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Description
The Python Imaging Library enhances your Python interpreter with advanced image processing features. This library offers a wide range of file format compatibility, an efficient internal structure, and robust image processing functionalities. Its core design focuses on enabling quick access to data in several fundamental pixel formats, serving as a reliable base for general image processing applications. For enterprises, Pillow is accessible through a Tidelift subscription, catering to professional needs. The Python Imaging Library is particularly well-suited for tasks related to image archiving and batch processing workflows. Users can leverage the library to generate thumbnails, switch between file formats, print images, and more. The latest version supports a diverse array of formats, while write capabilities are carefully limited to the most prevalent interchange and display formats. Additionally, the library includes essential image processing features such as point operations, filtering through built-in convolution kernels, and converting color spaces, making it a comprehensive tool for both casual and advanced users alike. Its versatility ensures that developers can efficiently handle various image-related tasks with ease.
Description
Pandas is an open-source data analysis and manipulation tool that is not only fast and powerful but also highly flexible and user-friendly, all within the Python programming ecosystem. It provides various tools for importing and exporting data across different formats, including CSV, text files, Microsoft Excel, SQL databases, and the efficient HDF5 format. With its intelligent data alignment capabilities and integrated management of missing values, users benefit from automatic label-based alignment during computations, which simplifies the process of organizing disordered data. The library features a robust group-by engine that allows for sophisticated aggregating and transforming operations, enabling users to easily perform split-apply-combine actions on their datasets. Additionally, pandas offers extensive time series functionality, including the ability to generate date ranges, convert frequencies, and apply moving window statistics, as well as manage date shifting and lagging. Users can even create custom time offsets tailored to specific domains and join time series data without the risk of losing any information. This comprehensive set of features makes pandas an essential tool for anyone working with data in Python.
API Access
Has API
API Access
Has API
Integrations
3LC
Activeeon ProActive
Amazon SageMaker Data Wrangler
ApertureDB
Avanzai
Coiled
Daft
DagsHub
Dagster
Flyte
Integrations
3LC
Activeeon ProActive
Amazon SageMaker Data Wrangler
ApertureDB
Avanzai
Coiled
Daft
DagsHub
Dagster
Flyte
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Pillow
Founded
1995
Country
United States
Website
pillow.readthedocs.io/en/stable/
Vendor Details
Company Name
pandas
Founded
2008
Website
pandas.pydata.org
Product Features
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics