Job ready Python

Job ready Python

Get ready to take on Python with a practical and job-focused guide Job Ready Python offers readers a straightforward and elegant approach to learning Python that emphasizes hands-on and employable skills you can apply to real-world environments immediately. Based on the renowned mthree Global Academ...

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Detalles Bibliográficos
Otros Autores: Balti, Haythem, author (author), Weiss, Kimberly A., author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley [2022]
Colección:Mthree tech skills series.
Materias:
Python (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009645693106719
Tabla de Contenidos:
  • Intro
  • Table of Contents
  • Title Page
  • Introduction
  • WHAT DOES THIS BOOK COVER?
  • READER SUPPORT FOR THIS BOOK
  • PART I: Getting Started with Python
  • Lesson 1: Setting Up a Python Programming Environment
  • PYTHON OVERVIEW
  • USING REPLIT ONLINE
  • GETTING STARTED WITH JUPYTER NOTEBOOK
  • A QUICK LOOK AT VISUAL STUDIO CODE
  • USING PYTHON FROM THE COMMAND LINE
  • SUMMARY
  • EXERCISES
  • Lesson 2: Understanding Programming Basics
  • THE FUTURE OF COMPUTER PROGRAMMING
  • PROGRAMMING LANGUAGES
  • DATA TYPES AND VARIABLES
  • SUMMARY
  • EXERCISES
  • Lesson 3: Exploring Basic Python Syntax
  • USING WITH SINGLE-LINE COMMANDS
  • USING SEMICOLONS
  • CONTINUING WITH BACKSLASH
  • WORKING WITH CASE STRUCTURE
  • ADDING COMMENTS
  • USING THE INPUT FUNCTION
  • STORING INPUT
  • UNDERSTANDING VARIABLE TYPES
  • DISPLAYING VARIABLE VALUES
  • NAMING VARIABLES
  • SUMMARY
  • EXERCISES
  • Lesson 4: Working with Basic Python Data Types
  • REVIEW OF DATA TYPES
  • NUMBER DATA TYPES
  • IDENTIFYING DATA TYPES
  • MATHEMATICAL OPERATIONS
  • PEMDAS
  • COMMON MATH FUNCTIONS
  • MATH LIBRARY FUNCTIONS
  • USING NUMBERS WITH USER INPUT
  • BOOLEAN TYPES AND BOOLEAN OPERATIONS
  • LOGIC OPERATIONS
  • COMPARATIVE OPERATORS
  • SUMMARY
  • EXERCISES
  • Lesson 5: Using Python Control Statements
  • CONTROL STRUCTURES REVIEW
  • UNDERSTANDING SEQUENCE CONTROL STRUCTURE
  • UNDERSTANDING SELECTION STATEMENTS
  • UNDERSTANDING CONDITIONAL STATEMENTS
  • IF-ELSE STATEMENTS
  • WORKING WITH NESTED CONDITIONS
  • EMBEDDING CONDITIONS
  • SUMMARY
  • EXERCISES
  • Lesson 6: Pulling It All Together: Income Tax Calculator
  • GETTING STARTED
  • STEP 1: GATHER REQUIREMENTS
  • STEP 2: DESIGN THE PROGRAM
  • STEP 3: CREATE THE INPUTS
  • STEP 4: CALCULATE THE TAXABLE INCOME
  • STEP 5: CALCULATE THE TAX RATE
  • STEP 6: UPDATE THE APPLICATION
  • STEP 7: ADDRESS THE UI
  • ON YOUR OWN
  • SUMMARY.
