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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Developed and continuously improved by a dedicated team of professionals specializing in differential privacy, this system is actively utilized by organizations such as the U.S. Census Bureau. It operates on the Spark framework, seamlessly handling input tables with billions of entries. The platform offers an extensive and expanding array of aggregation functions, data transformation operations, and privacy frameworks. Users can execute public and private joins, apply filters, or utilize custom functions on their datasets. It enables the computation of counts, sums, quantiles, and more under various privacy models, ensuring that differential privacy is accessible through straightforward tutorials and comprehensive documentation. Tumult Analytics is constructed on our advanced privacy architecture, Tumult Core, which regulates access to confidential data, ensuring that every program and application inherently includes a proof of privacy. The system is designed by integrating small, easily scrutinized components, ensuring a high level of safety through proven stability tracking and floating-point operations. Furthermore, it employs a flexible framework grounded in peer-reviewed academic research, guaranteeing that users can trust the integrity and security of their data handling processes. This commitment to transparency and security sets a new standard in the field of data privacy.

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 
Amazon SageMaker Data Wrangler No 
ApertureDB No 
Codédex No 
Daft No 
DagsHub No 
Dash No 
Flower No 
GLM-5.2 No 
Kedro No 
LanceDB No 
OrcaSheets No 
RunCode No 
SPARK Yes 
Sliq No 
Spyder No 
Train in Data No 
Union Pandera No 
Yandex Data Proc No 

Integrations

3LC Yes 
Amazon SageMaker Data Wrangler Yes 
ApertureDB Yes 
Codédex Yes 
Daft Yes 
DagsHub Yes 
Dash Yes 
Flower Yes 
GLM-5.2 Yes 
Kedro Yes 
LanceDB Yes 
OrcaSheets Yes 
RunCode Yes 
SPARK No 
Sliq Yes 
Spyder Yes 
Train in Data Yes 
Union Pandera Yes 
Yandex Data Proc Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

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 No 
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 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

Tumult Analytics

Founded

2019

Country

United States

Website

www.tmlt.dev/

Vendor Details

Company Name

pandas

Founded

2008

Website

pandas.pydata.org

Product Features

Data Privacy Management

Access Control No 
CCPA Compliance No 
Consent Management No 
Data Mapping No 
GDPR Compliance No 
Incident Management No 
PIA / DPIA No 
Policy Management No 
Risk Management No 
Sensitive Data Identification 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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