While you’ve shown that you can calculate the average yourself, it becomes time-consuming as the size of your dataset increases — imagine adding all of the numbers in a dataset with 10,000 observations.

The NumPy .average() or .mean() function can do the work of adding and dividing for you. In the example below, we use np.average() to calculate the average of a dataset with ten values.

example_array = np.array([24, 16, 30, 10, 12, 28, 38, 2, 4, 36]) example_average = np.average(example_array) print(example_average)

The code above calculates the average of example_array and saves the value to example_average. The resulting average of this array is 20.



Use NumPy to calculate the average value of the author_ages array. Save the result to average_age.

Does the average age of the authors surprise you? If so, how? Is it older, or younger than you expected?

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