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Description

Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.

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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

3LC Yes 
Anaconda No 
Avanzai Yes 
Codédex Yes 
Coiled Yes 
Cython Yes 
Dash Yes 
Flower Yes 
Gensim Yes 
JAX Yes 
MPI for Python (mpi4py) Yes 
NVIDIA FLARE Yes 
PaizaCloud Yes 
Python No 
Spyder Yes 
Train in Data Yes 
Unify AI Yes 
Visual Studio Code Yes 
h5py Yes 
imageio Yes 

Integrations

3LC No 
Anaconda Yes 
Avanzai No 
Codédex No 
Coiled No 
Cython No 
Dash No 
Flower No 
Gensim No 
JAX No 
MPI for Python (mpi4py) No 
NVIDIA FLARE No 
PaizaCloud No 
Python Yes 
Spyder No 
Train in Data No 
Unify AI No 
Visual Studio Code No 
h5py No 
imageio No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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

NumPy

Website

numpy.org

Vendor Details

Company Name

statsmodels

Website

www.statsmodels.org/stable/index.html

Product Features

Product Features

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