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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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Activeeon ProActive
COZYROC SSIS+ Suite
Coiled
Dagster
Dash
Flower
JMP Statistical Software
LanceDB
Modelscape
Netdata
OpenAccess SDK
RunCode
SAS Viya
ShareCRF
Spyder
ThinkData Works
Union Pandera
Yandex Data Proc
xtype

Integrations

Activeeon ProActive
COZYROC SSIS+ Suite
Coiled
Dagster
Dash
Flower
JMP Statistical Software
LanceDB
Modelscape
Netdata
OpenAccess SDK
RunCode
SAS Viya
ShareCRF
Spyder
ThinkData Works
Union Pandera
Yandex Data Proc
xtype

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

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
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

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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