parsel vs. React Toolbox vs. Scrapy vs. statsmodels Comparison Chart

Bootstrap your application with beautiful Material Design components. React Toolbox is a set of React components that implements Google Material Design specification. It's built on top of some of the trendiest proposals like CSS Modules (written in SASS), Webpack, and ES6. The library harmoniously integrates with your Webpack workflow and it's easily customizable and very flexible. Check our awesome documentation (which is built using React Toolbox) and try all the components with live examples. We've created a playground so you don't need to install anything to fall in love with our components, so fun! The app bar is a special kind of toolbar that’s used for branding, navigation, search, and actions. Usually, it contains controls on the right and left side and a title with the current section or app name. You should give the content with children elements. Consists of text, an image, or both, designed in accordance with your app’s color theme.

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.