Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • RaimaDB Reviews & Ratings
    4.8 out of 5 stars 12 Ratings
    Company Website for RaimaDB
  • SurveyJS Reviews & Ratings
    4.8 out of 5 stars 64 Ratings
    Company Website for SurveyJS
  • Google Cloud BigQuery Reviews & Ratings
    4.5 out of 5 stars 2,027 Ratings
    Company Website for Google Cloud BigQuery
  • Dragonfly Reviews & Ratings
    4.9 out of 5 stars 16 Ratings
    Company Website for Dragonfly
  • TIMi Reviews & Ratings
    4.9 out of 5 stars 68 Ratings
    Company Website for TIMi
  • DbVisualizer Reviews & Ratings
    4.8 out of 5 stars 593 Ratings
    Company Website for DbVisualizer
  • TinyPNG Reviews & Ratings
    4.7 out of 5 stars 72 Ratings
    Company Website for TinyPNG
  • Google Compute Engine Reviews & Ratings
    4.4 out of 5 stars 1,169 Ratings
    Company Website for Google Compute Engine
  • DocketManager Reviews & Ratings
    4.6 out of 5 stars 31 Ratings
  • NINJIO Reviews & Ratings
    4.8 out of 5 stars 416 Ratings
    Company Website for NINJIO

What is pandas?

Pandas is a versatile open-source library for data analysis and manipulation that excels in speed and power while maintaining a user-friendly interface within the Python ecosystem. It supports a wide range of data formats for both importing and exporting, such as CSV, text documents, Microsoft Excel, SQL databases, and the efficient HDF5 format. The library stands out with its intelligent data alignment features and its adept handling of missing values, allowing for seamless label-based alignment during calculations, which greatly aids in the organization of chaotic datasets. Moreover, pandas includes a sophisticated group-by engine that facilitates complex aggregation and transformation tasks, making it simple for users to execute split-apply-combine operations on their data. In addition to these capabilities, pandas is equipped with extensive time series functions that allow for the creation of date ranges, frequency conversions, and moving window statistics, as well as managing date shifting and lagging. Users also have the flexibility to define custom time offsets for specific applications and merge time series data without losing any critical information. Ultimately, the comprehensive array of features offered by pandas solidifies its status as an indispensable resource for data professionals utilizing Python, ensuring they can efficiently handle a diverse range of data-related tasks.

What is Oracle Data Access Components (ODAC)?

Oracle Data Access Components (ODAC) represent a comprehensive suite of tools and drivers tailored for Windows and .NET ecosystems. This collection not only streamlines access to data within .NET but also incorporates Microsoft Visual Studio tools, enabling the development of applications that connect with Oracle databases, including support for ASP.NET providers. ODAC provides extensive client support and optimizes advanced capabilities of Oracle databases, enhancing performance, ensuring high availability, and implementing stringent security protocols. Furthermore, it integrates smoothly with Visual Studio, creating an efficient and cohesive development experience for programmers. The Oracle Data Provider for .NET complies with Microsoft’s ADO.NET interface, allowing for easy access to Oracle databases. Additionally, the OLAP Data Manipulation Language (OLAP DML) empowers users to effectively define and manage objects in analytic workspaces. With a commitment to high performance, ODAC delivers a rich array of data access mechanisms via Microsoft ADO and OLE DB, as well as crucial information on installation, configuration after installation, and operational guidelines to help users maximize its capabilities. Overall, ODAC stands out as a robust solution for developers engaged in Oracle database projects within the .NET framework, making it an indispensable tool in their toolkit. This versatility makes it suitable for a wide range of applications, from simple data retrieval to complex enterprise-level solutions.

Media

Media

Integrations Supported

3LC
Amazon SageMaker Data Wrangler
Cleanlab
DagsHub
Dagster
Dash
Flyte
GLM-5.2
GLM-5.3
LanceDB
OrcaSheets
Sliq
Spyder
Train in Data
Union Pandera

Integrations Supported

.NET
ASP.NET
Oracle Database

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

pandas

Date Founded

2008

Company Website

pandas.pydata.org

Company Facts

Organization Name

Oracle

Company Location

United States

Company Website

docs.oracle.com/en/database/oracle/oracle-data-access-components/

Categories and Features

Component Libraries

Not specified

Data Analysis

Not specified

Categories and Features

Component Libraries

Not specified

Popular Alternatives

ML.NET Reviews & Ratings

ML.NET

Microsoft

Popular Alternatives