Pandas: Get and Set Options for Display, Data Behaviour in Python

The Pandas control various display and data behavior options to customize the way data is presented and how operations are performed. You can use the pd.get_option() and pd.set_option() functions to get and set these options, respectively.

Here are some common options you might want to modify:

1. Display Options:

• display.max_rows: Maximum number of rows to display in the DataFrame.
• display.max_columns: Maximum number of columns to display in the DataFrame.
• display.precision: Number of decimal places to display for floating-point numbers.
• display.width: Maximum width of the display output. Example:

 import pandas as pd

 # Get the current value of max_rows
 max_rows_value = pd.get_option("display.max_rows")
 print("Current max_rows value:", max_rows_value)

 # Set max_rows to display only 10 rows
 pd.set_option("display.max_rows", 10)

 # Set precision for floating-point numbers
 pd.set_option("display.precision", 2)

 # Display your DataFrame
 print(your_dataframe)

2. Data Options:

• mode.chained_assignment: Control how warnings are issued when performing chained assignment operations.
• compute.use_bottleneck: Control whether to use the Bottleneck library for certain operations (can improve performance). Example:

 import pandas as pd

 # Disable the warning for chained assignment
 pd.set_option("mode.chained_assignment", None)

 # Enable Bottleneck for certain operations
 pd.set_option("compute.use_bottleneck", True)

3. I/O Options:

• io.excel.xlsx.reader: Control the Excel engine used for reading Excel files.
• io.excel.xlsx.writer: Control the Excel engine used for writing Excel files. Example:

 import pandas as pd

 # Set the Excel reader to use 'openpyxl'
 pd.set_option("io.excel.xlsx.reader", "openpyxl")

4. Other Options:

• There are many other options you can explore in the Pandas documentation for fine-tuning your Pandas experience.

Remember that modifying these options can affect the behavior of Pandas throughout your script or notebook, so it’s important to set them appropriately for your specific use case. To revert to default options, you can use pd.reset_option() with the option you want to reset.

For a comprehensive list of available options and their descriptions, refer to the official Pandas documentation:
https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html