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`

.

### Instructions

**1.**

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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