Set pd.options.display.max_columns=0 by default

doc/source/options.rst

@@ -78,8 +78,8 @@ with no argument ``describe_option`` will print out the descriptions for all ava
 Getting and Setting Options
 ---------------------------
 
-As described above, :func:`~pandas.get_option` and :func:`~pandas.set_option` 
-are available from the pandas namespace.  To change an option, call 
+As described above, :func:`~pandas.get_option` and :func:`~pandas.set_option`
+are available from the pandas namespace.  To change an option, call
 ``set_option('option regex', new_value)``.
 
 .. ipython:: python
@@ -230,7 +230,7 @@ can specify the option ``df.info(null_counts=True)`` to override on showing a pa
    df.info()
    pd.reset_option('max_info_rows')
 
-``display.precision`` sets the output display precision in terms of decimal places. 
+``display.precision`` sets the output display precision in terms of decimal places.
 This is only a suggestion.
 
 .. ipython:: python
@@ -323,21 +323,21 @@ display.latex.multicolumn_format        'l'          Alignment of multicolumn la
 display.latex.multirow                  False        Combines rows when using a MultiIndex.
                                                      Centered instead of top-aligned,
                                                      separated by clines.
-display.max_columns                     20           max_rows and max_columns are used
+display.max_columns                     0 or 20      max_rows and max_columns are used
                                                      in __repr__() methods to decide if
                                                      to_string() or info() is used to
                                                      render an object to a string.  In
-                                                     case python/IPython is running in
-                                                     a terminal this can be set to 0 and
+                                                     case Python/IPython is running in
+                                                     a terminal this is set to 0 by default and
                                                      pandas will correctly auto-detect
-                                                     the width the terminal and swap to
+                                                     the width of the terminal and switch to
                                                      a smaller format in case all columns
                                                      would not fit vertically. The IPython
                                                      notebook, IPython qtconsole, or IDLE
                                                      do not run in a terminal and hence
                                                      it is not possible to do correct
-                                                     auto-detection. 'None' value means
-                                                     unlimited.
+                                                     auto-detection, in which case the default
+                                                     is set to 20. 'None' value means unlimited.
 display.max_colwidth                    50           The maximum width in characters of
                                                      a column in the repr of a pandas
                                                      data structure. When the column overflows,
@@ -402,9 +402,9 @@ display.html.table_schema               False        Whether to publish a Table
 display.html.border                     1            A ``border=value`` attribute is
                                                      inserted in the ``<table>`` tag
                                                      for the DataFrame HTML repr.
-display.html.use_mathjax                True         When True, Jupyter notebook will process 
-                                                     table contents using MathJax, rendering 
-                                                     mathematical expressions enclosed by the 
+display.html.use_mathjax                True         When True, Jupyter notebook will process
+                                                     table contents using MathJax, rendering
+                                                     mathematical expressions enclosed by the
                                                      dollar symbol.
 io.excel.xls.writer                     xlwt         The default Excel writer engine for
                                                      'xls' files.
@@ -422,7 +422,7 @@ io.hdf.dropna_table                     True         drop ALL nan rows when appe
 io.parquet.engine                       None         The engine to use as a default for
                                                      parquet reading and writing. If None
                                                      then try 'pyarrow' and 'fastparquet'
-mode.chained_assignment                 warn         Controls ``SettingWithCopyWarning``: 
+mode.chained_assignment                 warn         Controls ``SettingWithCopyWarning``:
                                                      'raise', 'warn', or None. Raise an
                                                      exception, warn, or no action if
                                                      trying to use :ref:`chained assignment <indexing.evaluation_order>`.

doc/source/whatsnew/v0.23.0.txt

@@ -658,6 +658,35 @@ Notice in the example above that the converted ``Categorical`` has retained ``or
 
 Note that the unintenional conversion of ``ordered`` discussed above did not arise in previous versions due to separate bugs that prevented ``astype`` from doing any type of category to category conversion (:issue:`10696`, :issue:`18593`).  These bugs have been fixed in this release, and motivated changing the default value of ``ordered``.
 
+.. _whatsnew_0230.api_breaking.pretty_printing:
+
+Better pretty-printing of DataFrames in a terminal
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Previously, the default value for the maximum number of columns was
+``pd.options.display.max_columns=20``. This meant that relatively wide data
+frames would not fit within the terminal width, and pandas would introduce line
+breaks to display these 20 columns. This resulted in an output that was
+relatively difficult to read:
+
+.. image:: _static/print_df_old.png
+
+If Python runs in a terminal, the maximum number of columns is now determined
+automatically so that the printed data frame fits within the current terminal
+width (``pd.options.display.max_columns=0``) (:issue:`17023`). If Python runs
+as a Jupyter kernel (such as the Jupyter QtConsole or a Jupyter notebook, as
+well as in many IDEs), this value cannot be inferred automatically and is thus
+set to `20` as in previous versions. In a terminal, this results in a much
+nicer output:
+
+.. image:: _static/print_df_new.png
+
+Note that if you don't like the new default, you can always set this option
+yourself. To revert to the old setting, you can run this line:
+
+.. code-block:: python
+
+  pd.options.display.max_columns = 20
+
 .. _whatsnew_0230.api.datetimelike:
 
 Datetimelike API Changes

pandas/core/config_init.py

@@ -13,6 +13,7 @@
 from pandas.core.config import (is_int, is_bool, is_text, is_instance_factory,
                                 is_one_of_factory, is_callable)
 from pandas.io.formats.console import detect_console_encoding
+from pandas.io.formats.terminal import is_terminal
 
 # compute
 
@@ -314,7 +315,11 @@ def table_schema_cb(key):
     cf.register_option('max_categories', 8, pc_max_categories_doc,
                        validator=is_int)
     cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int)
-    cf.register_option('max_columns', 20, pc_max_cols_doc,
+    if is_terminal():
+        max_cols = 0  # automatically determine optimal number of columns
+    else:
+        max_cols = 20  # cannot determine optimal number of columns
+    cf.register_option('max_columns', max_cols, pc_max_cols_doc,
                        validator=is_instance_factory([type(None), int]))
     cf.register_option('large_repr', 'truncate', pc_large_repr_doc,
                        validator=is_one_of_factory(['truncate', 'info']))

pandas/io/formats/format.py

@@ -625,7 +625,8 @@ def to_string(self):
                 max_len += size_tr_col  # Need to make space for largest row
                 # plus truncate dot col
                 dif = max_len - self.w
-                adj_dif = dif
+                # '+ 1' to avoid too wide repr (GH PR #17023)
+                adj_dif = dif + 1
                 col_lens = Series([Series(ele).apply(len).max()
                                    for ele in strcols])
                 n_cols = len(col_lens)

pandas/io/formats/terminal.py

@@ -17,7 +17,7 @@
 import sys
 import shutil
 
-__all__ = ['get_terminal_size']
+__all__ = ['get_terminal_size', 'is_terminal']
 
 
 def get_terminal_size():
@@ -48,6 +48,23 @@ def get_terminal_size():
     return tuple_xy
 
 
+def is_terminal():
+    """
+    Detect if Python is running in a terminal.
+
+    Returns True if Python is running in a terminal or False if not.
+    """
+    try:
+        ip = get_ipython()
+    except NameError:  # assume standard Python interpreter in a terminal
+        return True
+    else:
+        if hasattr(ip, 'kernel'):  # IPython as a Jupyter kernel
+            return False
+        else:  # IPython in a terminal
+            return True
+
+
 def _get_terminal_size_windows():
     res = None
     try:

pandas/tests/frame/test_dtypes.py

@@ -875,10 +875,11 @@ def test_astype_str(self):
                              columns=self.tzframe.columns)
         tm.assert_frame_equal(result, expected)
 
