NumPy has quite a few useful statistical functions for finding minimum, maximum, percentile standard deviation and variance, etc from the given elements in the array. The functions are explained as follows −

### Statistical function

Numpy is equipped with the robust statistical function as listed below

 Function Numpy Min np.min() Max np.max() Mean np.mean() Median np.median() Standard deviation np.std()

Consider the following Array

```import numpy as np
normal_array = np.random.normal(5, 0.5, 10)
print(normal_array)		```

Output:

`[5.56171852 4.84233558 4.65392767 4.946659   4.85165567 5.61211317 4.46704244 5.22675736 4.49888936 4.68731125]			`

Example:Statistical function

```### Min
print(np.min(normal_array))

### Max
print(np.max(normal_array))

### Mean
print(np.mean(normal_array))

### Median
print(np.median(normal_array))

### Sd
print(np.std(normal_array))
```

Output:

```4.467042435266913
5.612113171990201
4.934841002270593
4.846995625786663
0.3875019367395316
```

YOU MIGHT LIKE: