Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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 

Screenshots View All

Screenshots View All

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 
Netdata No 
Sliq No 
Spyder No 
TeamStation No 
ThinkData Works No 
Train in Data No 
Union Pandera No 
Yandex Data Proc No 
skills.ai 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 
Netdata Yes 
Sliq Yes 
Spyder Yes 
TeamStation Yes 
ThinkData Works Yes 
Train in Data Yes 
Union Pandera Yes 
Yandex Data Proc Yes 
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 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

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

Polymer Reviews

Polymer

Polymer Search
ML.NET Reviews

ML.NET

Microsoft
Polymer Reviews

Polymer

Inflow Hiring
GENOA 3DP Reviews

GENOA 3DP

AlphaSTAR
Polymer Reviews

Polymer

Polymer Data Security