calculate BMI by numpy array

Numpy arrays are great alternatives to Python Lists. Some of the key advantages of Numpy arrays are that they are fast, easy to work with, and give users the opportunity to perform calculations across entire arrays.

In the following example, you will first create two Python lists. Then, you will import the numpy package and create numpy arrays out of the newly created lists.

# Create 2 new lists height and weight
height = [1.6, 1.87,  1.87, 1.82, 1.91]
weight = [55.2,81.65, 97.52, 95.25, 92.98]
print("height")
print(height)
print("weight")
print(weight)
# Import the numpy package as np
import numpy as np

# Create 2 numpy arrays from height and weight
np_height = np.array(height)
np_weight = np.array(weight)
print("type")
print(type(np_height))

# Calculate bmi
bmi = np_weight / np_height ** 2

# Print the result
print("BMI")
print(bmi)

# For a boolean response
print("bmi > 23")
print(bmi > 23)

print("bmi < 23")
print(bmi < 23)

# Print only those observations above 23
print("bmi[bmi > 23]")
print(bmi[bmi > 23])


==== RESTART: C:/python/calculateBMIbyNumpy.py =====
height
[1.6, 1.87, 1.87, 1.82, 1.91]
weight
[55.2, 81.65, 97.52, 95.25, 92.98]
type

BMI
[21.5625     23.34925219 27.88755755 28.75558507 25.48723993]
bmi > 23
[False  True  True  True  True]
bmi < 23
[ True False False False False]
bmi[bmi > 23]
[23.34925219 27.88755755 28.75558507 25.48723993]
>>>