introduction to data science programming.pptx
- 1. رa Introduction to Python name: ahmed mashaf al-Mutairi ID:382105541 Dr.KhaledNazem Department of Computer Science and Information Majmaah University
- 2. Introduction to Python Python is a high-level programming language known for its simplicity and ease of use. It is often used for web development, data analysis, artificial intelligence, and scientific computing. Python's clear syntax and large standard library make it an ideal choice for beginners and professionals alike. رa
- 3. History of Python 1 Birth of Python Python was created by Guido van Rossum in the late 1980s with a focus on code readability. 2 First Release The first version of Python, version 0.9.0, was released in February 1991. 3 Growth in Popularity Python gained significant momentum and community support in the early 2000s.
- 4. Features of Python • Readability: Python syntax is designed to be clear and easily understandable, emphasizing code readability. • Extensive standard library: Python comes with a large library of modules and functions, providing support for many common programming tasks. • Dynamic typing: Python is dynamically typed, allowing for flexibility and ease of use when working with data types.
- 5. Python Syntax and Data Types Python's syntax is clean and simple, making it easy to read and write. It supports diverse data types such as strings, numbers, lists, tuples, and dictionaries. Understanding Python's syntax and data types is fundamental for effective programming and data manipulation.
- 6. Control flow statements in Python Conditional Statements Use if, else, and elif to make decisions based on conditions. Loops Utilize for and while loops to iterate through code multiple times. Break and Continue Interrupt loops using break and skip iterations with continue.
- 7. Functions and modules in Python In Python, functions are defined using the def keyword and can take multiple arguments. Modules in Python are files containing Python code. Using functions and modules helps in organizing code and promoting reusability. Python provides various built-in modules for commonly used functions such as math, os, datetime, and more. Additionally, developers can create their own modules to package reusable code for different projects. Understanding functions and modules is fundamental in Python programming and plays a crucial role in creating scalable and maintainable codebases. For more information on Python functions and modules, check out Python official documentation.
- 8. Object-oriented programming in Python 1 Classes and Objects Blueprint for creating objects 2 Inheritance Ability for a class to inherit properties 3 Polymorphism Multiple forms of the same method Object-oriented programming in Python involves the use of classes, inheritance, and polymorphism. Classes act as blueprints for creating objects, while inheritance allows a class to inherit the properties of another class. Polymorphism enables the existence of multiple forms of the same method within the program.
- 9. File handling in Python File handling in Python involves various operations such as reading, writing, and manipulating files. Python provides built-in functions and methods for file operations, making it convenient to work with files of different formats.
- 10. Python libraries and frameworks Django A high-level Python web framework that encourages rapid development and clean, pragmatic design. Pandas A powerful data manipulation and analysis library that offers data structures and operations for manipulating numerical tables and time series. TensorFlow An open-source machine learning framework for building and training machine learning models. Flask A lightweight WSGI web application framework known for its simplicity and flexibility.
- 11. Conclusion and Resources Python's Versatility Python's versatility makes it suitable for a wide range of applications, from web development to data analysis and artificial intelligence. Community Support The vast community of Python developers offers a wealth of resources, tutorials, and support forums for learners and experienced professionals. Extensive Libraries Python's extensive libraries, like NumPy and Pandas, provide powerful tools for scientific computing and data manipulation. Continuous Development Python's active development ensures that it remains at the forefront of technological innovation and adaptation.