.describe() for series of objects

pandas/core/frame.py

@@ -2497,7 +2497,7 @@ def min(self, axis=0, skipna=True):
         min : Series
         """
         values = self.values.copy()
-        if skipna:
+        if skipna and not issubclass(values.dtype.type, np.int_):
             np.putmask(values, -np.isfinite(values), np.inf)
         return Series(values.min(axis), index=self._get_agg_axis(axis))
 
@@ -2518,7 +2518,7 @@ def max(self, axis=0, skipna=True):
         max : Series
         """
         values = self.values.copy()
-        if skipna:
+        if skipna and not issubclass(values.dtype.type, np.int_):
             np.putmask(values, -np.isfinite(values), -np.inf)
         return Series(values.max(axis), index=self._get_agg_axis(axis))
 

pandas/core/series.py

@@ -5,6 +5,7 @@
 # pylint: disable=E1101,E1103
 # pylint: disable=W0703,W0622,W0613,W0201
 
+import collections
 import csv
 import itertools
 import operator
@@ -873,12 +874,20 @@ def describe(self):
         -------
         desc : Series
         """
-        names = ['count', 'mean', 'std', 'min',
-                 '25%', '50%', '75%', 'max']
-
-        data = [self.count(), self.mean(), self.std(), self.min(),
-                self.quantile(.25), self.median(), self.quantile(.75),
-                self.max()]
+        if self.dtype == object:
+            names = ['count', 'unique', 'top', 'freq']
+
+            objcounts = collections.Counter(self)
+            top, freq = objcounts.most_common(1)[0]
+            data = [self.count(), len(objcounts), top, freq]
+
+        else:    
+            names = ['count', 'mean', 'std', 'min',
+                     '25%', '50%', '75%', 'max']
+
+            data = [self.count(), self.mean(), self.std(), self.min(),
+                    self.quantile(.25), self.median(), self.quantile(.75),
+                    self.max()]
 
         return Series(data, index=names)
 

pandas/tests/test_frame.py

@@ -2721,9 +2721,11 @@ def wrapper(x):
 
     def test_min(self):
         self._check_stat_op('min', np.min)
+        self._check_stat_op('min', np.min, frame=self.intframe)
 
     def test_max(self):
         self._check_stat_op('max', np.max)
+        self._check_stat_op('max', np.max, frame=self.intframe)
 
     def test_mad(self):
         f = lambda x: np.abs(x - x.mean()).mean()

pandas/tests/test_series.py

@@ -550,6 +550,7 @@ def test_quantile(self):
     def test_describe(self):
         _ = self.series.describe()
         _ = self.ts.describe()
+        _ = self.objSeries.describe()
 
     def test_append(self):
         appendedSeries = self.series.append(self.ts)