Print list as tabular data in Python

Data manipulation and analysis are key aspects of programming, especially when working with large data sets. A challenge programmers often face is how to present data in a clear and organized format that facilitates understanding and analysis. Being a versatile language, Python provides various techniques and libraries to print lists as tabular data, thus enabling visually appealing representation of information. Printing a list as tabular data involves arranging the data in rows and columns, similar to a tabular structure. This format makes it easier to compare and understand the relationships between different data points. Whether you are working on a data analysis project, generating reports, or presenting information to stakeholders, being able to print a list as a table in Python is a valuable skill.

In this article, we will explore the different methods and libraries in Python for printing lists as tabular data. We'll start with the basics, creating a simple table using the built-in print() function. We'll then dive into more advanced techniques utilizing popular libraries like tabulate and PrettyTable. So, make sure to read this article till the end for better understanding.

Use the built-in print() function

The easiest way to print a list as a table is to use the built-in print() function. However, this approach only works for basic tables with uniform row lengths.

This is an example you can refer to:

data = [
    ['Name', 'Age', 'Country'],
    ['John Doe', '25', 'USA'],
    ['Jane Smith', '32', 'Canada'],
    ['Mark Johnson', '45', 'UK']
]

for row in data:
    print('\t'.join(row))

Output

Name         Age    Country
John Doe     25     USA
Jane Smith   32     Canada
Mark Johnson 45     UK

In the above code snippet, we use the join() method to join each row element with the tab character ('\t'). The printed result is a tab-delimited table-like structure.

While this method is quick and easy, it requires more flexibility to handle complex table formatting such as alignment and headers. For more advanced table printing options we can use external libraries.

Use tabulate library

Thetabulate library is a good choice for handling more complex tabular formats. It offers a variety of formatting options, including adding table headers, modifying alignment, and choosing a table style (such as "plain", "simple", "grid" or "fancy_grid").

To use tabulate, we first need to install it using the following command:

pip install tabulate

Successful output

Collecting tabulate
  Downloading tabulate-0.8.9-py3-none-any.whl (25 kB)
Installing collected packages: tabulate
Successfully installed tabulate-0.8.9

Once installed, we can use the library to output lists as tables. Let's update our earlier example to add the tabulate library.

Here is the code to open the terminal and start execution:

Example

from tabulate import tabulate

data = [
    ['Name', 'Age', 'Country'],
    ['John Doe', '25', 'USA'],
    ['Jane Smith', '32', 'Canada'],
    ['Mark Johnson', '45', 'UK']
]

print(tabulate(data, headers='firstrow', tablefmt='fancy_grid'))

Output

╒═════════════╤═════╤═════════╕
│ Name        │ Age │ Country │
╞═════════════╪═════╪═════════╡
│ John Doe    │ 25  │ USA     │
├─────────────┼─────┼─────────┤
│ Jane Smith  │ 32  │ Canada  │
├─────────────┼─────┼─────────┤
│ Mark Johnson│ 45  │ UK      │
╘═════════════╧═════╧═════════╛

We import the tabulate function from the tabulate library in the above code snippet. The first parameter of the tabulate() function is a data list. We set the headers parameter to 'firstrow', which means the first row contains the header. The tablefmt parameter specifies the desired table format ('fancy_grid' in this example).

Thetabulate library provides a variety of table formats to choose from, depending on the visual appearance requirements of the table. For example, the 'plain' format provides a simple table without any extra decoration, while the 'grid' format adds vertical and horizontal lines to separate cells. The flexibility of this library allows us to present the data in a way that best suits our needs.

Use PrettyTable

PrettyTable is another popular library for rendering lists as tables. It provides a simple and intuitive way to create and customize tables.

To install PrettyTable, use the following command:

pip install prettytable

Successful output

Collecting prettytable
  Downloading prettytable-2.2.1-py3-none-any.whl (22 kB)
Requirement already satisfied: setuptools in /usr/local/lib/python3.9/site-packages (from prettytable) (57.4.0)
Installing collected packages: prettytable
Successfully installed prettytable-2.2.1

Once installed, we can use this library to print the list into a table. Let's modify the previous example to include the PrettyTable library.

Example

Refer to the code below:

from prettytable import PrettyTable

table = PrettyTable()
table.field_names = ['Name', 'Age', 'Country']
table.add_row(['John Doe', '25', 'USA'])
table.add_row(['Jane Smith', '32', 'Canada'])
table.add_row(['Mark Johnson', '45', 'UK'])

print(table)

Output

+--------------+-----+---------+
|     Name     | Age | Country |
+--------------+-----+---------+
|   John Doe   |  25 |   USA   |
|  Jane Smith  |  32 |  Canada |
| Mark Johnson |  45 |    UK   |
+--------------+-----+---------+

In the above code, we imported the PrettyTable class from the prettytable package. We create a PrettyTable object and set the field names using the field_names property. Then use the add_row() method to add rows to the table. Finally, we print the table object, which is automatically formatted in table format.

There are many benefits to using PrettyTable, including the ability to change the appearance of the table. You can even sort your data while specifying column alignment and modifying border designs and footer row additions before printing. This makes it possible to present the data in a more aesthetically pleasing and educational way.

in conclusion

In summary, printing lists as tabular data in Python is a valuable data processing and presentation skill. In this article, we explored various techniques and libraries, such as tabulate and PrettyTable, that can effectively help us accomplish this task. These tools allow us to transform raw data into structured and visually appealing tables, making it easier for us to understand and communicate our data-driven insights. Whether we choose the simplicity of the built-in print() function or the variety of external libraries, Python provides us with the necessary resources to present our data in a structured and organized way. By mastering these technologies, we can improve our data analysis and presentation skills, effectively deliver information to stakeholders, and make our work more impactful.

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