## Libraries & Dataset

We will start by importing the necessary libraries and loading the dataset.

Since bubble plots requires **numerical values**, we need to have quantitative data in our dataset.

```
# libraries
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# create data
df = pd.DataFrame({
'x': np.random.rand(40),
'y': np.random.rand(40),
'z': np.random.rand(40),
})
df.head()
```

x | y | z | |
---|---|---|---|

0 | 0.487913 | 0.640856 | 0.685197 |

1 | 0.904584 | 0.029056 | 0.289917 |

2 | 0.186066 | 0.909341 | 0.576339 |

3 | 0.560585 | 0.119788 | 0.857088 |

4 | 0.335864 | 0.779507 | 0.092400 |

## Bubble plot

A bubble plot is very similar to a scatterplot. Using matplotlib library, a bubble plot can be constructed using the `scatter()`

function. In the example, the following parameters are used:

`x`

: The data position on the x axis`y`

: The data position on the y axis`s`

: The marker size`alpha`

: Transparancy ratio

```
plt.scatter(df['x'], df['y'], s=df['z']*1000, alpha=0.5)
plt.show()
```

## Going further

You might be interested in:

- how to change colors, shape and size of the bubbles
- how to map bubble colors with a 4th variable