.. _options:

.. currentmodule:: pandas

.. ipython:: python
   :suppress:

   import pandas as pd
   import numpy as np
   np.random.seed(123456)

********************
Options and Settings
********************

Overview
--------
pandas has an options system that lets you customize some aspects of its behaviour,
display-related options being those the user is most likely to adjust.

Options have a full "dotted-style", case-insensitive name (e.g. ``display.max_rows``).
You can get/set options directly as attributes of the top-level ``options`` attribute:

.. ipython:: python

   import pandas as pd
   pd.options.display.max_rows
   pd.options.display.max_rows = 999
   pd.options.display.max_rows

There is also an API composed of 5 relevant functions, available directly from the ``pandas``
namespace:

- :func:`~pandas.get_option` / :func:`~pandas.set_option` - get/set the value of a single option.
- :func:`~pandas.reset_option` - reset one or more options to their default value.
- :func:`~pandas.describe_option` - print the descriptions of one or more options.
- :func:`~pandas.option_context` - execute a codeblock with a set of options
  that revert to prior settings after execution.

**Note:** developers can check out pandas/core/config.py for more info.

All of the functions above accept a regexp pattern (``re.search`` style) as an argument,
and so passing in a substring will work - as long as it is unambiguous :

.. ipython:: python

   pd.get_option("display.max_rows")
   pd.set_option("display.max_rows",101)
   pd.get_option("display.max_rows")
   pd.set_option("max_r",102)
   pd.get_option("display.max_rows")


The following will **not work** because it matches multiple option names, e.g.
``display.max_colwidth``, ``display.max_rows``, ``display.max_columns``:

.. ipython:: python
   :okexcept:

   try:
       pd.get_option("column")
   except KeyError as e:
       print(e)


**Note:** Using this form of shorthand may cause your code to break if new options with similar names are added in future versions.


You can get a list of available options and their descriptions with ``describe_option``. When called
with no argument ``describe_option`` will print out the descriptions for all available options.

.. ipython:: python
   :suppress:

   pd.reset_option("all")

Getting and Setting Options
---------------------------

As described above, ``get_option()`` and ``set_option()`` are available from the
pandas namespace.  To change an option, call ``set_option('option regex', new_value)``

.. ipython:: python

   pd.get_option('mode.sim_interactive')
   pd.set_option('mode.sim_interactive', True)
   pd.get_option('mode.sim_interactive')

**Note:** that the option 'mode.sim_interactive' is mostly used for debugging purposes.

All options also have a default value, and you can use ``reset_option`` to do just that:

.. ipython:: python
   :suppress:

   pd.reset_option("display.max_rows")

.. ipython:: python

   pd.get_option("display.max_rows")
   pd.set_option("display.max_rows",999)
   pd.get_option("display.max_rows")
   pd.reset_option("display.max_rows")
   pd.get_option("display.max_rows")


It's also possible to reset multiple options at once (using a regex):

.. ipython:: python

   pd.reset_option("^display")


``option_context`` context manager has been exposed through
the top-level API, allowing you to execute code with given option values. Option values
are restored automatically when you exit the `with` block:

.. ipython:: python

   with pd.option_context("display.max_rows",10,"display.max_columns", 5):
        print(pd.get_option("display.max_rows"))
        print(pd.get_option("display.max_columns"))
   print(pd.get_option("display.max_rows"))
   print(pd.get_option("display.max_columns"))


Setting Startup Options in python/ipython Environment
-----------------------------------------------------

Using startup scripts for the python/ipython environment to import pandas and set options makes working with pandas more efficient.  To do this, create a .py or .ipy script in the startup directory of the desired profile.  An example where the startup folder is in a default ipython profile can be found at:

.. code-block:: python

  $IPYTHONDIR/profile_default/startup

More information can be found in the `ipython documentation
<http://ipython.org/ipython-doc/stable/interactive/tutorial.html#startup-files>`__.  An example startup script for pandas is displayed below:

.. code-block:: python

  import pandas as pd
  pd.set_option('display.max_rows', 999)
  pd.set_option('precision', 5)

.. _options.frequently_used:

Frequently Used Options
-----------------------
The following is a walkthrough of the more frequently used display options.

``display.max_rows`` and ``display.max_columns`` sets the maximum number
of rows and columns displayed when a frame is pretty-printed.  Truncated
lines are replaced by an ellipsis.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(7,2))
   pd.set_option('max_rows', 7)
   df
   pd.set_option('max_rows', 5)
   df
   pd.reset_option('max_rows')

``display.expand_frame_repr`` allows for the the representation of
dataframes to stretch across pages, wrapped over the full column vs row-wise.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(5,10))
   pd.set_option('expand_frame_repr', True)
   df
   pd.set_option('expand_frame_repr', False)
   df
   pd.reset_option('expand_frame_repr')

``display.large_repr`` lets you select whether to display dataframes that exceed
``max_columns`` or ``max_rows`` as a truncated frame, or as a summary.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(10,10))
   pd.set_option('max_rows', 5)
   pd.set_option('large_repr', 'truncate')
   df
   pd.set_option('large_repr', 'info')
   df
   pd.reset_option('large_repr')
   pd.reset_option('max_rows')

``display.max_colwidth`` sets the maximum width of columns.  Cells
of this length or longer will be truncated with an ellipsis.

.. ipython:: python

   df = pd.DataFrame(np.array([['foo', 'bar', 'bim', 'uncomfortably long string'],
                               ['horse', 'cow', 'banana', 'apple']]))
   pd.set_option('max_colwidth',40)
   df
   pd.set_option('max_colwidth', 6)
   df
   pd.reset_option('max_colwidth')

``display.max_info_columns`` sets a threshold for when by-column info
will be given.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(10,10))
   pd.set_option('max_info_columns', 11)
   df.info()
   pd.set_option('max_info_columns', 5)
   df.info()
   pd.reset_option('max_info_columns')

``display.max_info_rows``: ``df.info()`` will usually show null-counts for each column.
For large frames this can be quite slow. ``max_info_rows`` and ``max_info_cols``
limit this null check only to frames with smaller dimensions then specified. Note that you
can specify the option ``df.info(null_counts=True)`` to override on showing a particular frame.

.. ipython:: python

   df  =pd.DataFrame(np.random.choice([0,1,np.nan], size=(10,10)))
   df
   pd.set_option('max_info_rows', 11)
   df.info()
   pd.set_option('max_info_rows', 5)
   df.info()
   pd.reset_option('max_info_rows')

``display.precision`` sets the output display precision in terms of decimal places. This is only a
suggestion.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(5,5))
   pd.set_option('precision',7)
   df
   pd.set_option('precision',4)
   df

``display.chop_threshold`` sets at what level pandas rounds to zero when
it displays a Series of DataFrame.  Note, this does not effect the
precision at which the number is stored.

.. ipython:: python

   df = pd.DataFrame(np.random.randn(6,6))
   pd.set_option('chop_threshold', 0)
   df
   pd.set_option('chop_threshold', .5)
   df
   pd.reset_option('chop_threshold')

``display.colheader_justify`` controls the justification of the headers.
Options are 'right', and 'left'.

.. ipython:: python

   df = pd.DataFrame(np.array([np.random.randn(6), np.random.randint(1,9,6)*.1, np.zeros(6)]).T,
                     columns=['A', 'B', 'C'], dtype='float')
   pd.set_option('colheader_justify', 'right')
   df
   pd.set_option('colheader_justify', 'left')
   df
   pd.reset_option('colheader_justify')



List of Options
---------------

========================== ============ ==================================
Option                     Default      Function
========================== ============ ==================================
display.chop_threshold     None         If set to a float value, all float
                                        values smaller then the given
                                        threshold will be displayed as
                                        exactly 0 by repr and friends.
display.colheader_justify  right        Controls the justification of
                                        column headers. used by DataFrameFormatter.
display.column_space       12           No description available.
display.date_dayfirst      False        When True, prints and parses dates
                                        with the day first, eg 20/01/2005
display.date_yearfirst     False        When True, prints and parses dates
                                        with the year first, eg 2005/01/20
display.encoding           UTF-8        Defaults to the detected encoding
                                        of the console. Specifies the encoding
                                        to be used for strings returned by
                                        to_string, these are generally strings
                                        meant to be displayed on the console.
display.expand_frame_repr  True         Whether to print out the full DataFrame
                                        repr for wide DataFrames across
                                        multiple lines, `max_columns` is
                                        still respected, but the output will
                                        wrap-around across multiple "pages"
                                        if its width exceeds `display.width`.
display.float_format       None         The callable should accept a floating
                                        point number and return a string with
                                        the desired format of the number.
                                        This is used in some places like
                                        SeriesFormatter.
                                        See core.format.EngFormatter for an example.
display.height             60           Deprecated. Use `display.max_rows` instead.
display.large_repr         truncate     For DataFrames exceeding max_rows/max_cols,
                                        the repr (and HTML repr) can show
                                        a truncated table (the default from 0.13),
                                        or switch to the view from df.info()
                                        (the behaviour in earlier versions of pandas).
                                        allowable settings, ['truncate', 'info']
display.line_width         80           Deprecated. Use `display.width` instead.
display.max_columns        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
                                        pandas will correctly auto-detect
                                        the width the terminal and swap 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.
display.max_colwidth       50           The maximum width in characters of
                                        a column in the repr of a pandas
                                        data structure. When the column overflows,
                                        a "..." placeholder is embedded in
                                        the output.
display.max_info_columns   100          max_info_columns is used in DataFrame.info
                                        method to decide if per column information
                                        will be printed.
display.max_info_rows      1690785      df.info() will usually show null-counts
                                        for each column. For large frames
                                        this can be quite slow. max_info_rows
                                        and max_info_cols limit this null
                                        check only to frames with smaller
                                        dimensions then specified.
display.max_rows           60           This sets the maximum number of rows
                                        pandas should output when printing
                                        out various output. For example,
                                        this value determines whether the
                                        repr() for a dataframe prints out
                                        fully or just a summary repr.
                                        'None' value means unlimited.
display.max_seq_items      100          when pretty-printing a long sequence,
                                        no more then `max_seq_items` will
                                        be printed. If items are omitted,
                                        they will be denoted by the addition
                                        of "..." to the resulting string.
                                        If set to None, the number of items
                                        to be printed is unlimited.
display.memory_usage       True         This specifies if the memory usage of
                                        a DataFrame should be displayed when the
                                        df.info() method is invoked.
display.mpl_style          None         Setting this to 'default' will modify
                                        the rcParams used by matplotlib
                                        to give plots a more pleasing visual
                                        style by default. Setting this to
                                        None/False restores the values to
                                        their initial value.
display.multi_sparse       True         "Sparsify" MultiIndex display (don't
                                        display repeated elements in outer
                                        levels within groups)
display.notebook_repr_html True         When True, IPython notebook will
                                        use html representation for
                                        pandas objects (if it is available).
display.pprint_nest_depth  3            Controls the number of nested levels
                                        to process when pretty-printing
display.precision          6            Floating point output precision in
                                        terms of number of places after the
                                        decimal, for regular formatting as well
                                        as scientific notation. Similar to
                                        numpy's ``precision`` print option
display.show_dimensions    truncate     Whether to print out dimensions
                                        at the end of DataFrame repr.
                                        If 'truncate' is specified, only
                                        print out the dimensions if the
                                        frame is truncated (e.g. not display
                                        all rows and/or columns)
display.width              80           Width of the display in characters.
                                        In case python/IPython is running in
                                        a terminal this can be set to None
                                        and pandas will correctly auto-detect
                                        the width. Note that the IPython notebook,
                                        IPython qtconsole, or IDLE do not run in a
                                        terminal and hence it is not possible
                                        to correctly detect the width.
io.excel.xls.writer        xlwt         The default Excel writer engine for
                                        'xls' files.
io.excel.xlsm.writer       openpyxl     The default Excel writer engine for
                                        'xlsm' files. Available options:
                                        'openpyxl' (the default).
io.excel.xlsx.writer       openpyxl     The default Excel writer engine for
                                        'xlsx' files.
io.hdf.default_format      None         default format writing format, if
                                        None, then put will default to
                                        'fixed' and append will default to
                                        'table'
io.hdf.dropna_table        True         drop ALL nan rows when appending
                                        to a table
mode.chained_assignment    warn         Raise an exception, warn, or no
                                        action if trying to use chained
                                        assignment, The default is warn
mode.sim_interactive       False        Whether to simulate interactive mode
                                        for purposes of testing
mode.use_inf_as_null       False        True means treat None, NaN, -INF,
                                        INF as null (old way), False means
                                        None and NaN are null, but INF, -INF
                                        are not null (new way).
========================== ============ ==================================

