wip

pandas/core/arrays/base.py

@@ -680,8 +680,8 @@ def __repr__(self):
                                length=len(self),
                                dtype=self.dtype)
 
-    def _formatter(self, boxed=False):
-        # type: (bool) -> Callable[Any]
+    def _formatter(self, formatter):
+        # type: (ExtensionArrayFormatter) -> Callable[Any]
         """Formatting function for scalar values.
 
         This is used in the default '__repr__'. The formatting function
@@ -693,7 +693,7 @@ def _formatter(self, boxed=False):
             Whether the formatter is to be used by pandas inside a Series
             or DataFrame repr.
         """
-        return str
+        return formatter.formatter or str
 
     def _formatting_values(self):
         # type: () -> np.ndarray

pandas/core/internals/blocks.py

@@ -1963,9 +1963,7 @@ def formatting_values(self):
             warnings.warn(msg, FutureWarning, stacklevel=10)
             return self.values._formatting_values()
 
-        # the future implementation (and current, if not overrode)
-        formatter = self.values._formatter(boxed=True)
-        return np.array([formatter(x) for x in self.values], dtype=object)
+        return self.values
 
     def concat_same_type(self, to_concat, placement=None):
         """

pandas/io/formats/format.py

@@ -16,11 +16,12 @@
 from pandas.compat import StringIO, lzip, map, u, zip
 
 from pandas.core.dtypes.common import (
-    is_categorical_dtype, is_datetime64_dtype, is_datetimetz, is_float,
-    is_float_dtype, is_integer, is_integer_dtype, is_interval_dtype,
-    is_list_like, is_numeric_dtype, is_period_arraylike, is_scalar,
-    is_timedelta64_dtype)
-from pandas.core.dtypes.generic import ABCMultiIndex, ABCSparseArray
+    is_categorical_dtype, is_datetime64_dtype, is_datetimetz,
+    is_extension_array_dtype, is_float, is_float_dtype, is_integer,
+    is_integer_dtype, is_list_like, is_numeric_dtype, is_period_arraylike,
+    is_scalar, is_timedelta64_dtype)
+from pandas.core.dtypes.generic import (
+    ABCIndex, ABCMultiIndex, ABCSeries, ABCSparseArray)
 from pandas.core.dtypes.missing import isna, notna
 
 from pandas import compat
@@ -849,22 +850,20 @@ def _get_column_name_list(self):
 def format_array(values, formatter, float_format=None, na_rep='NaN',
                  digits=None, space=None, justify='right', decimal='.'):
 
-    if is_categorical_dtype(values):
-        fmt_klass = CategoricalArrayFormatter
-    elif is_interval_dtype(values):
-        fmt_klass = IntervalArrayFormatter
+    if is_period_arraylike(values):
+        fmt_klass = PeriodArrayFormatter
+    elif is_datetime64_dtype(values.dtype):
+        fmt_klass = Datetime64Formatter
+    elif is_timedelta64_dtype(values.dtype):
+        fmt_klass = Timedelta64Formatter
+    elif is_extension_array_dtype(values.dtype):
+        fmt_klass = ExtensionArrayFormatter
     elif is_float_dtype(values.dtype):
         fmt_klass = FloatArrayFormatter
-    elif is_period_arraylike(values):
-        fmt_klass = PeriodArrayFormatter
     elif is_integer_dtype(values.dtype):
         fmt_klass = IntArrayFormatter
     elif is_datetimetz(values):
         fmt_klass = Datetime64TZFormatter
-    elif is_datetime64_dtype(values.dtype):
-        fmt_klass = Datetime64Formatter
-    elif is_timedelta64_dtype(values.dtype):
-        fmt_klass = Timedelta64Formatter
     else:
         fmt_klass = GenericArrayFormatter
 
@@ -1126,14 +1125,18 @@ def _format_strings(self):
         return fmt_values.tolist()
 
 
-class IntervalArrayFormatter(GenericArrayFormatter):
-
-    def __init__(self, values, *args, **kwargs):
-        GenericArrayFormatter.__init__(self, values, *args, **kwargs)
-
+class ExtensionArrayFormatter(GenericArrayFormatter):
     def _format_strings(self):
-        formatter = self.formatter or str
-        fmt_values = np.array([formatter(x) for x in self.values])
+        values = self.values
+        if isinstance(values, (ABCIndex, ABCSeries)):
+            values = values._values
+
+        formatter = self.values._formatter(self)
+        fmt_values = format_array(np.asarray(self.values),
+                                  formatter,
+                                  float_format=self.float_format,
+                                  na_rep=self.na_rep, digits=self.digits,
+                                  space=self.space, justify=self.justify)
         return fmt_values
 
 
@@ -1152,19 +1155,6 @@ def _format_strings(self):
         return fmt_values
 
 
-class CategoricalArrayFormatter(GenericArrayFormatter):
-
-    def __init__(self, values, *args, **kwargs):
-        GenericArrayFormatter.__init__(self, values, *args, **kwargs)
-
-    def _format_strings(self):
-        fmt_values = format_array(self.values.get_values(), self.formatter,
-                                  float_format=self.float_format,
-                                  na_rep=self.na_rep, digits=self.digits,
-                                  space=self.space, justify=self.justify)
-        return fmt_values
-
-
 def format_percentiles(percentiles):
     """
     Outputs rounded and formatted percentiles.

pandas/tests/arrays/test_period.py

@@ -215,14 +215,16 @@ def test_repr_large():
     arr = period_array(['2000', '2001'] * 500, freq='D')
     result = str(arr)
     expected = (
-        '<PeriodArray>\n'
-        '[2000-01-01, 2001-01-01, 2000-01-01, 2001-01-01, 2000-01-01, '
-        '2001-01-01,\n'  # continuation
-        ' 2000-01-01, 2001-01-01, 2000-01-01, 2001-01-01,\n'
-        ' ...\n'
-        ' 2000-01-01, 2001-01-01, 2000-01-01, 2001-01-01, 2000-01-01, '
-        '2001-01-01,\n'  # continuation
-        ' 2000-01-01, 2001-01-01, 2000-01-01, 2001-01-01]\n'
-        'Length: 1000, dtype: period[D]'
+        "<PeriodArray>\n"
+        "['2000-01-01', '2001-01-01', '2000-01-01', '2001-01-01', "
+        "'2000-01-01',\n"
+        " '2001-01-01', '2000-01-01', '2001-01-01', '2000-01-01', "
+        "'2001-01-01',\n"
+        " ...\n"
+        " '2000-01-01', '2001-01-01', '2000-01-01', '2001-01-01', "
+        "'2000-01-01',\n"
+        " '2001-01-01', '2000-01-01', '2001-01-01', '2000-01-01', "
+        "'2001-01-01']\n"
+        "Length: 1000, dtype: period[D]"
     )
     assert result == expected