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Bash for Data Scientists
| Bash for Data Scientists |
| Autore | Campesato Oswald |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (293 pages) |
| Disciplina | 005.43 |
| Soggetto topico | COMPUTERS / Programming Languages / Python |
| Soggetto non controllato |
Computer Science
Data Science Pandas Programming Python UNIX awk data mining grep sed |
| ISBN |
9781683929710
1683929713 9781683929727 1683929721 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Bash for Data Scientists -- CONTENTS -- PREFACE -- WHAT IS THE GOAL? -- IS THIS BOOK IS FOR ME AND WHAT WILL I LEARN? -- HOW WERE THE CODE SAMPLES CREATED? -- WHAT YOU NEED TO KNOW FOR THIS BOOK -- WHICH BASH COMMANDS ARE EXCLUDED? -- HOW DO I SET UP A COMMAND SHELL? -- WHAT ARE THE "NEXT STEPS" AFTER FINISHING THIS BOOK? -- CHAPTER 1 INTRODUCTION -- WHAT IS UNIX? -- Available Shell Types -- WHAT IS BASH? -- Getting Help for Bash Commands -- Navigating Around Directories -- The history Command -- LISTING FILENAMES WITH THE LS COMMAND -- DISPLAYING CONTENTS OF FILES -- The cat Command -- The head and tail Commands -- The Pipe Symbol -- The fold Command -- FILE OWNERSHIP: OWNER, GROUP, AND WORLD -- HIDDEN FILES -- HANDLING PROBLEMATIC FILENAMES -- WORKING WITH ENVIRONMENT VARIABLES -- The env Command -- Useful Environment Variables -- Setting the PATH Environment Variable -- Specifying Aliases and Environment Variables -- FINDING EXECUTABLE FILES -- THE printf COMMAND AND THE echo COMMAND -- THE cut COMMAND -- THE echo COMMAND AND WHITESPACES -- COMMAND SUBSTITUTION ("BACK TICK") -- THE PIPE SYMBOL AND MULTIPLE COMMA -- USING A SEMICOLON TO SEPARATE COMMANDS -- THE paste COMMAND -- Inserting Blank Lines with the paste Command -- A SIMPLE USE CASE WITH THE paste COMMAND -- A SIMPLE USE CASE WITH cut AND paste COMMANDS -- WORKING WITH META CHARACTERS -- WORKING WITH CHARACTER CLASSES -- WHAT ABOUT ZSH? -- Switching between bash and zsh -- Configuring zsh -- SUMMARY -- CHAPTER 2 FILES AND DIRECTORIES -- CREATE, COPY, REMOVE, AND MOVE FILES -- Creating Files -- Copying Files -- Copy Files with Command Substitution -- Deleting Files -- Moving Files -- THE BASENAME, DIRNAME, AND FILE COMMANDS -- THE wc COMMAND -- THE more COMMAND AND THE less COMMAND -- THE head COMMAND -- THE tail COMMAND -- FILE COMPARISON COMMANDS -- THE PARTS OF A FILENA.