.. _basics.console_output:

Number Formatting
------------------

pandas also allows you to set how numbers are displayed in the console.
This option is not set through the ``set_options`` API.

Use the ``set_eng_float_format`` function
to alter the floating-point formatting of pandas objects to produce a particular
format.

For instance:

.. ipython:: python

   import numpy as np

   pd.set_eng_float_format(accuracy=3, use_eng_prefix=True)
   s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
   s/1.e3
   s/1.e6

.. ipython:: python
   :suppress:

   pd.reset_option('^display\.')

To round floats on a case-by-case basis, you can also use :meth:`~pandas.Series.round` and :meth:`~pandas.DataFrame.round`.

.. _options.east_asian_width:

Unicode Formatting
------------------

.. warning::

   Enabling this option will affect the performance for printing of DataFrame and Series (about 2 times slower).
   Use only when it is actually required.

Some East Asian countries use Unicode characters its width is corresponding to 2 alphabets.
If DataFrame or Series contains these characters, default output cannot be aligned properly.

.. note:: Screen captures are attached for each outputs to show the actual results.

.. ipython:: python

   df = pd.DataFrame({u'国籍': ['UK', u'日本'], u'名前': ['Alice', u'しのぶ']})
   df;

.. image:: _static/option_unicode01.png

Enable ``display.unicode.east_asian_width`` allows pandas to check each character's "East Asian Width" property.
These characters can be aligned properly by checking this property, but it takes longer time than standard ``len`` function.

.. ipython:: python

   pd.set_option('display.unicode.east_asian_width', True)
   df;

.. image:: _static/option_unicode02.png

In addition, Unicode contains characters which width is "Ambiguous". These character's width should be either 1 or 2 depending on terminal setting or encoding. Because this cannot be distinguished from Python, ``display.unicode.ambiguous_as_wide`` option is added to handle this.

By default, "Ambiguous" character's width, "¡" (inverted exclamation) in below example, is regarded as 1.

.. ipython:: python

   df = pd.DataFrame({'a': ['xxx', u'¡¡'], 'b': ['yyy', u'¡¡']})
   df;

.. image:: _static/option_unicode03.png

Enabling ``display.unicode.ambiguous_as_wide`` lets pandas to figure these character's width as 2. Note that this option will be effective only when ``display.unicode.east_asian_width`` is enabled. Confirm starting position has been changed, but is not aligned properly because the setting is mismatched with this environment.

.. ipython:: python

   pd.set_option('display.unicode.ambiguous_as_wide', True)
   df;

.. image:: _static/option_unicode04.png

.. ipython:: python
   :suppress:

   pd.set_option('display.unicode.east_asian_width', False)
   pd.set_option('display.unicode.ambiguous_as_wide', False)
