book

Python Programming: A Modular Approach

Name: Python Programming: A Modular Approach
Author: Sheetal Taneja
ISBN: 9789367135440

by Sheetal Taneja

January 2025

Intermediate to advanced

716 pages

16h 11m

English

Pearson India

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Cover
About Pearson
Title Page
Contents
Foreword
Preface
About the Authors
1. Python Programming: An Introduction
1.1 IDLE – An Interpreter for Python1.2 Python Strings1.3 Relational Operators1.4 Logical Operators1.5 Bitwise Operators1.6 Variables and Assignment StatementsAssignment StatementShorthand Notation1.7 Keywords1.8 Script ModeSummaryExercises
2. Functions
2.1 Built-in Functionsinput() Functioneval() FunctionCompositionprint() Functiontype() Functionround() FunctionType Conversionmin() and max() Functionspow() FunctionRandom Number GenerationFunctions from math ModuleComplete List of Built-in Functions2.2 Formatted String Literals within Print Function2.3 Function Definition and CallFruitful Functions vs Void FunctionsFunction helpDefault Parameter ValuesKeyword Arguments2.4 Importing User-defined Module2.5 Assert Statement2.6 Command Line Arguments2.7 Specification of Type as Part of Function DefinitionSummaryExercises
3. Control Structures
3.1 if Conditional StatementGeneral Form of if Conditional StatementConditional ExpressionGeneral Form of if-else Conditional StatementGeneral Form of if-elif-else Conditional StatementNested if-elif-else Conditional Statement3.2 match: Conditional Statement (Structural Pattern Matching)3.3 Iteration (for and while Statements)3.3.1 for LoopGeneral Format of for Statement3.3.2 while LoopGeneral Format of while StatementInfinite Loops3.3.3 while Statement vs. for Statement3.3.4 Example: To Print Some Pictures3.3.5 Nested Loops3.3.6 break, continue, and pass Statements3.3.7 Example: To Compute sin(x)3.3.8 else StatementSummaryExercises