WORKING WITH FILE PERMISSIONS -- The chmod Command -- The chown Command -- The chgrp Command -- The umask and ulimit Commands -- WORKING WITH DIRECTORIES -- Absolute and Relative Directories -- Absolute and Relative Path Names -- Creating Directories -- Removing Directories -- Changing Directories -- Renaming Directories -- USING QUOTE CHARACTERS -- STREAMS AND REDIRECTION COMMANDS -- METACHARACTERS AND CHARACTER CLASSES -- Digits and Characters -- Working with "^" and "\" and "!" -- FILENAMES AND METACHARACTERS -- SUMMARY -- CHAPTER 3 USEFUL COMMANDS -- THE join COMMAND -- THE fold COMMAND -- THE split COMMAND -- THE sort COMMAND -- THE uniq COMMAND -- HOW TO COMPARE FILES -- THE od COMMAND -- THE tr COMMAND -- A SIMPLE USE CASE -- THE find COMMAND -- THE tee COMMAND -- FILE COMPRESSION COMMANDS -- The tar command -- The cpio Command -- The gzip and gunzip Commands -- The bunzip2 Command -- The zip Command -- COMMANDS FOR zip FILES AND bz FILES -- INTERNAL FIELD SEPARATOR (IFS) -- DATA FROM A RANGE OF COLUMNS IN A DATASET -- WORKING WITH UNEVEN ROWS IN DATASETS -- THE alias COMMAND -- SUMMARY -- CHAPTER 4 CONDITIONAL LOGIC AND LOOPS -- ARITHMETIC OPERATIONS AND OPERATORS -- WORKING WITH ARRAYS -- ARRAYS AND TEXT FILES -- WORKING WITH VARIABLES -- Assigning Values to Variables -- WORKING WITH OPERATORS FOR STRINGS AND NUMBERS -- THE read COMMAND FOR USER INPUT -- THE test COMMAND FOR VARIABLES, FILES, AND DIRECTORIES -- Relational Operators -- Boolean Operators -- String Operators -- File Test Operators -- CONDITIONAL LOGIC WITH if/else STATEMENTS -- THE case/esac STATEMENT -- ARITHMETIC OPERATORS AND COMPARISONS -- WORKING WITH STRINGS IN SHELL SCRIPTS -- Working with Strings -- WORKING WITH LOOPS -- Using a for loop -- WORKING WITH NESTED LOOPS -- USING A while LOOP -- THE while, case, AND if/elif/fi STATEMENTS -- USING AN UNTIL LOOP. USER-DEFINED FUNCTIONS -- CREATING A SIMPLE MENU FROM SHELL COMMANDS -- SUMMARY -- CHAPTER 5 PROCESSING DATASETS WITH GREPAND SED -- WHAT IS THE grep COMMAND? -- METACHARACTERS AND THE grep COMMAND -- ESCAPING METACHARACTERS WITH THE grep COMMAND -- USEFUL OPTIONS FOR THE grep COMMAND -- Character Classes and the grep Command -- WORKING WITH THE -C OPTION IN grep -- MATCHING A RANGE OF LINES -- USING BACK REFERENCES IN THE grep COMMAND -- FINDING EMPTY LINES IN DATASETS -- USING KEYS TO SEARCH DATASETS -- THE BACKSLASH CHARACTER AND THE grep COMMAND -- MULTIPLE MATCHES IN THE GREP COMMAND -- THE grep COMMAND AND THE xargs COMMAND -- Searching zip Files for a String -- CHECKING FOR A UNIQUE KEY VALUE -- Redirecting Error Messages -- THE egrep COMMAND AND fgrep COMMAND -- Displaying "Pure" Words in a Dataset with egrep -- Redirecting Error Messages -- THE egrep COMMAND AND fgrep COMMAND -- Displaying "Pure" Words in a Dataset with egrep -- The fgrep Command -- DELETE ROWS WITH MISSING VALUES -- A SIMPLE USE CASE -- WHAT IS THE sed COMMAND? -- The sed Execution Cycle -- MATCHING STRING PATTERNS USING sed -- SUBSTITUTING STRING PATTERNS USING sed -- Replacing Vowels from a String or a File -- Deleting Multiple Digits and Letters from a String -- SEARCH AND REPLACE WITH sed -- DATASETS WITH MULTIPLE DELIMITERS -- USEFUL SWITCHES IN sed -- WORKING WITH DATASETS -- Printing Lines -- Character Classes and sed -- Removing Control Characters -- COUNTING WORDS IN A DATASET -- BACK REFERENCES IN sed -- ONE-LINE sed COMMANDS -- POPULATE MISSING VALUES WITH THE sed COMMAND -- A DATASET WITH 1,000,000 ROWS -- Numeric Comparisons -- Counting Adjacent Digits -- Average Support Rate -- SUMMARY -- CHAPTER 6 PROCESSING DATASETS WITH AWK -- THE awk COMMAND -- Built-in Variables that Control awk -- How