(a) Key Features of NumPy

1 Fast Numerical Computation : NumPy is written in C and optimized for speed, making mathematical operations significantly faster than Python lists.

2 Multidimensional Arrays : It provides the ndarray object that supports 1D, 2D, and higher-dimensional arrays.

3 Vectorized Operations : Operations are applied on the whole array without loops — cleaner and faster.

4 Memory Efficient : NumPy arrays store elements of the same data type, reducing memory usage.

5 Large Collection of Mathematical Functions : Includes linear algebra, statistics, trigonometry, reshaping, sorting, and more.

6 Supports Broadcasting : Enables operations between arrays of different shapes.

Differences Between NumPy Arrays and Python Lists

Feature	NumPy Array	Python List
Speed	Much faster (C optimized)	Slower
Data Type	Homogeneous (one type)	Heterogeneous (mixed types)
Memory Usage	Lower	Higher
Operations	Element-wise directly	Need loops for element-wise
Dimensions	Supports multi-dimensional	Mostly 1D (nested lists for 2D)
Functions	Large scientific function library	Limited built-in operations

(b) Python program using NumPy to create one-dimensional and two-dimensional arrays and display their shape, dimensions, and data type

Author

Name : Rohit

Roll Number : 2501060098

Section : "A"

Program : BCA(AI & DS

Course : Problem Solving Python

Assignment : 04