# Chapter 5 Applications

Some *fun* applications are demonstrated in this chapter. To be added …

Here is an example of a simple **random-walk** plot using the **Python Matplotlib** library, and its classic plot formatting and colors. We start with the typical imports:

```
import matplotlib.pyplot as plt
'classic')
plt.style.use(import numpy as np
import pandas as pd
```

Now we create some random walk data:

```
= np.random.RandomState(0)
rng = np.linspace(0, 10, 500)
x = np.cumsum(rng.randn(500, 6), 0) y
```

And do a simple plot:

```
;
plt.plot(x, y)#plt.legend('ABCDEF', ncol=2, loc='upper left');
plt.show()
```

Now let us take a look at how it works with the Python **Seaborn** library. As we will see, **Seaborn** has many of its own high-level plotting routines, but it can also overwrite **Matplotlib**’s default parameters and in turn get even simple **Matplotlib** scripts to produce vastly superior output. We can set the style by calling **Seaborn**’s `set()`

method. By convention, **Seaborn** is imported as `sns`

:

```
import seaborn as sns
set() sns.
```

Now let’s rerun the same two lines as before:

```
# same plotting code as above!
;
plt.plot(x, y)'ABCDEF', ncol=2, loc='upper left');
plt.legend( plt.show()
```