Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AG Grid is a robust and versatile JavaScript Data Grid library designed for efficiently displaying, managing, and interacting with extensive tabular datasets in contemporary web applications, providing essential functionalities like sorting, filtering, editing, grouping, aggregation, pivoting, pagination, and exceptional performance that can handle hundreds of thousands of rows with minimal resource usage. It is compatible with different frameworks, offering official support for popular platforms such as React, Angular, Vue, and vanilla JavaScript, all while preserving a unified API and avoiding third-party dependencies, which facilitates easy integration into existing projects and allows for extensive customization through user-defined components, theming, and modularity that grant precise control over both bundle size and features. Additionally, AG Grid offers a free open-source Community edition under the MIT license, which includes fundamental grid capabilities, alongside a commercial Enterprise edition that provides supplementary advanced functionalities that cater to more complex use cases. This flexibility makes AG Grid a preferred choice for developers looking to enhance user experience through dynamic data presentation.
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
Yes
API Access
Has API
Yes
Integrations
3LC
No
ApertureDB
No
Avanzai
No
CSS
Yes
Cleanlab
No
Codédex
No
Coiled
No
Daft
No
Dagster
No
Dash
No
Integrations
3LC
Yes
ApertureDB
Yes
Avanzai
Yes
CSS
No
Cleanlab
Yes
Codédex
Yes
Coiled
Yes
Daft
Yes
Dagster
Yes
Dash
Yes
Pricing Details
$999 per developer
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
No
Live Rep (24/7)
No
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
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
AG Grid
Founded
2015
Country
United States
Website
www.ag-grid.com
Vendor Details
Company Name
pandas
Founded
2008
Website
pandas.pydata.org
Product Features
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