Does the awk Command Work? -- ALIGNING TEXT WITH THE printf COMMAND. CONDITIONAL LOGIC AND CONTROL STATEMENTS -- The while Statement -- A for loop in awk -- A for loop with a break Statement -- The next and continue Statements -- DELETING ALTERNATE LINES IN DATASETS -- MERGING LINES IN DATASETS -- Printing File Contents as a Single Line -- Joining Groups of Lines in a Text File -- Joining Alternate Lines in a Text File -- MATCHING WITH METACHARACTERS AND CHARACTER SETS -- PRINTING LINES USING CONDITIONAL LOGIC -- SPLITTING FILENAMES WITH awk -- WORKING WITH POSTFIX ARITHMETIC OPERATORS -- NUMERIC FUNCTIONS IN awk -- ONE-LINE awk COMMANDS -- USEFUL SHORT awk SCRIPTS -- PRINTING THE WORDS IN A TEXT STRING IN awk -- COUNT OCCURRENCES OF A STRING IN SPECIFIC ROWS -- PRINTING A STRING IN A FIXED NUMBER OF COLUMNS -- PRINTING A DATASET IN A FIXED NUMBER OF COLUMNS -- ALIGNING COLUMNS IN DATASETS -- ALIGNING COLUMNS AND MULTIPLE ROWS IN DATASETS -- DISPLAYING A SUBSET OF COLUMNS IN A TEXT FILE -- SUBSETS OF COLUMN-ALIGNED ROWS IN DATASETS -- COUNTING WORD FREQUENCY IN DATASETS -- DISPLAYING ONLY "PURE" WORDS IN A DATASET -- DELETE ROWS WITH MISSING VALUES -- WORKING WITH MULTI-LINE RECORDS IN AWK -- A SIMPLE USE CASE -- ANOTHER USE CASE -- A DATASET WITH 1,000,000 ROWS -- Counting Adjacent Digits -- Average Support Rate -- SUMMARY -- CHAPTER 7 PROCESSING DATASETS (PANDAS) -- PREREQUISITES FOR THIS CHAPTER -- ANALYZING MISSING DATA -- Causes of Missing Data -- PANDAS, CSV FILES, AND MISSING DATA -- Single Column CSV Files -- Two Column CSV Files -- MISSING DATA AND IMPUTATION -- Counting Missing Data Values -- Drop Redundant Columns -- Remove Duplicate Rows -- Display Duplicate Rows -- Uniformity of Data Values -- Too Many Missing Data Values -- Categorical Data -- Data Inconsistency -- Mean Value Imputation -- Random Value Imputation -- Multiple Imputation -- Matching and Hot Deck Imputation. Is a Zero Value Valid or Invalid? -- SKEWED DATASETS -- CSV FILES WITH MULTI-ROW RECORDS -- COLUMN SUBSET AND ROW SUBRANGE OF THE TITANIC CSV FILE -- DATA NORMALIZATION -- Assigning Classes to Data -- Other Data Cleaning Tasks -- DeepChecks and Data Validation -- HANDLING CATEGORICAL DATA -- Processing Inconsistent Categorical Data -- Mapping Categorical Data to Numeric Values -- Mapping Categorical Data to One Hot Encoded Values -- WORKING WITH CURRENCY -- WORKING WITH DATES -- Find Missing Dates -- Find Unique Dates -- Switch Date Formats -- WORKING WITH IMBALANCED DATASETS -- Data Sampling Techniques -- Removing Noisy Data -- Cost-sensitive Learning -- Detecting Imbalanced Data -- Rebalancing Datasets -- Specify stratify in Data Splits -- WHAT IS SMOTE? -- DATA WRANGLING -- Data Transformation: What Does This Mean? -- A DATASET WITH 1,000,000 ROWS -- Dataset Details -- Numeric Comparisons -- Counting Adjacent Digits -- SAVING CSV DATA TO XML, JSON, AND HTML FILES -- SUMMARY -- CHAPTER 8 NOSQL, SQLITE, AND PYTHON -- NON-RELATIONAL DATABASE SYSTEMS -- Advantages of Non-relational Databases -- WHAT IS NOSQL? -- What is NewSQL? -- RDBMS VERSUS NOSQL: WHICH ONE TO USE? -- Good Data Types for NoSQL -- Some Guidelines for Selecting a Database -- NoSQL Databases -- WHAT IS MONGODB? -- Features of MongoDB -- Installing MongoDB -- Launching MongoDB -- USEFUL MONGO APIS -- Metacharacters in Mongo Queries -- MONGODB COLLECTIONS AND DOCUMENTS -- Document Format in MongoDB -- CREATE A MONGODB COLLECTION -- WORKING WITH MONGODB COLLECTIONS -- Find All Android Phones -- Find All Android Phones in 2018 -- Insert a New Item (Document) -- Update an Existing Item (Document) -- Calculate the Average Price for Each Brand -- Calculate the Average Price for Each Brand in 2019 -- Import Data with mongoimport -- WHAT IS FUGUE? -- WHAT IS COMPASS? -- WHAT IS PYMONGO?. MYSQL, SQLALCHEMY, AND PANDAS. |
