NumPy Fundamentals

Arrays, vectorised operations, broadcasting, and numerical computing basics.

Installing NumPy

pip install numpy

Creating Arrays

import numpy as np

a = np.array([1, 2, 3, 4, 5])
b = np.zeros((3, 3))    # 3x3 zeros
c = np.ones((2, 4))     # 2x4 ones
d = np.arange(0, 10, 2) # [0,2,4,6,8]
e = np.linspace(0, 1, 5) # 5 equally-spaced values

Array Operations

x = np.array([1, 2, 3])
y = np.array([4, 5, 6])

print(x + y)         # [5 7 9]
print(x * 2)         # [2 4 6]
print(x ** 2)        # [1 4 9]
print(np.dot(x, y))  # 32 (dot product)
print(x.mean())      # 2.0
print(x.sum())       # 6

2D Arrays (Matrices)

m = np.array([[1,2,3],[4,5,6]])
print(m.shape)   # (2, 3)
print(m[0, 2])   # 3  (row 0, col 2)
print(m[:, 1])   # [2 5]  (all rows, col 1)
print(m.T)       # transpose