-        result = str(self.tzframe)
-        assert ('0 2013-01-01 2013-01-01 00:00:00-05:00 '
-                '2013-01-01 00:00:00+01:00') in result
-        assert ('1 2013-01-02                       '
-                'NaT                       NaT') in result
-        assert ('2 2013-01-03 2013-01-03 00:00:00-05:00 '
-                '2013-01-03 00:00:00+01:00') in result
+        with option_context('display.max_columns', 20):
+            result = str(self.tzframe)
+            assert ('0 2013-01-01 2013-01-01 00:00:00-05:00 '
+                    '2013-01-01 00:00:00+01:00') in result
+            assert ('1 2013-01-02                       '
+                    'NaT                       NaT') in result
+            assert ('2 2013-01-03 2013-01-03 00:00:00-05:00 '
+                    '2013-01-03 00:00:00+01:00') in result

pandas/tests/frame/test_repr_info.py

@@ -172,8 +172,8 @@ def test_repr_column_name_unicode_truncation_bug(self):
                                       'the CSV file externally. I want to Call'
                                       ' the File through the code..')})
 
-        result = repr(df)
-        assert 'StringCol' in result
+        with option_context('display.max_columns', 20):
+            assert 'StringCol' in repr(df)
 
     def test_latex_repr(self):
         result = r"""\begin{tabular}{llll}

pandas/tests/io/formats/test_format.py

@@ -961,7 +961,8 @@ def test_pprint_thing(self):
 
     def test_wide_repr(self):
         with option_context('mode.sim_interactive', True,
-                            'display.show_dimensions', True):
+                            'display.show_dimensions', True,
+                            'display.max_columns', 20):
             max_cols = get_option('display.max_columns')
             df = DataFrame(tm.rands_array(25, size=(10, max_cols - 1)))
             set_option('display.expand_frame_repr', False)
@@ -979,15 +980,17 @@ def test_wide_repr(self):
         reset_option('display.expand_frame_repr')
 
     def test_wide_repr_wide_columns(self):
-        with option_context('mode.sim_interactive', True):
+        with option_context('mode.sim_interactive', True,
+                            'display.max_columns', 20):
             df = DataFrame(np.random.randn(5, 3),
                            columns=['a' * 90, 'b' * 90, 'c' * 90])
             rep_str = repr(df)
 
             assert len(rep_str.splitlines()) == 20
 
     def test_wide_repr_named(self):
-        with option_context('mode.sim_interactive', True):
+        with option_context('mode.sim_interactive', True,
+                            'display.max_columns', 20):
             max_cols = get_option('display.max_columns')
             df = DataFrame(tm.rands_array(25, size=(10, max_cols - 1)))
             df.index.name = 'DataFrame Index'
@@ -1008,7 +1011,8 @@ def test_wide_repr_named(self):
         reset_option('display.expand_frame_repr')
 
     def test_wide_repr_multiindex(self):
-        with option_context('mode.sim_interactive', True):
+        with option_context('mode.sim_interactive', True,
+                            'display.max_columns', 20):
             midx = MultiIndex.from_arrays(tm.rands_array(5, size=(2, 10)))
             max_cols = get_option('display.max_columns')
             df = DataFrame(tm.rands_array(25, size=(10, max_cols - 1)),
@@ -1030,7 +1034,8 @@ def test_wide_repr_multiindex(self):
         reset_option('display.expand_frame_repr')
 
     def test_wide_repr_multiindex_cols(self):
-        with option_context('mode.sim_interactive', True):
+        with option_context('mode.sim_interactive', True,
+                            'display.max_columns', 20):
             max_cols = get_option('display.max_columns')
             midx = MultiIndex.from_arrays(tm.rands_array(5, size=(2, 10)))
             mcols = MultiIndex.from_arrays(
@@ -1044,15 +1049,16 @@ def test_wide_repr_multiindex_cols(self):
             wide_repr = repr(df)
             assert rep_str != wide_repr
 
-        with option_context('display.width', 150):
+        with option_context('display.width', 150, 'display.max_columns', 20):
             wider_repr = repr(df)
             assert len(wider_repr) < len(wide_repr)
 
         reset_option('display.expand_frame_repr')
 
     def test_wide_repr_unicode(self):
-        with option_context('mode.sim_interactive', True):
-            max_cols = get_option('display.max_columns')
+        with option_context('mode.sim_interactive', True,
+                            'display.max_columns', 20):
+            max_cols = 20
             df = DataFrame(tm.rands_array(25, size=(10, max_cols - 1)))
             set_option('display.expand_frame_repr', False)
             rep_str = repr(df)
@@ -1442,17 +1448,17 @@ def test_repr_html_mathjax(self):
             assert 'tex2jax_ignore' in df._repr_html_()
 
