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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 No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Data Wrangler No 
Avanzai No 
Cleanlab No 
DagsHub No 
Dagster No 
Dash No 
Flower No 
GLM-5.1 No 
GLM-5.2 No 
GLM-5.3 No 
Giskard No 
Kedro No 
LanceDB No 
OrcaSheets No 
Sliq No 
Spyder No 
Tidelift Yes 
Union Pandera No 
imageio Yes 
skills.ai No 

Integrations

Amazon SageMaker Data Wrangler Yes 
Avanzai Yes 
Cleanlab Yes 
DagsHub Yes 
Dagster Yes 
Dash Yes 
Flower Yes 
GLM-5.1 Yes 
GLM-5.2 Yes 
GLM-5.3 Yes 
Giskard Yes 
Kedro Yes 
LanceDB Yes 
OrcaSheets Yes 
Sliq Yes 
Spyder Yes 
Tidelift No 
Union Pandera Yes 
imageio No 
skills.ai Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

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

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Alternatives

Alternatives

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