7 +1820,26 @@ def _format_with_header(self, header, na_rep='NaN', **kwargs):
         return header + result
 
     def to_native_types(self, slicer=None, **kwargs):
-        """ slice and dice then format """
+        """
+        Format specified values of `self` and return them.
+
+        Parameters
+        ----------
+        slicer : int, array-like
+            An indexer into `self` that specifies which values
+            are used in the formatting process.
+        kwargs : dict
+            Options for specifying how the values should be formatted.
+            These options include the following:
+
+            1) na_rep : str
+                The value that serves as a placeholder for NULL values
+            2) quoting : bool or None
+                Whether or not there are quoted values in `self`
+            3) date_format : str
+                The format used to represent date-like values
+        """
+
         values = self
         if slicer is not None:
             values = values[slicer]

pandas/tests/indexes/datetimes/test_formats.py

@@ -0,0 +1,47 @@
+from pandas import DatetimeIndex
+
+import numpy as np
+
+import pandas.util.testing as tm
+import pandas as pd
+
+
+def test_to_native_types():
+    index = DatetimeIndex(freq='1D', periods=3, start='2017-01-01')
+
+    # First, with no arguments.
+    expected = np.array(['2017-01-01', '2017-01-02',
+                         '2017-01-03'], dtype=object)
+
+    result = index.to_native_types()
+    tm.assert_numpy_array_equal(result, expected)
+
+    # No NaN values, so na_rep has no effect
+    result = index.to_native_types(na_rep='pandas')
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure slicing works
+    expected = np.array(['2017-01-01', '2017-01-03'], dtype=object)
+
+    result = index.to_native_types([0, 2])
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure date formatting works
+    expected = np.array(['01-2017-01', '01-2017-02',
+                         '01-2017-03'], dtype=object)
+
+    result = index.to_native_types(date_format='%m-%Y-%d')
+    tm.assert_numpy_array_equal(result, expected)
+
+    # NULL object handling should work
+    index = DatetimeIndex(['2017-01-01', pd.NaT, '2017-01-03'])
+    expected = np.array(['2017-01-01', 'NaT', '2017-01-03'], dtype=object)
+
+    result = index.to_native_types()
+    tm.assert_numpy_array_equal(result, expected)
+
+    expected = np.array(['2017-01-01', 'pandas',
+                         '2017-01-03'], dtype=object)
+
+    result = index.to_native_types(na_rep='pandas')
+    tm.assert_numpy_array_equal(result, expected)

pandas/tests/indexes/period/test_formats.py

@@ -0,0 +1,48 @@
+from pandas import PeriodIndex
+
+import numpy as np
+
+import pandas.util.testing as tm
+import pandas as pd
+
+
+def test_to_native_types():
+    index = PeriodIndex(['2017-01-01', '2017-01-02',
+                         '2017-01-03'], freq='D')
+
+    # First, with no arguments.
+    expected = np.array(['2017-01-01', '2017-01-02',
+                         '2017-01-03'], dtype='<U10')
+
+    result = index.to_native_types()
+    tm.assert_numpy_array_equal(result, expected)
+
+    # No NaN values, so na_rep has no effect
+    result = index.to_native_types(na_rep='pandas')
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure slicing works
+    expected = np.array(['2017-01-01', '2017-01-03'], dtype='<U10')
+
+    result = index.to_native_types([0, 2])
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure date formatting works
+    expected = np.array(['01-2017-01', '01-2017-02',
+                         '01-2017-03'], dtype='<U10')
+
+    result = index.to_native_types(date_format='%m-%Y-%d')
+    tm.assert_numpy_array_equal(result, expected)
+
+    # NULL object handling should work
+    index = PeriodIndex(['2017-01-01', pd.NaT, '2017-01-03'], freq='D')
+    expected = np.array(['2017-01-01', 'NaT', '2017-01-03'], dtype=object)
+
+    result = index.to_native_types()
+    tm.assert_numpy_array_equal(result, expected)
+
+    expected = np.array(['2017-01-01', 'pandas',
+                         '2017-01-03'], dtype=object)
+
+    result = index.to_native_types(na_rep='pandas')
+    tm.assert_numpy_array_equal(result, expected)