| Record Nr. | UNINA-9911006689403321 |
Campesato Oswald
|
||
| Bloomfield : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Dealing with Data Pocket Primer
| Dealing with Data Pocket Primer |
| Autore | Campesato Oswald |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (246 pages) |
| Disciplina | 001.42 |
| Collana | Computing |
| Soggetto topico |
Quantitative research - Reliability
Quantitative research - Data processing |
| Soggetto non controllato |
NLP
Pandas RDBMS SQL computer science data analytics data cleaning data visualization programming python statistics |
| ISBN |
1-5231-4740-7
1-68392-818-0 1-68392-819-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Probability and Statistics -- Chapter 2: Working with Data -- Chapter 3: Introduction to Pandas -- Chapter 4: Introduction to RDBMS and SQL -- Chapter 5: Working with SQL and MySQL -- Chapter 6: NLP and Data Cleaning -- Chapter 7: Data Visualization -- Index |
| Record Nr. | UNINA-9910795724303321 |
|
Campesato Oswald
|
||
| Bloomfield : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Dealing with Data Pocket Primer
| Dealing with Data Pocket Primer |
| Autore | Campesato Oswald |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (246 pages) |
| Disciplina | 001.42 |
| Collana | Computing |
| Soggetto topico |
Quantitative research - Reliability
Quantitative research - Data processing |
| Soggetto non controllato |
NLP
Pandas RDBMS SQL computer science data analytics data cleaning data visualization programming python statistics |
| ISBN |
1-5231-4740-7
1-68392-818-0 1-68392-819-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Probability and Statistics -- Chapter 2: Working with Data -- Chapter 3: Introduction to Pandas -- Chapter 4: Introduction to RDBMS and SQL -- Chapter 5: Working with SQL and MySQL -- Chapter 6: NLP and Data Cleaning -- Chapter 7: Data Visualization -- Index |
| Record Nr. | UNINA-9910823375903321 |
|
Campesato Oswald
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||
| Bloomfield : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Modern Survey Analysis : Using Python for Deeper Insights / Walter R. Paczkowski
| Modern Survey Analysis : Using Python for Deeper Insights / Walter R. Paczkowski |
| Autore | Paczkowski, Walter R. |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xxvi, 347 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68-XX - Computer science [MSC 2020] 68Txx - Artificial intelligence [MSC 2020] 90B60 - Marketing, advertising [MSC 2020] |
| Soggetto non controllato |
Consulting
Correspondence maps Cross-tabs Data Analytics Market research Pandas Python Regression models Survey data visualization Surveys |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277960 |
|
Paczkowski, Walter R.
|
||
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Modern Survey Analysis : Using Python for Deeper Insights / Walter R. Paczkowski
| Modern Survey Analysis : Using Python for Deeper Insights / Walter R. Paczkowski |
| Autore | Paczkowski, Walter R. |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xxvi, 347 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68-XX - Computer science [MSC 2020] 68Txx - Artificial intelligence [MSC 2020] 90B60 - Marketing, advertising [MSC 2020] |
| Soggetto non controllato |
Consulting
Correspondence maps Cross-tabs Data Analytics Market research Pandas Python Regression models Survey data visualization Surveys |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277960 |
|
Paczkowski, Walter R.
