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Description
Dask is a freely available open-source library that is developed in collaboration with various community initiatives such as NumPy, pandas, and scikit-learn. It leverages the existing Python APIs and data structures, allowing users to seamlessly transition between NumPy, pandas, and scikit-learn and their Dask-enhanced versions. The schedulers in Dask are capable of scaling across extensive clusters with thousands of nodes, and its algorithms have been validated on some of the most powerful supercomputers globally. However, getting started doesn't require access to a large cluster; Dask includes schedulers tailored for personal computing environments. Many individuals currently utilize Dask to enhance computations on their laptops, taking advantage of multiple processing cores and utilizing disk space for additional storage. Furthermore, Dask provides lower-level APIs that enable the creation of customized systems for internal applications. This functionality is particularly beneficial for open-source innovators looking to parallelize their own software packages, as well as business executives aiming to scale their unique business strategies efficiently. In essence, Dask serves as a versatile tool that bridges the gap between simple local computations and complex distributed processing.
Description
Statsmodels is a Python library designed for the estimation of various statistical models, enabling users to perform statistical tests and explore data effectively. Each estimator comes with a comprehensive array of result statistics, which are validated against established statistical software to ensure accuracy. This package is distributed under the open-source Modified BSD (3-clause) license, promoting free use and modification. Users can specify models using R-style formulas or utilize pandas DataFrames for convenience. To discover available results, you can check dir(results), and you will find that attributes are detailed in results.__doc__, while methods include their own docstrings for further guidance. Additionally, numpy arrays can be employed as an alternative to formulas. For most users, the simplest way to install statsmodels is through the Anaconda distribution, which caters to data analysis and scientific computing across various platforms. Overall, statsmodels serves as a powerful tool for statisticians and data analysts alike.
API Access
Has API
API Access
Has API
Integrations
Anaconda
Coiled
Dagster
Domino Enterprise AI Platform
Flyte
Google Cloud Platform
Kedro
NVIDIA DIGITS
Prefect
Python
Integrations
Anaconda
Coiled
Dagster
Domino Enterprise AI Platform
Flyte
Google Cloud Platform
Kedro
NVIDIA DIGITS
Prefect
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Dask
Founded
2019
Website
dask.org
Vendor Details
Company Name
statsmodels
Website
www.statsmodels.org/stable/index.html
Product Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports