Vectorizing .upper()
There are many situations where you might want to use Python methods and functions on array elements in NumPy. You can always write a for loop to do this, but vectorized operations are much faster and more efficient, so consider using np.vectorize()!
You've got an array called names which contains first and last names:
names = np.array([["Izzy", "Monica", "Marvin"],
["Weber", "Patel", "Hernandez"]])
You'd like to use one of the Python methods you learned on DataCamp, .upper(), to make all the letters of every name in the array uppercase. As a reminder, .upper() is a string method, meaning that it must be called on an instance of a string: str.upper().
Your task is to vectorize this Python method. numpy is loaded for you as np, and the names array is available.
This exercise is part of the course
Introduction to NumPy
Exercise instructions
- Create a vectorized function called
vectorized_upperfrom the Python.upper()string method. - Apply
vectorized_upper()to thenamesarray and save the resulting array asuppercase_names.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Vectorize the .upper() string method
vectorized_upper = ____
# Apply vectorized_upper to the names array
uppercase_names = ____
print(uppercase_names)