Displaying Long Strings in Pandas: How to Print Complete Text in DataFrame Without Truncation

Introduction

While working with pandas DataFrames, we may get the truncated text data especially if the data size is large. The truncation of the text data while displaying can create difficulties when attempting to thoroughly analyze the complete content. This is frustrating, especially when the text contains important details that are crucial for the analysis. However, there are a few strategies we can use to ensure that we have access to the complete text in a DataFrame without any truncation. In this post, we will discuss some simple methods that can be used to print complete text in a dataframe without truncation. Also, if you are facing any challenge in displaying the complete dataframe (not a column value) on the screen in pandas when the dataframe is large, this post “Display All Columns of a Pandas DataFrame” can help you to display the complete dataframe on the screen without any column truncation.

Challenges in Printing Complete Text in a DataFrame Without Truncation

The challenge of displaying long text in a pandas DataFrame arises when working with data that contains large texts. By default, the pandas library truncates or abbreviates these long text entries when displaying them in tabular form. This truncation or abbreviation of the data makes it difficult to analyze the complete information. Addressing this challenge often involves customizing the DataFrame’s display settings which we will discuss in this post.

To demonstrate this, we will use the below line of code to generate a dataframe with a long text value and print the dataframe using the print method.

# Import pandas and numpy libraries
import pandas as pd

def generate_sample_data():
    # Create a dictionary with sample column and long text data
    dct = {"text_col": ["By adjusting the bitrate settings and choosing an appropriate preset, you can significantly reduce the file size of your video while maintaining an acceptable level of quality. Experiment with different settings to find the right balance for your specific project and output requirements.", 
    "By adjusting the bitrate settings and choosing an appropriate preset, you can significantly reduce the file size of your video while maintaining an acceptable level of quality. Experiment with different settings to find the right balance for your specific project and output requirements.", 
    "By adjusting the bitrate settings and choosing an appropriate preset, you can significantly reduce the file size of your video while maintaining an acceptable level of quality. Experiment with different settings to find the right balance for your specific project and output requirements.", 
    "By adjusting the bitrate settings and choosing an appropriate preset, you can significantly reduce the file size of your video while maintaining an acceptable level of quality. Experiment with different settings to find the right balance for your specific project and output requirements.", 
    "By adjusting the bitrate settings and choosing an appropriate preset, you can significantly reduce the file size of your video while maintaining an acceptable level of quality. Experiment with different settings to find the right balance for your specific project and output requirements."]}
    
    # Create the DataFrame using pandas
    df = pd.DataFrame(dct)
 
    # Print the DataFrame
    print(df.head())

if __name__ == "__main__":
    generate_sample_data()

When we execute the above print command, we get this output.

In the output, we can see that the long text data is truncated which makes it difficult to analyze.

Print Complete Text in DataFrame Without Truncation

Let’s discuss how we can print Complete Text in DataFrame Without Truncation.

Displaying Long Strings in Pandas without truncation

There are several ways to display long texts effectively in pandas. However, we will discuss the easiest methods to display the text data without truncation here. Let’s explore some of these techniques:

1. Using max_colwidth option

By default, pandas truncates text in the DataFrame cells to fit it on the screen while displaying it. This truncation can sometimes make it difficult to analyze the full content of the cells, especially when working with large datasets or lengthy text. However, there is a simple solution to address this issue.

In pandas, we can adjust the settings using the set_option() method to display the complete text instead of the truncated version. By modifying the display.max_colwidth option, we can specify the maximum width for each cell in the DataFrame. This allows us to view and analyze the entire content without any loss of information. For example, if we want to set the maximum width to 1000 characters, we can use the following code:

import pandas as pd
pd.set_option('display.max_colwidth', 1000)

Now, when we display the DataFrame, we will see that the cells containing text are not truncated but are displayed in their entirety, up to the specified width. This simple setting adjustment can greatly enhance the data analysis experience when working with text-based data in pandas.

2. Using to_string method

We can also utilize the to_string() method in Python to display the complete text rather than the truncated text. We can display the full text within our dataframe effortlessly. This method allows us to convert the dataframe to a formatted string representation, ensuring that all the text is visible and easily readable. To implement this, we can simply call the to_string() method on the dataframe object. This will return a string representation of the entire dataframe, including every row and column, with the complete text displayed on the screen. By invoking the to_string() method on the dataframe, we can ensure that the full text in each cell is visible, eliminating the need to worry about truncated or incomplete information.

For example, if we want to display the dataframe using to_string() method, we can use the following code:

import pandas as pd
print(df.head().to_string())

It is important to note that the to_string() method also provides various parameters and options that helps us to customize the formatting of the string representation. This flexibility enables us to tailor the output to suit our specific requirements, such as controlling the maximum width of columns or the number of decimal places displayed.

Conclusion

Printing complete text in a pandas DataFrame without truncation is essential for gaining insights from the data, especially when dealing with lengthy text content. By adjusting pandas settings using the pd.set_option method, we can easily display the complete text, ensuring that no information is lost due to the truncation. We can also display the dataframe content using to_string() method by converting the dataframe into a formatted string. These techniques enhance the ability to perform comprehensive data analysis and help us to take informed decisions based on the complete text content.

Thanks for the reading. Please share your inputs in the comment section.