Average Ratings 3 Ratings

Total
ease
features
design
support

Average Ratings 0 Ratings

Total
ease
features
design
support

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Description

Unlock the full potential of your enterprise's time-series data with the dataPARC Historian. This solution elevates data management, facilitating smooth and secure data flow across your organization. Its design ensures easy integration with AI, ML, and cloud technologies, paving the way for innovative adaptability and deeper insights. Rapid access to data, advanced manufacturing intelligence, and scalability make dataPARC Historian the optimal choice for businesses striving for excellence in their operations. It's not just about storing data; it's about transforming data into actionable insights with speed and precision. The dataPARC Historian stands out as more than just a repository for data. It empowers enterprises with the agility to use time-series data more effectively, ensuring decisions are informed and impactful, backed by a platform known for its reliability and ease of use.

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

AVEVA PI System
Amazon SageMaker Data Wrangler
ApertureDB
Braincube
Coiled
Daft
Flower
Flyte
Ignition SCADA
Kedro
Proficy Smart Factory MES
RunCode
Seeq
Spyder
TeamStation
TrendMiner
Union Pandera
Uptake
skills.ai

Integrations

AVEVA PI System
Amazon SageMaker Data Wrangler
ApertureDB
Braincube
Coiled
Daft
Flower
Flyte
Ignition SCADA
Kedro
Proficy Smart Factory MES
RunCode
Seeq
Spyder
TeamStation
TrendMiner
Union Pandera
Uptake
skills.ai

Pricing Details

No price information available.
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

dataPARC

Founded

1997

Country

United States

Website

www.dataparc.com

Vendor Details

Company Name

pandas

Founded

2008

Website

pandas.pydata.org

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Industrial IoT

Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Manufacturing

Accounting Integration
ERP
MES
MRP
Maintenance Management
Purchase Order Management
Quality Management
Quotes/Estimates
Reporting/Analytics
Safety Management
Shipping Management

OEE

Benchmarking
Cost Tracking
Downtime Tracking
Historical Reporting
Performance Metrics
Quality Control
Real Time Reporting
Root Cause Analysis
Trend Analysis
Work Order Management

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

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Alternatives

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