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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 IMSL?

Enhance your efficiency and cut down on development time with the IMSL numerical libraries. By utilizing IMSL's array of build tools, you can effectively achieve your strategic objectives. The IMSL library facilitates a range of functionalities, including modeling regression, building decision trees, developing neural networks, and forecasting time series data. The IMSL C Numerical Library has a longstanding reputation for reliability, having been extensively tested over decades in multiple industries, providing businesses with a solid, high-yield solution for crafting advanced analytical tools. This library empowers teams to swiftly integrate intricate features into their analytical applications, which encompass everything from data mining and forecasting to complex statistical analyses. In addition, the IMSL C library streamlines both integration and deployment, ensuring seamless transitions and compatibility with various popular platforms, all while avoiding the need for extra infrastructure for database or application embedding. By adopting IMSL libraries, organizations not only bolster their analytical prowess but also ensure they stay ahead in a rapidly changing market landscape. Additionally, the ongoing support and updates offered by IMSL further enhance its value proposition for businesses seeking to innovate and excel.

Media

Media

Integrations Supported

3LC
Amazon SageMaker Data Wrangler
ApertureDB
Avanzai
Coiled
DagsHub
Dash
GLM-5.2
Kedro
LanceDB
MLJAR Studio
Netdata
OrcaSheets
Sliq
ThinkData Works

Integrations Supported

C
C#
Java
Python

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

pandas

Date Founded

2008

Company Website

pandas.pydata.org

Company Facts

Organization Name

Perforce

Company Location

United States

Company Website

www.imsl.com

Categories and Features

Component Libraries

Not specified

Data Analysis

Not specified

Categories and Features

Component Libraries

Not specified

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