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features
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Description

The Pylons web framework is tailored for the straightforward and efficient creation of web applications and websites. These applications can vary significantly in size, ranging from a simple Python module to an extensive directory structure suitable for more intricate web solutions. With the availability of project templates, Pylons allows developers to quickly initiate a new web application, or they can opt to create a custom setup from square one to meet their specific requirements. This framework simplifies the process of developing web applications in Python, embracing a minimalist and component-based approach that enhances expandability. It also leverages developers' existing knowledge of Python, promoting an extensible application design that is both fast and efficient. The framework boasts an impressively small per-request call stack, which ensures exceptional performance levels and relies on established, reliable Python packages. While the Pylons 1.0 series is recognized as stable and ready for production, it is currently only in maintenance mode. Moving forward, the Pylons Project has shifted its focus to the Pyramid web framework for ongoing development, and users of Pylons 1.0 are highly encouraged to consider transitioning to Pyramid for their upcoming projects, which offers even more advanced functionalities and support. This transition can significantly enhance the development experience and provide access to new features that are continuously being improved.

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

Screenshots View All

Screenshots View All

Integrations

3LC
Amazon SageMaker Data Wrangler
ApertureDB
Cleanlab
Codédex
Coiled
Daft
Dagster
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
Python
RunCode
Sliq
TeamStation
ThinkData Works
Union Pandera

Integrations

3LC
Amazon SageMaker Data Wrangler
ApertureDB
Cleanlab
Codédex
Coiled
Daft
Dagster
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
Python
RunCode
Sliq
TeamStation
ThinkData Works
Union Pandera

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

Python Software Foundation

Country

United States

Website

pypi.org/project/Pylons/

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

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Alternatives

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