Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Polymer library offers a robust set of functionalities for developing custom elements, streamlining the process to ensure they behave like standard DOM elements. Just like conventional DOM elements, Polymer elements can be created through a constructor or by utilizing document creation methods, and they can be configured via attributes or properties. Each instance can contain an internal DOM, adapt to changes in properties and attributes, and receive styling both from internal defaults and external sources, all while responding to methods that alter their internal state. When you register a custom element, you link a class to a specific custom element name, and the element includes lifecycle callbacks to effectively manage its various stages. Additionally, Polymer facilitates property declarations, allowing for seamless integration of your element's property API with the Polymer data system. By employing Shadow DOM, your element gains a locally scoped and encapsulated DOM tree, and Polymer can automatically generate and fill a shadow tree for your element derived from a DOM template, enhancing the modularity and reusability of your code. This combination of features not only simplifies the creation of custom elements but also ensures they integrate smoothly into the wider ecosystem of web components.
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
Amazon SageMaker Data Wrangler
No
ApertureDB
No
Carbide
Yes
Cleanlab
No
Dash
No
Flower
No
Flyte
No
GLM-5.2
No
Gerrit Code Review
Yes
MLJAR Studio
No
Integrations
Amazon SageMaker Data Wrangler
Yes
ApertureDB
Yes
Carbide
No
Cleanlab
Yes
Dash
Yes
Flower
Yes
Flyte
Yes
GLM-5.2
Yes
Gerrit Code Review
No
MLJAR Studio
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
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
Yes
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)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Polymer
Founded
2014
Country
United States
Website
polymer-library.polymer-project.org/3.0/docs/devguide/feature-overview
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