Why custom ufuncs matter in NumPy - See It in Action

Why custom ufuncs matter

📖 Scenario: Imagine you have a list of temperatures in Celsius and you want to convert them to Fahrenheit. Normally, you might write a loop or use a simple function. But what if you want to do this conversion very fast on large arrays? That's where custom ufuncs in NumPy help.

🎯 Goal: You will create a simple custom universal function (ufunc) in NumPy to convert Celsius temperatures to Fahrenheit. Then you will apply it to a NumPy array and see the fast, easy result.

📋 What You'll Learn

Create a NumPy array with exact Celsius temperatures

Define a Python function to convert Celsius to Fahrenheit

Create a custom ufunc from the Python function using NumPy's frompyfunc

Apply the custom ufunc to the NumPy array

Print the resulting Fahrenheit temperatures

💡 Why This Matters

🌍 Real World

Scientists and engineers often need to apply custom calculations on large datasets quickly. Custom ufuncs let them do this efficiently with NumPy arrays.

💼 Career

Data scientists and analysts use custom ufuncs to speed up data transformations and apply complex functions element-wise in their data pipelines.

1

Create a NumPy array of Celsius temperatures

Import NumPy as np and create a NumPy array called celsius_temps with these exact values: 0, 20, 37, 100.

NumPy

import numpy as np
# Create a NumPy array called celsius_temps with values 0, 20, 37, 100
# Your code here

Need a hint?

Use np.array([...]) to create the array.

2

Define a Python function to convert Celsius to Fahrenheit

Define a function called c_to_f that takes one argument c and returns the Fahrenheit temperature using the formula c * 9 / 5 + 32.

NumPy

import numpy as np
celsius_temps = np.array([0, 20, 37, 100])
# Define function c_to_f(c) that returns c * 9 / 5 + 32
# Your code here

Need a hint?

Remember to use def to define the function and return the converted value.

3

Create a custom ufunc from the Python function

Use np.frompyfunc to create a universal function called c_to_f_ufunc from the c_to_f function. Specify it takes 1 input and returns 1 output.

NumPy

import numpy as np
celsius_temps = np.array([0, 20, 37, 100])
def c_to_f(c):
    return c * 9 / 5 + 32
# Create a ufunc c_to_f_ufunc from c_to_f using np.frompyfunc
# Your code here

Need a hint?

Use np.frompyfunc(function, nin, nout) where nin is number of inputs and nout is number of outputs.

4

Apply the custom ufunc and print the result

Apply the c_to_f_ufunc to the celsius_temps array and store the result in fahrenheit_temps. Then print fahrenheit_temps.

NumPy

import numpy as np
celsius_temps = np.array([0, 20, 37, 100])
def c_to_f(c):
    return c * 9 / 5 + 32
c_to_f_ufunc = np.frompyfunc(c_to_f, 1, 1)
# Apply c_to_f_ufunc to celsius_temps and print the result
# Your code here

Need a hint?

Use fahrenheit_temps = c_to_f_ufunc(celsius_temps) and then print(fahrenheit_temps).