textblobthis is another python library that promises simplified text processing it provides simple api for doing common text processing tasks including parts of speech taggingtokenizationphrase extractionsentiment analysisclassificationtranslationand much morespacythis is recent addition to the python text processing landscape but an excellent and robust framework nonetheless the focus of spacy is industrial strength natural language processingso it targets efficient text analytics for largescale corpora it achieves this efficiency by leveraging carefully memory-managed operations in cython we recommend using spacy for natural language processing and you will also see it being used extensively for our text normalization process in statsmodels statsmodels is library for statistical and econometric analysis in python the advantage of languages like is that it' statistically focused language with lot of capabilities it consists of easy-to-use yet powerful models that can be used for statistical analysis and modeling however from deploymentintegrationand performance aspectsdata scientists and engineers often prefer python but it doesn' have the power of easy-to-use statistical functions and libraries like the statsmodels library aims to bridge this gap for python users it provides the capabilities for statisticalfinancial and econometric operations with the aim of combining the advantages of python with the statistical powers of languages like hence users familiar with rsasstataspssand so on who might want similar functionality in python can use statsmodels the initial statsmodel package was developed by jonathan taylora statistician at stanfordas part of scipy under the name models improving this codebase was then accepted as scipy-focused project for the google summer of code in and again in the current package is available as scikit or an addon package for scipy we recommend you to check out the paper by seaboldskipperand josef perktold"statsmodelseconometric and statistical modeling with python,proceedings of the th python in science conference installation the package can be installed using pip or conda install and the following commands pip install statsmodels conda install - conda-forge statsmodels modules in this sectionwe briefly cover the important modules that comprise the statsmodel package and the capability those models provides this should give you enough idea of what to leverage to build statistical models and perform statistical analysis and inference distributions one of the central ideas in statistics is the distributions of statistical datasets distributions are listing or function that assigns probability value to all the possible values of the data the distributions module of the statsmodels package implements some important functions related to statistical distribution including sampling from the distributiontransformations of distributionsgenerating cumulative distribution functions of important distributionsand so on