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Options and Customization in Python Pandas
Divya Bhat
a year ago
In this article, we will see how we can
customize our data using different functions provided by the pandas API.
Table of Contents
- API functions
- get_option(param)
- set_option(param,value)
- reset_option()
- describe_option()
- option_context()
Pandas provides some default functions which
restrict the analysis of the data. So, to customize your data, it is important
to know the various functions available to change the default pandas behavior.
Some of the API to customize some aspects of
pandas behavior are mentioned below:
The most important API functions
are is They are −
- get_option()
- set_option()
- reset_option()
- describe_option()
- option_context()
Let’s
take an example to understand each one
get_option(param)
Pandas get_option() takes a single parameter and
returns the value as shown below−
display.max_rows
This parameter when passed will display the
default number of maximum row value. Here interpreter reads this value and
displays the rows with this value as an upper limit to display.
import pandas as pd
print pd.get_option("display.max_rows")Output
60display.max_columns
When this parameter is passed it displays the
default maximum number of values of the columns. Here, the interpreter reads this
value and displays the columns with this value as an upper limit to display.
import pandas as pd
print pd.get_option("display.max_columns")Output
20Note: Here, 60 and 20 are the default configuration parameter
values rows and columns respectively.
set_option(param,value)
Pandas
has a set_option function which takes two arguments and sets the value to the
parameter as given by the user.
Let’s
take an example
display.max_rows
By using this set_option(), we can
change the default number of rows to be displayed as per requirement.
Live Demo
import pandas as pd
pd.set_option("display.max_rows",80)
print pd.get_option("display.max_rows")Output
100display.max_columns
By using this set_option(), we can
change the default number of columns to be displayed as per our requirement.
import pandas as pd
pd.set_option("display.max_columns",30)
print pd.get_option("display.max_columns")Output
50reset_option(param)
Pandas has another method reset_option
which takes an argument and sets the value back to the default value.
display.max_rows
With
this reset_option(), we can change the value back to the default number
of rows to be displayed.
Let’s
take an example
import pandas as pd
pd.reset_option("display.max_rows")
print pd.get_option("display.max_rows")Output
60describe_option(param)
describe_option
helps us to print out the description of the argument.
display.max_rows
With reset_option(),
we can change the value back to the default number of rows to be displayed.
import pandas as pd
pd.describe_option("display.max_rows")Output
display.max_rows : int
If max_rows is exceeded, switch to truncate view. Depending on
'large_repr', objects are either centrally truncated or printed as
a summary view. 'none' value means unlimited.
In case python/IPython is running in a terminal and `large_repr`
equals 'truncate' this can be set to 0 and pandas will auto-detect
the height of the terminal and print a truncated object which fits
the screen height. The IPython notebook, IPython qtconsole, or
IDLE do not run in a terminal and hence it is not possible to do
correct auto-detection.
[default: 60] [currently: 60]option_context()
This option_context is a context manager which is used to set the option in with a statement temporarily. Option values are restored automatically when
you exit the with block −
display.max_rows
With option_context(), we can set the value
temporarily.
Let’s take an example
import pandas as pd
with pd.option_context("display.max_rows",35):
print(pd.get_option("display.max_rows"))
print(pd.get_option("display.max_rows"))Output
35
35You may notice, the difference between the first
and the second print statements. The first statement prints the value set
by option_context() which is temporary within the with
context itself. After the with context, the second print
statement prints out the configured value as per our requirements.
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