📊 NumPy Mathematical Functions

Last Updated: 09 Nov 2025

---

NumPy provides mathematical (like sin, log, exp, etc.) functions for array operations.

---

Basic Mathematical Functions

import numpy as np

arr = np.array([1, 2, 3, 4, 5])

print("Add 10:", np.add(arr, 10))
print("Subtract 2:", np.subtract(arr, 2))
print("Multiply by 3:", np.multiply(arr, 3))
print("Divide by 2:", np.divide(arr, 2))

---

Exponential & Logarithmic Functions

print("Exponential:", np.exp(arr))
print("Logarithm (Base e):", np.log(arr))
print("Logarithm (Base 10):", np.log10(arr))

---

Power & Square Root

arr = np.array([4, 9, 16, 25])

print("Square Root:", np.sqrt(arr))
print("Power of 2:", np.power(arr, 2))

---

Trigonometric Functions

angles = np.array([0, np.pi/2, np.pi])

print("sin:", np.sin(angles))
print("cos:", np.cos(angles))
print("tan:", np.tan(angles))
# If you have degrees → convert them
print(np.sin(np.deg2rad(90)))

🗣 Hinglish Tip:“Angles hamesha radians me dene padte hain (degrees nahi).”

---

Rounding & Absolute Functions

arr = np.array([-1.5, 1.234, 2.789])

print("Absolute:", np.abs(arr))
print("Round:", np.round(arr, 2))
print("Floor:", np.floor(arr))
print("Ceil:", np.ceil(arr))

🗣 Hinglish Tip:“Absolute negative sign hata deta hai, Floor neeche round karta hai, Ceil upar.”

---

Logical Functions

arr = np.array([10, 20, 0, 5])

print("Any True?:", np.any(arr))
print("All True?:", np.all(arr))
print("Condition Check (arr > 10):", arr[arr > 10])

np.any() → returns True if any element is non-zero np.all() → True only if all elements are non-zero

---