Python Pandas Tutorial
Python Pandas Useful Resources
Selected Reading
- Comparison with SQL
- Python Pandas - Caveats & Gotchas
- Python Pandas - Sparse Data
- Python Pandas - IO Tools
- Python Pandas - Visualization
- Python Pandas - Categorical Data
- Python Pandas - Timedelta
- Python Pandas - Date Functionality
- Python Pandas - Concatenation
- Python Pandas - Merging/Joining
- Python Pandas - GroupBy
- Python Pandas - Missing Data
- Python Pandas - Aggregations
- Python Pandas - Window Functions
- Statistical Functions
- Indexing & Selecting Data
- Options & Customization
- Working with Text Data
- Python Pandas - Sorting
- Python Pandas - Iteration
- Python Pandas - Reindexing
- Function Application
- Descriptive Statistics
- Python Pandas - Basic Functionality
- Python Pandas - Panel
- Python Pandas - DataFrame
- Python Pandas - Series
- Introduction to Data Structures
- Python Pandas - Environment Setup
- Python Pandas - Introduction
- Python Pandas - Home
Python Pandas Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Options & Customization
Python Pandas - Options and Customization
Pandas provide API to customize some aspects of its behavior, display is being mostly used.
The API is composed of five relevant functions. They are −
get_option()
set_option()
reset_option()
describe_option()
option_context()
Let us now understand how the functions operate.
get_option(param)
get_option takes a single parameter and returns the value as given in the output below −
display.max_rows
Displays the default number of value. Interpreter reads this value and displays the rows with this value as upper pmit to display.
import pandas as pd
print pd.get_option("display.max_rows")
Its output is as follows −
60
display.max_columns
Displays the default number of value. Interpreter reads this value and displays the rows with this value as upper pmit to display.
import pandas as pd
print pd.get_option("display.max_columns")
Its output is as follows −
20
Here, 60 and 20 are the default configuration parameter values.
set_option(param,value)
set_option takes two arguments and sets the value to the parameter as shown below −
display.max_rows
Using set_option(), we can change the default number of rows to be displayed.
import pandas as pd
pd.set_option("display.max_rows",80)
print pd.get_option("display.max_rows")
Its output is as follows −
80
display.max_columns
Using set_option(), we can change the default number of rows to be displayed.
import pandas as pd
pd.set_option("display.max_columns",30)
print pd.get_option("display.max_columns")
Its output is as follows −
30
reset_option(param)
reset_option takes an argument and sets the value back to the default value.
display.max_rows
Using reset_option(), we can change the value back to the default number of rows to be displayed.
import pandas as pd
pd.reset_option("display.max_rows")
print pd.get_option("display.max_rows")
Its output is as follows −
60
describe_option(param)
describe_option prints the description of the argument.
display.max_rows
Using 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")
Its output is as follows −
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 unpmited.
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()
option_context context manager is used to set the option in with statement temporarily. Option values are restored automatically when you exit the with block −
display.max_rows
Using option_context(), we can set the value temporarily.
import pandas as pd
with pd.option_context("display.max_rows",10):
print(pd.get_option("display.max_rows"))
print(pd.get_option("display.max_rows"))
Its output is as follows −
10 10
See, 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 the configured value.
Frequently used Parameters
| Sr.No | Parameter & Description |
|---|---|
| 1 |
display.max_rows Displays maximum number of rows to display |
| 2 |
2 display.max_columns Displays maximum number of columns to display |
| 3 |
display.expand_frame_repr Displays DataFrames to Stretch Pages |
| 4 |
display.max_colwidth Displays maximum column width |
| 5 |
display.precision Displays precision for decimal numbers |