.. currentmodule:: pandas
.. ipython:: python :suppress: import pandas as pd import numpy as np np.random.seed(123456)
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
The API is 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:
:okwarning:
pd.reset_option("all")
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
:okwarning:
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"))
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:
$IPYTHONDIR/profile_default/startup
More information can be found in the ipython documentation. An example startup script for pandas is displayed below:
import pandas as pd
pd.set_option('display.max_rows', 999)
pd.set_option('precision', 5)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')
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:
:okwarning:
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`.
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 whose width corresponds to two Latin characters. If a DataFrame or Series contains these characters, the default output mode may not align them properly.
Note
Screen captures are attached for each output 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;
Enabling display.unicode.east_asian_width allows pandas to check each character's "East Asian Width" property.
These characters can be aligned properly by setting this option to True. However, this will result in longer render
times than the standard len function.
.. ipython:: python
pd.set_option('display.unicode.east_asian_width', True)
df;
In addition, Unicode characters whose width is "Ambiguous" can either be 1 or 2 characters wide depending on the
terminal setting or encoding. The option display.unicode.ambiguous_as_wide can be used to handle the ambiguity.
By default, an "Ambiguous" character's width, such as "¡" (inverted exclamation) in the example below, is taken to be 1.
.. ipython:: python
df = pd.DataFrame({'a': ['xxx', u'¡¡'], 'b': ['yyy', u'¡¡']})
df;
Enabling display.unicode.ambiguous_as_wide makes pandas interpret these characters' widths to be 2.
(Note that this option will only be effective when display.unicode.east_asian_width is enabled.)
However, setting this option incorrectly for your terminal will cause these characters to be aligned incorrectly:
.. ipython:: python
pd.set_option('display.unicode.ambiguous_as_wide', True)
df;
.. ipython:: python
:suppress:
pd.set_option('display.unicode.east_asian_width', False)
pd.set_option('display.unicode.ambiguous_as_wide', False)
.. versionadded:: 0.20.0
DataFrame and Series will publish a Table Schema representation
by default. False by default, this can be enabled globally with the
display.html.table_schema option:
.. ipython:: python
pd.set_option('display.html.table_schema', True)
Only 'display.max_rows' are serialized and published.
.. ipython:: python
:suppress:
pd.reset_option('display.html.table_schema')