GuideChimp vs. Matplotlib vs. statsmodels vs. zope.interface Comparison Chart

GuideChimp can be seamlessly integrated with any web app and ready to drop into your application using React, Vue.js, Angular, ES Modules, or plain JavaScript and HTML. GuideChimp works well with tools you already use and can be easily customized through SCSS and clean CSS to look like an integral part of your product. GuideChimp is extendable using out-of-the-box and third-party plugins, which enhance functionality with usability, feedback, analytics, etc. tools. GuideChimp is well documented and the open-source library is easy to integrate and have a very short learning curve. GuideChimp is simple and robust enough to provide results with minimal effort! Set up it in just 3 minutes! Let GuideChimp look like an integral part of your software product by configuring its look & feel. Raise visitors attention by adding a beacon to any element on the web page.

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 is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.