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Mode
Mode SciPy

Finding the mode of a dataset becomes increasingly time-consuming as the size of your dataset increases — imagine finding the mode of a dataset with 10,000 observations.

The SciPy `stats.mode()` function can do the work of finding the mode for you. In the example below, we import `stats` then use `stats.mode()` to calculate the mode of a dataset with ten values:

#### Example: One Mode

``````from scipy import stats

example_array = np.array([24, 16, 12, 10, 12, 28, 38, 12, 28, 24])

example_mode = stats.mode(example_array)``````

The code above calculates the mode of the values in `example_array` and saves it to `example_mode`.

The result of `stats.mode()` is an object with the mode value, and its count.

``````>>> example_mode
ModeResult(mode=array([12]), count=array([3]))``````

#### Example: Two Modes

If there are multiple modes, the `stats.mode()` function will always return the smallest mode in the dataset.

Let’s look at an array with two modes, `12` and `24`:

``````from scipy import stats

example_array = np.array([24, 16, 12, 10, 12, 24, 38, 12, 28, 24])

example_mode = stats.mode(example_array)``````

The result of `stats.mode()` is an object with the smallest mode value, and its count.

``````>>> example_mode
ModeResult(mode=array([12]), count=array([3]))``````

### Instructions

1.

We have already imported the `stats` library for you.

On line 13, delete the current value set to `mode_age`.

Find the mode of the observations in the `author_ages` array. Save the result to `mode_age`.

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