---
title: statsmodels Reviews
meta_title: 'statsmodels Reviews 2026: Details, Pricing, & Features | G2'
meta_description: Filter reviews by the users' company size, role or industry to find
  out how statsmodels works for a business like yours.
aggregate_rating:
  rating_value: 4.5
  review_count: 3
  scale: '5'
date_modified: '2025-10-31'
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---


# statsmodels Reviews
**Vendor:** statsmodels  
**Category:** [Component Libraries Software](https://www.g2.com/categories/component-libraries)  
**Average Rating:** 4.5/5.0  
**Total Reviews:** 3
## About statsmodels
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available




## statsmodels Reviews
  ### 1. Statsmodels

**Rating:** 4.0/5.0 stars

**Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.)

**Reviewed Date:** February 06, 2019

**What do you like best about statsmodels?**

A comprehensive collection of advanced or special-use statistical and regression functions. Having access to models and statistical tests related to those models in the same package is very handy. Additionally, for regression models such as ARMA/ARIMA/ARIMAX/SARIMAX, the output already contains a lot of relevant information like AIC and BIC score.

**What do you dislike about statsmodels?**

Output type is inconsistent and can be a hurdle at times. For example some methods will output a list, others a dictionary, etc, which can make using a statsmodels output as an input somewhere else a little tricky. Documentation is also inconsistent.

**Recommendations to others considering statsmodels:**

Just be aware that outputs from very similar functions aren't necessarily consistent with one another. Some processing is often necessary for use with more standard libraries numpy, pandas, etc.

**What problems is statsmodels solving and how is that benefiting you?**

I primarily use statsmodels for time series analysis and regression modeling. Having tests such as augmented dickey-fuller and ACF/PACF functions built in are very useful when prepping data for an ARIMA model.



- [View statsmodels pricing details and edition comparison](https://www.g2.com/products/statsmodels/reviews?filters%5Bnps_score%5D%5B%5D=4&section=pricing&secure%5Bexpires_at%5D=2026-08-12+14%3A01%3A15+-0500&secure%5Bsession_id%5D=b57ef0fe-d01f-42ee-a21a-f156452922c2&secure%5Btoken%5D=9008854817645a4fe3b43d1770bb3ee0159184d8522d329a33448665b6e87b15&format=llm_user)

## statsmodels Features
**Functionality**
- Language Contingency
- Component Library
- Unlocked Components

**Management**
- Framework Integration
- Repository Management
- Support

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