  • PART II: Loops and Data Structures
  • Lesson 7: Controlling Program Flow with Loops
  • ITERATIONS OVERVIEW
  • THE ANATOMY OF A LOOP
  • THE FOR LOOP
  • THE WHILE LOOP
  • FOR VS. WHILE LOOPS
  • STRINGS AND STRING OPERATIONS
  • ITERATING THROUGH STRINGS
  • SUMMARY
  • EXERCISES
  • Lesson 8: Understanding Basic Data Structures: Lists
  • DATA STRUCTURE OVERVIEW-PART 1
  • CREATING LISTS
  • DETERMINING LIST LENGTH
  • WORKING WITH LIST INDEXES
  • NEGATIVE INDEXING IN LISTS
  • SLICING LISTS
  • ADDING ITEMS TO A LIST
  • INSERTING LIST ITEMS
  • REMOVING LIST ITEMS
  • CONCATENATING LISTS
  • LIST COMPREHENSION
  • SORTING LISTS
  • COPYING LISTS
  • SUMMARY
  • EXERCISES
  • Lesson 9: Understanding Basic Data Structures: Tuples
  • TUPLES AND TUPLE OPERATIONS
  • TUPLE INDEX VALUES
  • NEGATIVE INDEXING IN TUPLES
  • SLICING TUPLES
  • IMMUTABILITY
  • CONCATENATING TUPLES
  • SEARCHING TUPLES
  • SUMMARY
  • EXERCISES
  • Lesson 10: Diving Deeper into Data Structures: Dictionaries
  • DATA STRUCTURE OVERVIEW-PART 2
  • GETTING STARTED WITH DICTIONARIES
  • GENERATING A DICTIONARY
  • RETRIEVING ITEMS FROM A DICTIONARY
  • USING THE KEYS() METHOD
  • USING THE ITEMS() METHOD
  • REVIEWING THE KEYS(), VALUES(), AND ITEMS() METHODS
  • USING THE GET() METHOD
  • USING THE POP() METHOD
  • WORKING WITH THE IN OPERATOR
  • UPDATING A DICTIONARY
  • DUPLICATING A DICTIONARY
  • CLEARING A DICTIONARY
  • SUMMARY
  • EXERCISES
  • Lesson 11: Diving Deeper into Data Structures: Sets
  • SETS
  • RETRIEVING ITEMS FROM A SET
  • ADDING ITEMS TO A SET
  • CREATING AN EMPTY SET
  • UNDERSTANDING SET UNIQUENESS
  • SEARCHING ITEMS IN A SET
  • CALCULATING THE LENGTH OF A SET
  • DELETING ITEMS FROM A SET
  • CLEARING A SET
  • POPPING ITEMS IN A SET
  • DELETING A SET
  • DETERMINING THE DIFFERENCE BETWEEN SETS
  • INTERSECTING SETS
  • COMBINING SETS
  • SUMMARY
  • EXERCISES.
  • Lesson 12: Pulling It All Together: Prompting for an Address
  • STEP 1: GETTING STARTED
  • STEP 2: ACCEPT USER INPUT
  • STEP 3: DISPLAY THE INPUT VALUE
  • STEP 4: MODIFY THE OUTPUT
  • STEP 5: SPLIT A TEXT VALUE
  • STEP 6: DISPLAY ONLY THE HOUSE NUMBER
  • STEP 7: DISPLAY THE STREET NAME
  • STEP 8: ADD THE PERIOD
  • SUMMARY
  • Lesson 13: Organizing with Functions
  • FUNCTIONS OVERVIEW
  • DEFINING FUNCTIONS IN PYTHON
  • FUNCTION SYNTAX
  • DEFAULT INPUT VALUES
  • PARAMETER SYNTAX
  • ARBITRARY ARGUMENTS
  • KEYWORD ARGUMENTS
  • ARBITRARY KEYWORD ARGUMENTS
  • SUMMARY
  • EXERCISES
  • PART III: Object-Oriented Programming in Python
  • Lesson 14: Incorporating Object-Oriented Programming
  • OBJECT-ORIENTED PROGRAMMING OVERVIEW
  • DEFINING CLASSES
  • CREATING OBJECTS
  • WORKING WITH METHODS
  • CLASS ATTRIBUTES
  • SUMMARY
  • EXERCISES
  • Lesson 15: Including Inheritance
  • UNDERSTANDING INHERITANCE
  • CREATING A PARENT CLASS
  • CREATING A CHILD CLASS
  • INHERITING AT MULTIPLE LEVELS
  • OVERRIDING METHODS
  • SUMMARY
  • EXERCISES
  • Lesson 16: Pulling It All Together: Building a Burger Shop
  • REQUIREMENTS FOR OUR APPLICATION
  • PLAN THE CODE
  • CREATE THE CLASSES
  • CREATE THE FOOD ITEM CLASS
  • CREATE THE MAIN FILE
  • DISPLAY THE OUTPUT
  • TIE THE CODE FILES TOGETHER
  • SUMMARY
  • PART IV: Data Processing with Python
  • Lesson 17: Working with Dates and Times
  • GETTING STARTED WITH DATES AND TIMES
  • GETTING THE CURRENT DATE AND TIME
  • SPLITTING A DATE STRING
  • USING DATETIME ATTRIBUTES
  • CREATING CUSTOM DATETIME OBJECTS
  • COMPARE DATETIME VALUES
  • WORKING WITH UTC FORMAT
  • APPLYING TIMESTAMPS
  • ARITHMETIC AND DATES
  • CALCULATING THE DIFFERENCE IN DAYS
  • USING DATE WITHOUT TIME
  • USING TIME WITHOUT DATE
  • SUMMARY
  • EXERCISES
  • Lesson 18: Processing Text Files
  • FILE PROCESSING OVERVIEW
  • INTRODUCTION TO FILE INPUT/OUTPUT
  • PROCESSING TEXT FILES.