4. Debugging
4.1 TestingAn Example: Finding Maximum of Three Numbers4.2 DebuggingSummaryExercises
5. Scope
5.1 Objects and Object ids5.2 Scope of Objects and Names5.2.1 Namespaces5.2.2 ScopeLEGB RuleSummaryExercises
6. Strings
6.1 Strings6.1.1 Slicing6.1.2 Membership6.1.3 Built-in Functions on StringsFunction count()Functions find() and rfind()Functions capitalize(), title(), lower(), upper(), and swapcase()Functions islower(), isupper(), and istitle()Function replace()Functions strip(), lstrip(), and rstrip()Functions split() and partition()Function join()Functions isspace(), isalpha(), isdigit(), and isalnum()Function startswith() and endswith()Functions removeprefix() and removesuffix()Functions encode and decodeList of Functions6.2 String Processing Examples6.2.1 Counting the Number of Matching Characters in a Pair of Strings6.2.2 Counting the Number of Common Characters in a Pair of Strings6.2.3 Reversing a String6.2.4 Determining Whether a String is a Palindrome6.3 Pattern Matching6.3.1 Some Important DefinitionsSummaryExercises
7. Mutable and Immutable Objects
7.1 Lists7.1.1 Summary of List Operations7.1.2 Function list7.1.3 Functions append(), extend(), count(), remove(), index(), pop(), and insert()7.1.4 Function insert()7.1.5 Function reverse()7.1.6 Functions sort() and reverse()7.1.7 List Functions7.1.8 List Comprehension7.1.9 Lists as Arguments7.1.10 Copying List Objects7.1.11 map(), reduce(), and filter() Operations on a Sequence7.2 Sets7.2.1 Set Functions add(), update(), remove(), pop(), and clear()7.2.2 Set Functions union(), intersection(), difference(), and symmetric_difference()7.2.3 Function copy()7.2.4 Subset and Superset Test7.2.5 List of Functions7.2.6 Finding Common Factors7.2.7 Union and Intersection Operation on Lists7.3 Tuples7.3.1 Summary of Tuple Operations7.3.2 Functions tuple() and zip()7.3.3 Functions count() and index()7.3.4 Creating a List of Tuples Comprising Strings and Their Corresponding Length7.4 Dictionary7.4.1 Dictionary Operations7.4.2 Deletion7.4.3 Function get() and setdefault()7.4.4 Function update()7.4.5 Function copy()7.4.6 Function pop()7.4.7 Function popitem()7.4.8 Function fromkeys()7.4.9 List of Functions7.4.10 Inverted Dictionary7.4.11 Dictionary ComprehensionSummaryExercises
8. Recursion
8.1 Recursive Solutions for Problems on Numeric Data8.1.1 FactorialIterative ApproachRecursive Approach8.1.2 Fibonacci SequenceIterative ApproachRecursive Approach8.2 Recursive Solutions for Problems on Strings8.2.1 Length of a String8.2.2 Reversing a String8.2.3 Palindrome8.3 Recursive Solutions for Problems on Lists8.3.1 Flatten a List8.3.2 Copy8.3.3 Deep Copy8.3.4 Permutation8.4 Problem of Tower of HanoiSummaryExercises
9. Files and Exceptions
9.1 File Handling9.2 Counting Number of Characters, Lines, and Words in a File9.3 Writing Structured Objects to a File9.4 Errors and Exceptions9.5 Handling Exceptions Using try…except9.6 File Processing Example9.7 Reading and Writing to and from CSV File9.7.1 Writing to a CSV File9.7.2 Reading from a CSV File9.7.3 Reading and Writing a Dictionary to and from a CSV File9.8 Working in Python Development ModeSummaryExercises
10. Classes I
10.1 Classes and Objects10.2 Person: An Example of Class10.2.1 Destructor10.3 Class as Abstract Data Type10.4 Date Class10.5 Data ClassSummaryExercises
11. Classes II
11.1 Polymorphism11.1.1 Operator OverloadingComparing Dates11.1.2 Function Overloading11.2 Encapsulation, Data Hiding, and Data Abstraction11.3 Modifier and Accessor Methods11.4 Static Method11.5 Adding Methods Dynamically11.6 Composition11.7 Inheritance11.7.1 Single InheritanceScope RuleExtending Scope of int Class Using a User Defined Class11.7.2 Hierarchical Inheritance11.7.3 Multiple Inheritance11.7.4 Abstract Methods11.7.5 Attribute Resolution Order for Inheritance11.8 Built-in Functions for ClassesSummaryExercises
12. List Manipulation
12.1 Sorting12.1.1 Selection Sort12.1.2 Bubble Sort12.1.3 Insertion Sort12.2 Searching12.2.1 Linear Search12.2.2 Binary Search12.3 A Case Study12.3.1 Operations for Class SectionComplete Script12.4 More on Sorting12.4.1 Merge Sort12.4.2 Quick SortSummaryExercises
13. Data Structures I: Stack and Queues
13.1 Stacks13.1.1 Parentheses Matching13.1.2 Evaluating Arithmetic Expressions13.1.3 Conversion of Infix Expression to Postfix Expression13.2 Queues13.3 Restricted and Generic Data StructuresSummaryExercises
