NumPy — Matrix Operations

Arithmetic

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])

print(a + b)    # [5, 7, 9]
print(a - b)    # [-3, -3, -3]
print(a * b)    # [4, 10, 18]
print(a / b)    # [0.25, 0.4, 0.5]
print(a ** b)   # [1, 32, 729]

Trigonometric

arr = np.array([0, np.pi/4, np.pi/2])
print(np.sin(arr))
print(np.cos(arr))
print(np.tan(arr))

Logarithmic

arr = np.array([1, 10, 100])
print(np.log(arr))    # Natural log
print(np.log10(arr))  # Base 10
print(np.log2(arr))   # Base 2

Exponential

arr = np.array([0, 1, 2, 3])
print(np.exp(arr))
print(np.exp2(arr))

Aggregations

arr = np.array([1, 2, 3, 4, 5])
print(np.sum(arr))
print(np.prod(arr))
print(np.cumsum(arr))
print(np.cumprod(arr))

Mini Practice

1. Perform arithmetic
2. Use trigonometric functions
3. Calculate logarithms
4. Practice aggregations

Up Next

Continue with Statistics - Statistical functions.