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Description

React Spectrum serves as a React-based version of Adobe's Spectrum design system, offering a variety of components that adapt seamlessly to different interactions and screen sizes on various devices. Notably, it ensures full accessibility with support for screen readers and keyboard navigation, making it user-friendly for all. The components are crafted to accommodate mouse, touch, and keyboard inputs, adhering to responsive design principles to provide an optimal user experience across all devices. Furthermore, React Spectrum automatically adjusts to dark and light modes in alignment with the user's operating system settings. In addition to this, the framework supports more than 30 languages, which includes features for right-to-left languages, as well as date and number formatting. The extensive library of components encompasses buttons, pickers, collections, date and time inputs, color selection tools, forms, navigation elements, overlays, status indicators, and various content components. This wide-ranging set of tools ensures that developers can create accessible and versatile applications tailored to diverse user needs.

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
Activeeon ProActive
Amazon SageMaker Data Wrangler
ApertureDB
Cleanlab
Coiled
DagsHub
Dagster
Dash
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
React
TeamStation
ThinkData Works
Yandex Data Proc
skills.ai

Integrations

3LC
Activeeon ProActive
Amazon SageMaker Data Wrangler
ApertureDB
Cleanlab
Coiled
DagsHub
Dagster
Dash
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
React
TeamStation
ThinkData Works
Yandex Data Proc
skills.ai

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

Adobe

Founded

1982

Country

United States

Website

react-spectrum.adobe.com/react-spectrum/index.html

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

Alternatives

Alternatives

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