  • OPENING A FILE
  • READING TEXT FROM A FILE
  • ADD CONTENT TO A FILE
  • OVERWRITING THE CONTENTS OF A FILE
  • CREATING A NEW FILE
  • USING THE OS MODULE
  • DELETING A FILE
  • SUMMARY
  • EXERCISES
  • Lesson 19: Processing CSV Files
  • READING CSV FILES
  • USING THE DICTREADER CLASS
  • CREATING A DATASET LIST
  • USING WRITEROW()
  • APPENDING DATA
  • WRITING ROWS AS LISTS
  • WRITING ROWS FROM DICTIONARIES
  • SUMMARY
  • EXERCISES
  • Lesson 20: Processing JSON Files
  • PROCESSING JSON FILES
  • CREATING A JSON FILE WITH DUMP()
  • CONVERTING TO JSON WITH DUMPS()
  • FORMATTING JSON DATA
  • USING JSON.LOADS()
  • ITERATING THROUGH JSON DATA
  • READING AND WRITING JSON DATA
  • SUMMARY
  • EXERCISES
  • PART V: Data Analysis and Exception Handling
  • Lesson 21: Using Lambdas
  • CREATING A LAMBDA FUNCTION
  • WORKING WITH MULTIPLE INPUTS
  • PLACING LAMBDA FUNCTIONS INSIDE A FUNCTION
  • USING THE MAP() FUNCTION
  • COMBINING MAP AND LAMBDA FUNCTIONS
  • USING THE FILTER() FUNCTION
  • COMBINING A FILTER AND A LAMBDA
  • USING THE REDUCE() FUNCTION
  • SUMMARY
  • EXERCISES
  • Lesson 22: Handling Exceptions
  • BUILT-IN EXCEPTIONS
  • WORKING WITH TRY AND EXCEPT
  • WORKING WITH MULTIPLE EXCEPTS
  • COMBINING EXCEPTION TYPES
  • USING MULTIPLE OPERATIONS IN A TRY
  • USING THE RAISE KEYWORD
  • EXPLORING THE GENERAL EXCEPTION CLASSES
  • ADDING FINALLY
  • SUMMARY
  • EXERCISES
  • Lesson 23: Pulling It All Together: Word Analysis in Python
  • EXAMINE THE DATA
  • READ THE DATA
  • TOKENIZE THE DATASET
  • COUNT THE WORDS IN EACH REVIEW
  • SUMMARY
  • Lesson 24: Extracting, Transforming, and Loading with ETL Scripting
  • ETL SCRIPTING IN PYTHON
  • DESIGN AND IMPLEMENT CUSTOM ETL SCRIPTS
  • THE EXTRACT CLASS
  • THE TRANSFORM CLASS
  • THE LOAD CLASS
  • SUMMARY
  • EXERCISES
  • Lesson 25: Improving ETL Scripting
  • CONVERTING TO STATIC METHODS FOR THE EXTRACT CLASS.
  • CONVERTING TO STATIC METHODS FOR THE TRANSFORM CLASS
  • SUMMARY
  • EXERCISES
  • PART VI: Appendices
  • Appendix A: Flowcharts
  • FLOWCHART BASICS
  • COMMON FLOWCHARTING SHAPES
  • Appendix B: Creating Pseudocode
  • WHAT IS PSEUDOCODE?
  • Appendix C: Installing MySQL
  • MySQL INSTALLATION
  • VERIFY THE INSTALLATION
  • THE MySQL NOTIFIER
  • Appendix D: Installing Vinyl DB
  • DATABASE STRUCTURE
  • CREATE THE DATABASE
  • Appendix E: Installing MongoDB
  • INSTALLING MongoDB COMMUNITY SERVER
  • RUNNING MongoDB
  • Appendix F: Importing to MongoDB
  • Index
  • Copyright
  • About the Authors
  • About the Technical Writer
  • About the Technical Editor
  • Acknowledgments
  • End User License Agreement.

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