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Description

Seaborn is a versatile data visualization library for Python that builds upon matplotlib. It offers a user-friendly interface for creating visually appealing and insightful statistical graphics. To gain a foundational understanding of the library's concepts, you can explore the introductory notes or relevant academic papers. For installation instructions, check out the dedicated page that guides you on how to download and set up the package. You can also explore the example gallery to discover various visualizations you can create with Seaborn, and further your knowledge by diving into the tutorials or API reference for detailed guidance. If you wish to examine the source code or report any issues, the GitHub repository is the place to go. Additionally, for general inquiries and community support, StackOverflow features a specific section for Seaborn discussions. Engaging with these resources will enhance your ability to effectively use the library.

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

3LC
Activeeon ProActive
Cleanlab
Daft
DagsHub
Dagster
Flower
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
Python
Spyder
TeamStation
ThinkData Works
Union Pandera
Yandex Data Proc

Integrations

3LC
Activeeon ProActive
Cleanlab
Daft
DagsHub
Dagster
Flower
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
Netdata
Python
Spyder
TeamStation
ThinkData Works
Union Pandera
Yandex Data Proc

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

Seaborn

Website

seaborn.pydata.org

Vendor Details

Company Name

pandas

Founded

2008

Website

pandas.pydata.org

Product Features

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

Alternatives

Alternatives

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