|
||
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
The perfect pet pageant : starring Penny Ling / / written by Lisa Shea
| The perfect pet pageant : starring Penny Ling / / written by Lisa Shea |
| Autore | Shea Lisa |
| Pubbl/distr/stampa | LB Kids |
| Descrizione fisica | 1 online resource (160 p.) |
| Disciplina | [Fic] |
| Soggetto non controllato |
Children's Fiction
Pandas Juvenile Fiction |
| ISBN | 0-316-38986-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Littlest Pet Shop |
| Record Nr. | UNINA-9910148641103321 |
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Shea Lisa
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| LB Kids | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Python Programming Using Problem Solving
| Python Programming Using Problem Solving |
| Autore | Bhasin Harsh |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2023 |
| Descrizione fisica | 1 online resource (601 pages) |
| Disciplina | 005.133 |
| Soggetto topico |
Python (Computer program language)
COMPUTERS / General |
| Soggetto non controllato |
Matplotlib
NumPy Pandas algorithm business communication computer science engineering programming science |
| ISBN |
1-68392-861-X
1-68392-860-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half-Title -- Title -- Copyright -- Dedication -- Content -- Preface -- Section I: Algorithmic Problem-Solving and Python Fundamentals -- Chapter 1: Algorithmic Problem-Solving -- 1.1 Introduction -- 1.2 Definition and Characteristics -- 1.3 Notations: Pseudocode and Flow Chart -- 1.4 Strategies for Problem-Solving: Recursion Versus Iteration -- 1.5 Asymptotic Notation -- 1.6 Complexity -- 1.7 Illustrations -- 1.7.1 Minimum in a List -- 1.7.2 Insert a Card in a Pack of Cards (Or Insert an element ina sorted list). There are ten cards in the pack, numbered from 1 to 10. -- 1.7.3 Guess a Number in a Given Range -- 1.7.4 Tower of Hanoi -- 1.8 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Application -- Chapter 2: Introduction to Python -- 2.1 Introduction -- 2.2 Features of Python -- 2.2.1 Easy -- 2.2.2 Type and Run -- 2.2.3 Syntax -- 2.2.4 Mixing -- 2.2.5 Dynamic Typing -- 2.2.6 Built-in Object Types -- 2.2.7 Numerous Libraries and Tools -- 2.2.8 Portable -- 2.2.9 Free -- 2.3 The Paradigms -- 2.3.1 Procedural -- 2.3.2 Object-Oriented -- 2.3.3 Functional -- 2.4 Chronology and Uses -- 2.4.1 Chronology -- 2.4.2 Uses -- 2.5 Installation of Anaconda -- 2.6 Implementation of an Algorithm: Statement, State, Control Blocks, and Functions -- 2.6.1 Statement -- 2.6.2 State -- 2.6.3 Control Flow -- 2.7 Conclusion -- Glossary -- Points to Remember -- Resources -- Exercises -- Multiple Choice Questions -- Theory -- Chapter 3: Fundamentals -- 3.1 Introduction -- 3.2 Basic Input Output -- 3.2.1 Print Function -- 3.2.2 Input -- 3.3 Running a Program -- 3.3.1 Using the Command Prompt -- 3.3.2 Executing Programs Written in .py Files -- 3.3.3 Using Anaconda Navigator -- 3.4 The Jupyter Notebook -- 3.5 Value Type and Reference Type -- 3.6 Tokens, Keywords, and Identifiers -- 3.6.1 Python Keywords.
