### Generate some random data to work with

First, we'll generate some random numeric data to work with in the form of a Numpy array

```
import numpy as np
data = np.random.randint(100, size=(3, 5))
```

### Calculate the `mean`

We can use Numpy's `np.mean()`

function to calculate the mean value in the range of values in the `data`

array:

```
mean = np.mean(data)
print ("The mean value of the dataset is", mean)
```

`Out: The mean value of the dataset is 61.333333333333336`

### Calculate the `median`

Numpy also has a `np.median`

function, which is deployed like this:

```
median = np.median(data)
print ("The median value of the dataset is", median)
```

`Out: The median value of the dataset is 80.0`

### Calculate the `mode`

Numpy doesn't have a built-in function to calculate the modal value within a range of values, so use the stats module from the `scipy`

package.

```
from scipy import stats
mode = stats.mode(data)
print("The mode is {}".format(mode[0]))
```

`Out: The mode is [[55 6 56 35 7]]`