Dive into a comprehensive tutorial on the NumPy library for Python beginners. Explore the fundamentals of NumPy, including its advantages over Python's built-in lists in terms of speed and functionality. Learn to create arrays, understand their properties like shape and size, and work with different data types. Master techniques for accessing and modifying specific elements, rows, and columns through slicing. Discover various methods for initializing arrays, including ones, zeros, and random values. Tackle practical problems to reinforce your understanding of array initialization and variable copying. Delve into basic mathematical operations, linear algebra, and statistical functions within NumPy. Practice reorganizing arrays using reshape, vstack, and hstack methods. Learn how to load data from files and implement advanced indexing techniques with boolean masking. Access additional resources and documentation to further expand your NumPy knowledge and skills.
Overview
Syllabus
What is NumPy.
NumPy vs Lists (speed, functionality).
Applications of NumPy.
The Basics (creating arrays, shape, size, data type).
Accessing/Changing Specific Elements, Rows, Columns, etc (slicing).
Initializing Different Arrays (1s, 0s, full, random, etc...).
Problem #1 (How do you initialize this array?).
Be careful when copying variables!.
Basic Mathematics (arithmetic, trigonometry, etc.).
Linear Algebra.
Statistics.
Reorganizing Arrays (reshape, vstack, hstack).
Load data in from a file.
Advanced Indexing and Boolean Masking.
Problem #2 (How do you index these values?).
Taught by
freeCodeCamp.org
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Reviews
5.0 rating, based on 2 Class Central reviews
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Harshal DhageI recently completed a NumPy course, and it was an outstanding learning experience. The course was well-organized, starting with basic array operations and progressing to more advanced topics like broadcasting, linear algebra, and integration with other libraries. The instructor explained concepts clearly, using practical examples and exercises that reinforced learning effectively. The use of Jupyter Notebooks for demonstrations made the content engaging and interactive. Real-world applications highlighted the importance of NumPy in data analysis and scientific computing. Overall, the course significantly enhanced my understanding and confidence in using NumPy for various data science tasks. -
Lakshmi VIts just like wow. Really superb explanation.content are also good.i have got a amazing experience with this course. I saw more videos to learn numpy. But it was hard to understand. By god's grace i found this platform.Now i have learned about the numpy.it is really helpfull.Thank you class central. Keep rocking
