How to display all rows from dataframe using Pandas?

Pandas is a powerful data manipulation library in Python that provides a flexible way to handle tabular data through its DataFrame object. By default, Pandas truncates DataFrame display output when there are many rows, showing only a limited number to keep output concise and readable.

Using to_string() Method

The to_string() method displays the complete DataFrame regardless of the number of rows or columns ?

import pandas as pd

# Create sample data
data = {
    'Name': ['Sachin Tendulkar', 'Brian Lara', 'Ricky Ponting', 'Jacques Kallis', 'Inzamam-ul-Haq'],
    'Country': ['India', 'West Indies', 'Australia', 'South Africa', 'Pakistan'],
    'Debut Year': [1989, 1990, 1995, 1995, 1991],
    'Retirement Year': [2013, 2007, 2012, 2014, 2007]
}

cricketers_df = pd.DataFrame(data)
print(cricketers_df.to_string())

             Name       Country  Debut Year  Retirement Year
0  Sachin Tendulkar         India        1989             2013
1        Brian Lara   West Indies        1990             2007
2     Ricky Ponting     Australia        1995             2012
3    Jacques Kallis  South Africa        1995             2014
4    Inzamam-ul-Haq      Pakistan        1991             2007

Using to_markdown() Method

The to_markdown() method converts the DataFrame to a Markdown-formatted table that's easy to read and can be used in documentation ?

import pandas as pd

data = {
    'Name': ['Sachin Tendulkar', 'Brian Lara', 'Ricky Ponting', 'Jacques Kallis', 'Inzamam-ul-Haq'],
    'Country': ['India', 'West Indies', 'Australia', 'South Africa', 'Pakistan'],
    'Debut Year': [1989, 1990, 1995, 1995, 1991],
    'Retirement Year': [2013, 2007, 2012, 2014, 2007]
}

cricketers_df = pd.DataFrame(data)
print(cricketers_df.to_markdown())

|    | Name             | Country      |   Debut Year |   Retirement Year |
|---:|:-----------------|:-------------|-------------:|------------------:|
|  0 | Sachin Tendulkar | India        |         1989 |              2013 |
|  1 | Brian Lara       | West Indies  |         1990 |              2007 |
|  2 | Ricky Ponting    | Australia    |         1995 |              2012 |
|  3 | Jacques Kallis   | South Africa |         1995 |              2014 |
|  4 | Inzamam-ul-Haq   | Pakistan     |         1991 |              2007 |

Using option_context() for Temporary Settings

The option_context() function temporarily modifies display options within a specific context. Setting display.max_rows to None shows all rows ?

import pandas as pd

# Create larger dataset
data = {
    'Fruit': ['Apple', 'Orange', 'Banana', 'Grapes', 'Pineapple', 'Strawberry', 'Watermelon', 'Kiwi'],
    'Color': ['Red', 'Orange', 'Yellow', 'Green', 'Brown', 'Red', 'Green', 'Brown'],
    'Weight (oz)': [4.0, 6.0, 5.0, 3.0, 16.0, 1.0, 128.0, 3.0],
    'Price ($)': [0.50, 0.40, 0.20, 0.30, 1.50, 0.10, 2.00, 0.30]
}

fruits_df = pd.DataFrame(data)

with pd.option_context('display.max_rows', None):
    print(fruits_df)

       Fruit   Color  Weight (oz)  Price ($)
0      Apple     Red          4.0       0.50
1     Orange  Orange          6.0       0.40
2     Banana  Yellow          5.0       0.20
3     Grapes   Green          3.0       0.30
4  Pineapple   Brown         16.0       1.50
5 Strawberry     Red          1.0       0.10
6 Watermelon   Green        128.0       2.00
7       Kiwi   Brown          3.0       0.30

Using set_option() for Permanent Settings

The set_option() method permanently changes display settings until modified again ?

import pandas as pd

data = {
    'Fruit': ['Apple', 'Orange', 'Banana', 'Grapes', 'Pineapple', 'Strawberry'],
    'Color': ['Red', 'Orange', 'Yellow', 'Green', 'Brown', 'Red'],
    'Weight (oz)': [4.0, 6.0, 5.0, 3.0, 16.0, 1.0],
    'Price ($)': [0.50, 0.40, 0.20, 0.30, 1.50, 0.10]
}

fruits_df = pd.DataFrame(data)

# Set permanent option to display all rows
pd.set_option('display.max_rows', None)
print(fruits_df)

# Reset to default (optional)
pd.reset_option('display.max_rows')

       Fruit   Color  Weight (oz)  Price ($)
0      Apple     Red          4.0       0.50
1     Orange  Orange          6.0       0.40
2     Banana  Yellow          5.0       0.20
3     Grapes   Green          3.0       0.30
4  Pineapple   Brown         16.0       1.50
5 Strawberry     Red          1.0       0.10

Comparison of Methods

Conclusion

Use to_string() for quick console output, to_markdown() for documentation, option_context() for temporary changes, and set_option() for permanent display modifications. Choose the method based on whether you need temporary or permanent changes to display settings.