3.6.2 Python Identifiers -- 3.6.3 Python Escape Sequence -- 3.7 Statements -- 3.7.1 Expression Statement -- 3.7.2 Assignment Statements -- 3.7.3 The Assert Statements -- 3.7.4 The Pass Statements -- 3.7.5 The Control Statements -- 3.8 Comments -- 3.9 Operators -- 3.10 Types and Examples of Operators -- 3.10.1 Arithmetic Operators -- 3.10.2 String Operators -- 3.10.3 Comparison Operators -- 3.10.4 Assignment Operators -- 3.10.5 Logical Operators -- 3.10.6 Priority of Operators -- 3.11 Basic Data Types -- 3.11.1 Integer -- 3.11.2 Float -- 3.11.3 String -- 3.12 Conclusion -- Exercises -- Multiple Choice Questions -- Theory -- Explore -- Section II: Procedural Programming -- Chapter 4: Conditional Statements -- 4.1 Introduction -- 4.2 "If," If-Else, and If-Elif-Else Constructs -- 4.3 The If-Elif-Else Ladder -- 4.4 Logical Operators -- 4.5 The Ternary Operator -- 4.6 The Get Construct -- 4.7 Examples -- 4.8 Summary -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Programming Exercises -- Chapter 5: Looping -- 5.1 Introduction -- 5.2 While -- 5.3 Patterns -- 5.4 Nesting and Applications of Loops in Lists -- 5.5 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Programming Exercises -- Chapter 6: Functions -- 6.1 Introduction -- 6.2 Features of a Function -- 6.2.1 Modular Programming -- 6.2.2 Reusability of Code -- 6.2.3 Manageability -- 6.2.3.1 Easy debugging -- 6.2.3.2 Efficient -- 6.3 Basic Terminology -- 6.3.1 Name of a Function -- 6.3.2 Arguments -- 6.3.3 Return Value -- 6.4 Definition and Invocation -- 6.4.1 Working -- 6.5 Types of Function -- 6.5.1 Arguments: Types of Arguments -- 6.6 Implementing Search -- 6.7 Scope -- 6.8 Recursion -- 6.8.1 Rabbit Problem -- 6.8.2 Disadvantages of Using Recursion -- 6.9 Conclusion -- Glossary -- Points to Remember -- Exercises. Multiple Choice Questions -- Programming Exercises -- Questions Based on Recursion -- Theory -- Extra Questions -- Chapter 7: File Handling -- 7.1 Introduction -- 7.2 The File Handling Mechanism -- 7.3 The Open Function and File Access Modes -- 7.4 Python Functions for File Handling -- 7.4.1 The Essential Ones -- 7.4.2 The OS Methods -- 7.4.3 Miscellaneous Functions and File Attributes -- 7.5 Command Line Arguments -- 7.6 Implementation and illustrations -- 7.7 Conclusion -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Chapter 8: Lists, tuple, and Dictionar -- 8.1 Introduction -- 8.2 Lists -- 8.2.1 Accessing Elements: Indexing and Slicing -- 8.2.2 Mutability -- 8.2.3 Operators -- 8.2.4 Traversal -- 8.2.5 Functions -- 8.3 Tuple -- 8.3.1 Accessing Elements of a Tuple -- 8.3.2 Nonmutability -- 8.3.3 Operators -- 8.3.4 Traversal -- 8.3.5 Functions -- 8.4 Associate Arrays and Dictionaries -- 8.4.1 Displaying Elements of a Dictionary -- 8.4.2 Some Important Functions of Dictionaries -- 8.4.2.1 The len function returns the number of elements in a given dictionary. -- 8.4.2.2 The max function returns the key with maximum value. If the key is a string, then the value in the lexicographic ordering would be returned. -- 8.4.2.3 The min function returns the key with minimum value. If the key is a string, then the value in the lexicographic ordering would be returned. -- 8.4.2.4 The sorted function would sort the elements of a given dictionary by their keys. If the keys are strings then lexicographic ordering would be followed. -- 8.4.2.5 The pop function takes out the element with the given key from the dictionary. -- 8.4.3 Input from the User -- 8.5 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises. Chapter 9: Iterations, Generators, and Comprehensions -- 9.1 Introduction -- 9.2 The Power of "For -- 9.3 Iterator -- 9.4 Defining an Iterable Object -- 9.5 Generators -- 9.6 Comprehensions -- 9.7 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Chapter 10: Strings -- 10.1 Introduction -- 10.2 Loops Revised -- 10.3 String Operators -- 10.3.1 The Concatenation Operator (+) -- 10.3.2 The Replication Operator (*) -- 10.3.3 The Membership Operator -- 10.4 In-Built Functions -- 10.4.1 len() -- 10.4.2 Capitalize() -- 10.4.3 Find() -- 10.4.4 Count -- 10.4.5 endswith() -- 10.4.6 encode -- 10.4.7 decode -- 10.4.8 Miscellaneous Functions -- 10.5 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Section III: Object-Oriented Programming -- Chapter 11: Introduction to Object-Oriented Paradigm -- 11.1 Introduction -- 11.2 Creating New Types -- 11.3 Attributes and Functions -- 11.3.1 Attributes -- 11.3.2 Functions -- 11.4 Elements of Object-Oriented Programming -- 11.4.1 Class -- 11.4.2 Object -- 11.4.3 Encapsulation -- 11.4.4 Data Hiding -- 11.4.5 Inheritance -- 11.4.6 Polymorphism -- 11.4.7 Reusability -- 11.5 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Explore and Design -- Chapter 12: Classes and Objects -- 12.1 Introduction to Classes -- 12.2 Defining a Class -- 12.3 Creating an Object -- 12.4 Scope of Data Members -- 12.5 Nesting -- 12.6 Constructor -- 12.7 Multiple __Init__(s) -- 12.8 Destructors -- 12.9 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Chapter 13: Inheritance -- 13.1 Introduction to Inheritance and Composition -- 13.1.1 Inheritance and Methods -- 13.1.2 Composition. 13.2 Inheritance: Importance and Types -- 13.2.1 Need for Inheritance -- 13.2.2 Types of Inheritance -- 13.2.2.1 Simple inheritance -- 13.2.2.2 Hierarchical inheritance -- 13.2.2.3 Multilevel inheritance -- 13.2.2.4 Multiple inheritance and hybrid inheritance -- 13.3 Methods -- 13.3.1 Bound Methods -- 13.3.2 Unbound Method -- 13.3.3 Methods are Callable Objects -- 13.3.4 The Importance and Usage of Super -- 13.3.5 Calling the Base Class Function Using Super -- 13.4 Search in Inheritance Tree -- 13.5 Class Interface and Abstract Classes -- 13.6 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Chapter 14: Operator Overloading -- 14.1 Introduction -- 14.2 __Init__ Revisited -- 14.2.1 Overloading __init__(Sort of) -- 14.3 Methods for Overloading Binary Operators -- 14.4 Overloading Binary Operators: The Fraction Example -- 14.5 Overloading the += Operator -- 14.6 Overloading the > -- and < -- Operators -- 14.7 Overloading the __Bool__ Operator: Precedence of __Bool__ Over __Len__ -- 14.8 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Chapter 15: Exception Handling -- 15.1 Introduction -- 15.2 Importance and Mechanism -- 15.2.1 An Example of Try/Except -- 15.2.2 Manually Raising Exceptions -- 15.3 Build-in Exceptions in Python -- 15.4 The Process -- 15.4.1 Example -- 15.4.2 Exception Handling: Try/Except -- 15.4.3 Raising Exceptions -- 15.5 Crafting User Defined Exceptions -- 15.6 An Example of Exception Handling -- 15.7 Conclusion -- Glossary -- Points to Remember -- Exercises -- Multiple Choice Questions -- Theory -- Programming Exercises -- Section IV: Numpy, Pandas, and Matplotlib -- Chapter 16: Numpy-I -- 16.1 Introduction -- 16.2 Fundamentals. 16.2.1 Similarity and Differences Between a List and a NumPy Array. |
| Record Nr. | UNINA-9910915680903321 |
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Bhasin Harsh
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||
| Bloomfield : , : Mercury Learning & Information, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||