14. Data Structures II: Linked Lists
14.1 Introduction14.2 Insertion and Deletion at the Beginning of a Linked List14.3 Deleting a Node with a Particular Value from a Linked List14.4 Traversing a Linked List14.5 Maintaining Sorted Linked List While Inserting14.6 Stack Implementation Using Linked List14.7 Queue Implementation Using Linked ListSummaryExercises
15. Data Structures III: Binary Search Trees
15.1 Definitions and Notations15.2 Binary Search Tree15.3 Traversal of Binary Search Trees15.3.1 Inorder Traversal15.3.2 Preorder Traversal15.3.3 Postorder Traversal15.3.4 Height of a Binary Tree15.4 Building Binary Search TreeSummaryExercises
16. More on Recursion
16.1 Pattern within a Pattern16.2 Generalized Eight Queens Problem16.3 Knight’s Tour Problem16.4 Stable Marriage Problem16.5 Fractal (Hilbert Curve and Sierpinski Triangle)16.6 Sudoku16.7 Guidelines on Using RecursionSummaryExercises
17. Graphics
17.1 2D Graphics17.1.1 Point and LineAxis, Title, and LabelPlotting Multiple Functions in the Same FigureMultiple PlotsSaving Figure17.1.2 Histogram and Pi Chart17.1.3 Sine and Cosine Curves17.1.4 Graphical Objects: Circle, Ellipse, Rectangle, Polygon, and ArrowCircleEllipseRectanglePolygonArrow17.2 3D ObjectsBoxSphereRingCylinderArrowConeCurve17.3 Animation – Bouncing BallSummaryExercises
18. Applications of Python
18.1 Collecting Information from XOpen AuthenticationAn Example – Collecting User InformationCollecting Tweets of a UserCollecting Tweets Having Specific Words18.2 Sharing Data Using SocketsClient-Server Communication on the Same Machine – A Simple ExampleAn Echo ServerAccessing Web Data (Downloading a Pdf File)18.3 Managing Databases Using Structured Query Language (SQL)18.3.1 Database Concepts18.3.2 Creating Database and Tables18.3.3 Inserting Data into Table18.3.4 Retrieving Data from Table18.3.5 Updating Data in a Table18.3.6 Deleting Data from Table/Deleting Table18.4 Developing Mobile Application for Android18.4.1 A Simple Application involving a Registration Interface18.4.2 Tic-Tac-Toe Game18.4.3 Running Kivy Applications on Android18.5 Integrating Java with Python18.5.1 Accessing Java Collections and Arrays in Python18.5.2 Converting Python Collections to Java Collections18.5.3 Invoking a Parameterized Java Method from Python18.5.4 Invoking Parameterized Python Method from Java18.6 Python Chat Application Using Kivy and Socket ProgrammingSummaryExercises
19. Data Analysis Using PanDas
19.1 Series19.1.1 Setting Indexes Explicitly19.1.2 indexing and SlicingUsing loc and iloc for IndexingRetrieving Multiple Values with Slicing19.1.3 Manipulating Series ObjectDisplaying the Head and Tail of the Series (n elements)Summarizing a SeriesData Aggregation and Arithmetic Operations on Series ObjectsFiltering ValuesChecking for Membership19.2 DataframePandas DataFrame19.2.1 Creation of pandas DataFrame Using Series and Dictionary19.2.2 Reading from CSV FileSelecting Specific Columns and Skipping Rows While Reading a CSV FileExamining and Setting Column Data Types in a DataFrameDescribing a DataFrameRetrieving Subsets of Data – Indexing and SlicingColumn and Row IndexingAccessing ColumnsAccessing RowsBoolean Indexing: Filtering Data Based on ConditionsDescriptive StatisticsAggregating Data: Calculating Summary StatisticsDistinct Values in a Column and their Count of OccurrenceData ManipulationModifying a DataFrame: Adding, Dropping, and Updating Rows and ColumnsAdding New ColumnsDropping Columns and RowsDropping ColumnsDropping Rows by IndexUpdating Existing ColumnsConditional UpdatesRenaming Columns of a DataFrameRenaming ColumnsWriting to a csv fileGrouping and AggregationPerforming Multiple Aggregations with agg()19.3 Data Visualization19.3.1 Pie Chart: Department Distribution19.3.2 Bar Chart: Average Pay by Department19.3.3 Box Plot: Pay Distribution by Department19.3.4 Scatter Plot: Pay vs. AllowancesSummaryExercises
Index
Copyright

Overview

Python Programming: A Modular Approach (2nd Edition) is a comprehensive, updated guide to mastering modern Python.
Fully revised for Python 3.12, ensuring alignment with the latest features and updates.
Blends foundational concepts with advanced, real-world applications for a complete learning experience.
Presents Python in a clear, modular format, helping learners develop strong programming habits from the start.

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