Add functionalities such as building tables, data grids, and interactive data visualizations into your application easily and in a visually appealing way with the Python table libraries.
Python table libraries are highly useful in advanced applications with data management functions such as analytics, data science, and machine learning. Using these libraries, you can represent data in an organized manner while controlling and customizing various aspects of a table. These include:
- width and column padding
- text alignment
- data sorting
- table borders, and more.
These libraries also provide a large number of predefined formats that allows you to publish tables in different ways. Also, you can format the tables to publish on popular project management software such as Jira and GitHub.
Explore the top and trending Python table libraries to add table formatting features in your applications:
prettytable
- Supports custom table formatting and styling.
- Allows adding, deleting, and rearranging columns easily.
- Provides a simple way to display tabular data in a text-based interface.
prettytableby jazzband
Display tabular data in a visually appealing ASCII table format
prettytableby jazzband
Python
1034
Version:3.7.0
License: Others (Non-SPDX)
pytablewriter
- Supports various file formats for table export (CSV, Excel, JSON, etc.).
- Allows fine-grained control over cell alignment and formatting.
- Offers an intuitive and extensible API for creating and writing tables.
pytablewriterby thombashi
pytablewriter is a Python library to write a table in various formats: AsciiDoc / CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV.
pytablewriterby thombashi
Python
555
Version:v0.64.2
License: Permissive (MIT)
python-tabulate
- Provides multiple table styles and formatting options.
- Supports data alignment, numbering, and various output formats.
- Can render tables as plain text or HTML for different use cases.
python-tabulateby astanin
Pretty-print tabular data in Python, a library and a command-line utility. Repository migrated from bitbucket.org/astanin/python-tabulate.
python-tabulateby astanin
Python
1622
Version:Current
License: Permissive (MIT)
dataset
- Offers a simplified interface for working with databases.
- Supports data loading, querying, and manipulation with minimal code.
- Provides a consistent API across different database backends.
datasetby pudo
Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.
datasetby pudo
Python
4524
Version:Current
License: Permissive (MIT)
camelot
- Specialized for extracting tables from PDF documents.
- Supports both text-based and image-based table extraction.
- Offers advanced table configuration options for precise extraction.
pdftabextract
- Designed for OCR-based table extraction from scanned PDFs.
- Provides tools for layout analysis and structured table data extraction.
- Useful for digitizing tabular information from documents.
pdftabextractby WZBSocialScienceCenter
A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.
pdftabextractby WZBSocialScienceCenter
Python
2059
Version:Current
License: Permissive (Apache-2.0)
django-tables2
- Integrates seamlessly with Django web applications.
- Offers a declarative syntax for defining table structures.
- Supports sorting, pagination, and customization of table rendering.
django-tables2by jieter
django-tables2 - An app for creating HTML tables
django-tables2by jieter
Python
1643
Version:Current
License: Others (Non-SPDX)
django-watson
- A full-text search library for Django applications.
- Provides efficient search functionality across multiple models.
- Supports stemming, ranking, and result highlighting.
django-watsonby etianen
Full-text multi-table search application for Django. Easy to install and use, with good performance.
django-watsonby etianen
Python
1100
Version:release-1.6.3
License: Permissive (BSD-3-Clause)
petl
- A powerful library for ETL (Extract, Transform, Load) operations on tabular data.
- Offers a wide range of data manipulation functions.
- Integrates well with other data processing libraries like pandas.
petlby petl-developers
Python Extract Transform and Load Tables of Data
petlby petl-developers
Python
1100
Version:v1.7.12
License: Permissive (MIT)
csvtotable
- Converts CSV data into an interactive HTML table.
- Supports data sorting, filtering, and pagination in the web interface.
- Suitable for quickly visualizing and exploring CSV data.
csvtotableby vividvilla
Simple command-line utility to convert CSV files to searchable and sortable HTML table.
csvtotableby vividvilla
Python
1048
Version:v2.1.2
License: Permissive (MIT)
textfsm
- A template-based text parsing library.
- Used for extracting structured data from unstructured text.
- Commonly used for parsing network device configuration files.
textfsmby google
Python module for parsing semi-structured text into python tables.
textfsmby google
Python
1014
Version:v1.1.3
License: Permissive (Apache-2.0)
rows
- A minimalistic library for working with tabular data.
- Provides basic data manipulation and serialization capabilities.
- Lightweight and easy to use for simple table operations.
rowsby turicas
A common, beautiful interface to tabular data, no matter the format
rowsby turicas
Python
846
Version:v0.4.1
License: Weak Copyleft (LGPL-3.0)
image2csv
- Converts images containing tabular data into CSV format.
- Useful for digitizing data from scanned documents or images.
- Supports customization of image preprocessing and OCR options.
image2csvby artperrin
Convert tables stored as images to an usable .csv file
image2csvby artperrin
Python
742
Version:Current
License: Permissive (MIT)
csvtomd
- Converts CSV data into Markdown tables for documentation.
- Supports alignment and column formatting in Markdown.
- Useful for generating human-readable documentation from CSV data.
csvtomdby mplewis
📝📊 Convert your CSV files into Markdown tables.
csvtomdby mplewis
Python
632
Version:Current
License: Permissive (MIT)
Pylsy
- Creates pretty ASCII tables with cell alignment.
- Offers easy customization of table styling and formatting.
- Suitable for displaying tabular data in console applications.
Pylsyby Leviathan1995
Pylsy is a simple python library draw tables in the Terminal. Just two lines of code .
Pylsyby Leviathan1995
Python
467
Version:Current
License: Others (Non-SPDX)
jupyter_pivottablejs
- Integrates with Jupyter Notebook for interactive pivot table creation.
- Allows users to explore and analyze data with a graphical interface.
- Supports aggregation, filtering, and dynamic table manipulation within Jupyter notebooks.
jupyter_pivottablejsby nicolaskruchten
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js
jupyter_pivottablejsby nicolaskruchten
Python
572
Version:v0.9.0
License: Others (Non-SPDX)
FAQ
1. What Python libraries are available for data visualization?
Python boasts a plethora of libraries for data visualization. Some popular ones include Matplotlib, Seaborn, Plotly, and Bokeh. Each tool has different features and abilities. Analysts and scientists use this to make charts and graphs and study data better.
2. How can a Python data visualization library help someone in a Data Science Career?
Employing a Python data visualization library is instrumental in a Data Science career. It enables professionals to convey complex data findings in a visually comprehensible manner. This helps with decision-making using data and sharing insights to improve business results.
3. Which software do you need to run the PrettyTable library?
You do not need additional software to use the PrettyTable library in Python. This Python library can be easily added to Python scripts or projects. It doesn't require any external dependencies.
4. Is there a machine learning library available for Python?
Python has many machine learning libraries, and scikit-learn is a popular one. Python is a flexible platform for machine learning. It has powerful libraries like TensorFlow, PyTorch, and Keras. These libraries cater to deep learning and neural networks.
5. How does one learn Python, and which libraries should they focus on first?
Learning Python begins with grasping the fundamentals of the language. To become a programmer, start by learning libraries like NumPy and Pandas. These will help you manipulate data. Once you feel comfortable, you can use Matplotlib and Seaborn to visualize data. To delve into machine learning, starting with scikit-learn is advisable. Online tutorials, courses, and hands-on projects help you learn Python and its libraries.