Programming with Python

• Python Introduction
• Why Python? Installing and Running Python using Interactive Shell and Console
• Using IDLE and IDE
• Installing Third Party Libraries
• Working with Virtual Environment
• Writing Comments
• Indentation
• Tokens
• Identifiers
• Keywords
• Literals
• Variables and Constants
• The id() function
• Operators.

• Introduction
• Selection Statements (if statements and match -case statement)
• Using if-else as Ternary Operator
• Looping Statements ( for and while Loops)
• The else Clause after for or while Loops
• The break and continue Statements
• The pass Statement.

• Introduction
• Numeric Types – Integers, Floating Point Numbers and Complex Numbers
• String – Indexing and Slicing, String Formatting, Escape Sequences
• Boolean
• List – Indexing and Slicing, Changing Items, Adding and Removing Items, Looping, Copying, List Comprehension, Sorting, Cop ying, and Joining
• Tuple – Updating, Indexing and Slicing, Unpacking, Looping, Joining
• Set – Accessing, Adding and Removing Items, Set Operations
• Frozenset
• Range
• Dictionary
• Binary Types
• None Type.

• Introduction
• Benefits of using Functions
• Creating and Calling Functions
• Passing Arguments
• Packing and Unpacking Arguments using Tuples and Dictionaries
• Return Values and Returning Multiple Values
• Recursive Function
• Lambda Function.

• Introduction
• Object -Oriented Principles – Classes and Objects, Encapsulation
• Inheritance, Polymorphism, Abstraction
• Defining a Class – Adding Instance Variables, Adding Instance Methods, Adding Class Variables, Adding Class Methods, Ad ding Static Methods
• Constructors
• Method Overloading
• Inheritance and its Types
• Method Overriding
• Access Modifiers
• Abstract Class
• Operator Overloading
• Magic Methods
• Exception Handling
• Modules and Packages
• Enumeration.

• Introduction
• File Opening Models
• Reading and Writing Files
• The os Module and Common Functions
• The with Statement.

• Numpy: Introduction
• Array Creating
• Dimensions
• Data Types, Array Attributes, Indexing and Slicing
• Array Copy and View
• Creating Array from Numerical Range
• Array Broadcasting
• Iterating Over Array
• Sorting and Searching
• Statistical Functions Pandas: Series and DataFrames
• Creating DataFrames
• The head and tail Functions
• Attributes
• Working with Missing Data
• Indexing, Slicing, and Subsetting
• Merging and Joining DataFrames
• Working with CSV Files Matplotlib: Introduction
• Marker
• Line
• Color
• Label
• Grid Lines
• Subplot
• Scatter Plot
• Bar Graph
• Histogram, pie chart and Box plot.

Working with Database and Using SQL Statements; Basics of GUI Programming, Basics of Web Development. Laboratory Work: The laboratory work includes writing programs using Python programming language covering all the concepts studied in each unit of the course.