explanationin the first example " +zand " +yare evaluated first since they are inside the parenthesis and are then multiplied to each other hencethe result is * in the second examplesincemultiplication has higher precedence than additionhence multiplication of and is done first and then added to hencethe result is + similarlyin the last case since relational operators have higher precedence than logicalhence " >zand " <zare evaluated first and then "oroperator is used since > is true and < is falsehence "oroperator used on true and false returns true libraries in python python has rich collection of functions that comes along with python software besidespython has an extensive list of functions which are accessible only when the user imports the required library python library is collection of functions and sub packages functions related to one domain are grouped inside library and when the user wantsa particular library can be accessed using import statement in python there are thousands of libraries for pythonwritten by many authors some of these libraries implement specialized statistical methodsothers give access to arraysand others are designed to create visualization effects etc the user can import the respective libraries in the programdepending on the requirement to access particular functions some of the common libraries include numpythe most fundamental library around which the scientific computation stack is built is numpy (numerical pythonit provides an abundance of useful features for largemulti-dimensional arrays and matricesalong with large library of high-level mathematical functions to operate on these arrays pandasa python library designed to work with labeled and relational data is pandas it designed for quick and easy data manipulationaggregationand visualization the pandas is spreadsheets for python and it is able to describe the data efficiently it can do grouping and pivot tables on larger data than most spreadsheet programs matplotliba python library that is tailored for creating simple and powerful visualizations with ease is matplotlib line plotsscatter plotsbar charts and histogramspie chartsstem plotscontour plotsquiver plotsspectrograms etc different formatting styles like titlelabelsgridslegends etc are also available in this library seabornthe seaborn library is mostly focused on the visualization of statistical modelssuch visualizations include heat maps and those that summarize data but still depict overall distributions scipythe scipy contains modules for linear algebraoptimizationintegrationand statistics it provides efficient numerical routines as numerical integrationoptimizationand many others via its specific sub modules it adds significant power to the interactive python session by providing the user with high-level commands and classes for manipulating data nltkthe name of this suite of libraries stands for natural language toolkit andas the name impliesit used for common tasks associated with symbolic and statistical natural language processing the functionality of nltk allows lot of operations such as text taggingclassificationand tokenizingname entities identification