BUG/API: info repr should honor display.max_info_columns

doc/source/release.rst

@@ -515,6 +515,7 @@ Bug Fixes
 - Bug in the HTML repr of a truncated Series or DataFrame not showing the class name with the `large_repr` set to 'info'
   (:issue:`7105`)
 - Bug in ``DatetimeIndex`` specifying ``freq`` raises ``ValueError`` when passed value is too short (:issue:`7098`)
+- Fixed a bug with the `info` repr not honoring the `display.max_info_columns` setting (:issue:`6939`)
 
 pandas 0.13.1
 -------------

doc/source/v0.14.0.txt

@@ -210,6 +210,7 @@ API changes
      # this now raises for arith ops like ``+``, ``*``, etc.
      NotImplementedError: operator '*' not implemented for bool dtypes
 
+
 .. _whatsnew_0140.display:
 
 Display Changes
@@ -239,6 +240,11 @@ Display Changes
   length of the series (:issue:`7101`)
 - Fixed a bug in the HTML repr of a truncated Series or DataFrame not showing the class name with the
   `large_repr` set to 'info' (:issue:`7105`)
+- The `verbose` keyword in ``DataFrame.info()``, which controls whether to shorten the ``info``
+  representation, is now ``None`` by default. This will follow the global setting in
+  ``display.max_info_columns``. The global setting can be overriden with ``verbose=True`` or
+  ``verbose=False``.
+- Fixed a bug with the `info` repr not honoring the `display.max_info_columns` setting (:issue:`6939`)
 
 .. _whatsnew_0140.groupby:
 

pandas/core/frame.py

@@ -1392,17 +1392,20 @@ def to_latex(self, buf=None, columns=None, col_space=None, colSpace=None,
         if buf is None:
             return formatter.buf.getvalue()
 
-    def info(self, verbose=True, buf=None, max_cols=None):
+    def info(self, verbose=None, buf=None, max_cols=None):
         """
         Concise summary of a DataFrame.
 
         Parameters
         ----------
-        verbose : boolean, default True
-            If False, don't print column count summary
+        verbose : {None, True, False}, optional
+            Whether to print the full summary.
+            None follows the `display.max_info_columns` setting.
+            True or False overrides the `display.max_info_columns` setting.
         buf : writable buffer, defaults to sys.stdout
         max_cols : int, default None
-            Determines whether full summary or short summary is printed
+            Determines whether full summary or short summary is printed.
+            None follows the `display.max_info_columns` setting.
         """
         from pandas.core.format import _put_lines
 
@@ -1429,8 +1432,10 @@ def info(self, verbose=True, buf=None, max_cols=None):
         max_rows = get_option('display.max_info_rows', len(self) + 1)
 
         show_counts = ((len(self.columns) <= max_cols) and
-                         (len(self) < max_rows))
-        if verbose:
+                       (len(self) < max_rows))
+        exceeds_info_cols = len(self.columns) > max_cols
+
+        def _verbose_repr():
             lines.append('Data columns (total %d columns):' %
                          len(self.columns))
             space = max([len(com.pprint_thing(k)) for k in self.columns]) + 4
@@ -1442,22 +1447,33 @@ def info(self, verbose=True, buf=None, max_cols=None):
                 if len(cols) != len(counts):  # pragma: no cover
                     raise AssertionError('Columns must equal counts (%d != %d)' %
                                          (len(cols), len(counts)))
-                tmpl =  "%s non-null %s"
+                tmpl = "%s non-null %s"
 
             dtypes = self.dtypes
             for i, col in enumerate(self.columns):
                 dtype = dtypes[col]
                 col = com.pprint_thing(col)
 
-                count= ""
+                count = ""
                 if show_counts:
                     count = counts.iloc[i]
 
                 lines.append(_put_str(col, space) +
                              tmpl % (count, dtype))
-        else:
+
+        def _non_verbose_repr():
             lines.append(self.columns.summary(name='Columns'))
 
+        if verbose:
+            _verbose_repr()
+        elif verbose is False:  # specifically set to False, not nesc None
+            _non_verbose_repr()
+        else:
+            if exceeds_info_cols:
+                _non_verbose_repr()
+            else:
+                _verbose_repr()
+
         counts = self.get_dtype_counts()
         dtypes = ['%s(%d)' % k for k in sorted(compat.iteritems(counts))]
         lines.append('dtypes: %s' % ', '.join(dtypes))

pandas/tests/test_format.py

@@ -38,6 +38,12 @@ def has_info_repr(df):
     c2 = r.split('\n')[0].startswith(r"<class")  # _repr_html_
     return c1 or c2
 
+def has_non_verbose_info_repr(df):
+    has_info = has_info_repr(df)
+    r = repr(df)
+    nv = len(r.split('\n')) == 4  # 1. <class>, 2. Index, 3. Columns, 4. dtype
+    return has_info and nv
+
 def has_horizontally_truncated_repr(df):
     r = repr(df)
     return any(l.strip().endswith('...') for l in r.splitlines())
@@ -1573,6 +1579,22 @@ def test_info_repr(self):
         with option_context('display.large_repr', 'info'):
             assert has_info_repr(df)
 
+    def test_info_repr_max_cols(self):
+        # GH #6939
+        df = DataFrame(randn(10, 5))
+        with option_context('display.large_repr', 'info',
+                            'display.max_columns', 1,
+                            'display.max_info_columns', 4):
+            self.assertTrue(has_non_verbose_info_repr(df))
+
+        with option_context('display.large_repr', 'info',
+                            'display.max_columns', 1,
+                            'display.max_info_columns', 5):
+            self.assertFalse(has_non_verbose_info_repr(df))
+
+        # test verbose overrides
+        # fmt.set_option('display.max_info_columns', 4)  # exceeded
+
     def test_info_repr_html(self):
         max_rows = get_option('display.max_rows')
         max_cols = get_option('display.max_columns')

pandas/tests/test_frame.py

@@ -6326,6 +6326,41 @@ def test_info_shows_column_dtypes(self):
             name = '%d    %d non-null %s' % (i, n, dtype)
             assert name in res
 
+    def test_info_max_cols(self):
+        df = DataFrame(np.random.randn(10, 5))
+        for len_, verbose in [(4, None), (4, False), (9, True)]:
+        # For verbose always      ^ setting  ^ summarize ^ full output
+            with pd.option_context('max_info_columns', 4):
+                buf = StringIO()
+                df.info(buf=buf, verbose=verbose)
+                res = buf.getvalue()
+                self.assertEqual(len(res.split('\n')), len_)
+
+        for len_, verbose in [(9, None), (4, False), (9, True)]:
+
+            # max_cols no exceeded
+            with pd.option_context('max_info_columns', 5):
+                buf = StringIO()
+                df.info(buf=buf, verbose=verbose)
+                res = buf.getvalue()
+                self.assertEqual(len(res.split('\n')), len_)
+
+        for len_, max_cols in [(9, 5), (4, 4)]:
+            # setting truncates
+            with pd.option_context('max_info_columns', 4):
+                buf = StringIO()
+                df.info(buf=buf, max_cols=max_cols)
+                res = buf.getvalue()
+                self.assertEqual(len(res.split('\n')), len_)
+
+            # setting wouldn't truncate
+            with pd.option_context('max_info_columns', 5):
+                buf = StringIO()
+                df.info(buf=buf, max_cols=max_cols)
+                res = buf.getvalue()
+                self.assertEqual(len(res.split('\n')), len_)
+
+
     def test_dtypes(self):
         self.mixed_frame['bool'] = self.mixed_frame['A'] > 0
         result = self.mixed_frame.dtypes