     def test_repr_html_wide(self):
-        max_cols = get_option('display.max_columns')
+        max_cols = 20
         df = DataFrame(tm.rands_array(25, size=(10, max_cols - 1)))
-        reg_repr = df._repr_html_()
-        assert "..." not in reg_repr
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            assert "..." not in df._repr_html_()
 
         wide_df = DataFrame(tm.rands_array(25, size=(10, max_cols + 1)))
-        wide_repr = wide_df._repr_html_()
-        assert "..." in wide_repr
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            assert "..." in wide_df._repr_html_()
 
     def test_repr_html_wide_multiindex_cols(self):
-        max_cols = get_option('display.max_columns')
+        max_cols = 20
 
         mcols = MultiIndex.from_product([np.arange(max_cols // 2),
                                          ['foo', 'bar']],
@@ -1467,8 +1473,8 @@ def test_repr_html_wide_multiindex_cols(self):
                                         names=['first', 'second'])
         df = DataFrame(tm.rands_array(25, size=(10, len(mcols))),
                        columns=mcols)
-        wide_repr = df._repr_html_()
-        assert '...' in wide_repr
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            assert '...' in df._repr_html_()
 
     def test_repr_html_long(self):
         with option_context('display.max_rows', 60):
@@ -1512,14 +1518,15 @@ def test_repr_html_float(self):
             assert u('2 columns') in long_repr
 
     def test_repr_html_long_multiindex(self):
-        max_rows = get_option('display.max_rows')
+        max_rows = 60
         max_L1 = max_rows // 2
 
         tuples = list(itertools.product(np.arange(max_L1), ['foo', 'bar']))
         idx = MultiIndex.from_tuples(tuples, names=['first', 'second'])
         df = DataFrame(np.random.randn(max_L1 * 2, 2), index=idx,
                        columns=['A', 'B'])
-        reg_repr = df._repr_html_()
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            reg_repr = df._repr_html_()
         assert '...' not in reg_repr
 
         tuples = list(itertools.product(np.arange(max_L1 + 1), ['foo', 'bar']))
@@ -1530,20 +1537,22 @@ def test_repr_html_long_multiindex(self):
         assert '...' in long_repr
 
     def test_repr_html_long_and_wide(self):
-        max_cols = get_option('display.max_columns')
-        max_rows = get_option('display.max_rows')
+        max_cols = 20
+        max_rows = 60
 
         h, w = max_rows - 1, max_cols - 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
-        assert '...' not in df._repr_html_()
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            assert '...' not in df._repr_html_()
 
         h, w = max_rows + 1, max_cols + 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
-        assert '...' in df._repr_html_()
+        with option_context('display.max_rows', 60, 'display.max_columns', 20):
+            assert '...' in df._repr_html_()
 
     def test_info_repr(self):
-        max_rows = get_option('display.max_rows')
-        max_cols = get_option('display.max_columns')
+        max_rows = 60
+        max_cols = 20
         # Long
         h, w = max_rows + 1, max_cols - 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
@@ -1555,7 +1564,8 @@ def test_info_repr(self):
         h, w = max_rows - 1, max_cols + 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
         assert has_horizontally_truncated_repr(df)
-        with option_context('display.large_repr', 'info'):
+        with option_context('display.large_repr', 'info',
+                            'display.max_columns', max_cols):
             assert has_info_repr(df)
 
     def test_info_repr_max_cols(self):
@@ -1575,8 +1585,8 @@ def test_info_repr_max_cols(self):
         # 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')
+        max_rows = 60
+        max_cols = 20
         # Long
         h, w = max_rows + 1, max_cols - 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
@@ -1588,7 +1598,8 @@ def test_info_repr_html(self):
         h, w = max_rows - 1, max_cols + 1
         df = DataFrame({k: np.arange(1, 1 + h) for k in np.arange(w)})
         assert '<class' not in df._repr_html_()
-        with option_context('display.large_repr', 'info'):
+        with option_context('display.large_repr', 'info',
+                            'display.max_columns', max_cols):
             assert '&lt;class' in df._repr_html_()
 
     def test_fake_qtconsole_repr_html(self):