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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Introducing a user-friendly yet robust suite designed for accessing, manipulating, analyzing, and showcasing data, now offered for both cloud-based and on-premises solutions. Why struggle with disparate software tools from various providers? A unified collection that features three of our most sought-after products—Base SAS, SAS/STAT, and SAS/GRAPH—minimizes expenses related to licensing, maintenance, training, and support, all while ensuring uniform access to information throughout your organization. Our SAS statistical methods are regularly updated to incorporate the latest developments in statistical science. Additionally, our technical support team consists of seasoned statisticians with master's and doctorate degrees, providing a level of expertise and service that is rare among software vendors. With over forty years of experience in crafting statistical analysis tools, SAS continues to be the trusted choice for organizations globally seeking reliable solutions for their data inquiries. This commitment to excellence ensures that you are well-equipped to make informed decisions based on accurate data insights.

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 
ApertureDB No 
CodeConvert Yes 
Kedro No 
Microsoft PowerPoint Yes 
ModelOp Yes 
Netdata No 
OpenAccess SDK Yes 
Openbridge Yes 
SAS Viya Yes 
ShareCRF Yes 
SmartScrapers Yes 
Spyder No 
TeamStation No 
Union Pandera No 
Vast Edge ODR Yes 
skills.ai No 
xtype Yes 

Integrations

3LC Yes 
ApertureDB Yes 
CodeConvert No 
Kedro Yes 
Microsoft PowerPoint No 
ModelOp No 
Netdata Yes 
OpenAccess SDK No 
Openbridge No 
SAS Viya No 
ShareCRF No 
SmartScrapers No 
Spyder Yes 
TeamStation Yes 
Union Pandera Yes 
Vast Edge ODR No 
skills.ai Yes 
xtype No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

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 Yes 
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 Yes 

Types of Training

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

Vendor Details

Company Name

SAS

Country

United States

Website

www.sas.com/en_us/software/analytics-pro.html

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 

Data Visualization

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

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 

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