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

DataMelt, or "DMelt", is an environment for numeric computations, data analysis, data mining and computational statistics. DataMelt allows you to plot functions and data in 2D or 3D, perform statistical testing, data mining, data analysis, numeric computations and function minimization. It also solves systems of linear and differential equations. There are also options for symbolic, non-linear, and linear regression. Java API integrates neural networks and data-manipulation techniques using various data-manipulation algorithms. Support is provided for elements of symbolic computations using Octave/Matlab programming. DataMelt provides a Java platform-based computational environment. It can be used on different operating systems and programming languages. It is not limited to one programming language, unlike other statistical programs. This software combines Java, the most widely used enterprise language in the world, with the most popular data science scripting languages, Jython (Python), Groovy and JRuby.

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

3LC No 
Cleanlab No 
Coiled No 
DagsHub No 
Dagster No 
Dash No 
Eclipse BIRT Yes 
Flower No 
GLM-5.1 No 
GLM-5.2 No 
Kedro No 
LanceDB No 
Netdata No 
Sliq No 
Spyder No 
ThinkData Works No 
Yandex Data Proc No 
skills.ai No 

Integrations

3LC Yes 
Cleanlab Yes 
Coiled Yes 
DagsHub Yes 
Dagster Yes 
Dash Yes 
Eclipse BIRT No 
Flower Yes 
GLM-5.1 Yes 
GLM-5.2 Yes 
Kedro Yes 
LanceDB Yes 
Netdata Yes 
Sliq Yes 
Spyder Yes 
ThinkData Works Yes 
Yandex Data Proc Yes 
skills.ai Yes 

Pricing Details

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
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 Yes 
Live Rep (24/7) No 
Online Support No 

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 Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

jWork.ORG

Founded

2005

Country

United States

Website

datamelt.org

Vendor Details

Company Name

pandas

Founded

2008

Website

pandas.pydata.org

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare Yes 
For Sales No 
For eCommerce No 
Image Recognition Yes 
Machine Learning Yes 
Multi-Language No 
Natural Language Processing Yes 
Predictive Analytics Yes 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Data Analysis

Data Discovery Yes 
Data Visualization Yes 
High Volume Processing No 
Predictive Analytics Yes 
Regression Analysis Yes 
Sentiment Analysis No 
Statistical Modeling Yes 
Text Analytics Yes 

Data Mining

Data Extraction Yes 
Data Visualization Yes 
Fraud Detection No 
Linked Data Management No 
Machine Learning Yes 
Predictive Modeling Yes 
Semantic Search No 
Statistical Analysis Yes 
Text Mining Yes 

Data Visualization

Analytics Yes 
Content Management No 
Dashboard Creation No 
Filtered Views No 
OLAP No 
Relational Display No 
Simulation Models Yes 
Visual Discovery Yes 

Deep Learning

Convolutional Neural Networks Yes 
Document Classification Yes 
Image Segmentation No 
ML Algorithm Library Yes 
Model Training Yes 
Neural Network Modeling No 
Self-Learning Yes 
Visualization Yes 

Statistical Analysis

Analytics Yes 
Association Discovery Yes 
Compliance Tracking Yes 
File Management Yes 
File Storage Yes 
Forecasting Yes 
Multivariate Analysis Yes 
Regression Analysis Yes 
Statistical Process Control No 
Statistical Simulation Yes 
Survival Analysis Yes 
Time Series Yes 
Visualization Yes 

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

ML.NET Reviews

ML.NET

Microsoft
JMP Statistical Software Reviews

JMP Statistical Software

JMP Statistical Discovery
Statistix Reviews

Statistix

Analytical Software