# Plot the betweenness distributions of a graph#

```import nngt
import nngt.plot as nplt
from nngt.geometry import Shape

import matplotlib.pyplot as plt

plt.rcParams.update({
'axes.edgecolor': 'grey', 'xtick.color': 'grey', 'ytick.color': 'grey',
"figure.facecolor": (0, 0, 0, 0), "axes.facecolor": (0, 0, 0, 0),
"axes.labelcolor": "grey", "text.color": "grey", "legend.facecolor": "none"
})

nngt.seed(0)
```

Let’s start by making a random exponential graph

```shape = Shape.disk(100)

g = nngt.generation.distance_rule(5, shape=shape, nodes=1000, avg_deg=3)
```

then we can plot the betweenness

```nplt.betweenness_distribution(g, logx=True, show=True, legend_location='left')
``` we can of course change various parameters and plot only the nodes

```nplt.betweenness_distribution(g, logx=False, show=True)

nplt.betweenness_distribution(g, btype="node", num_nbins="auto", alpha=0.5,
show=True)
```
• • By the way, this is the graph we’re looking at

```nplt.draw_network(g, max_nsize=5, max_esize=4, ecolor="grey", eborder_color="w",
curved_edges=True, show_environment=False, show=True)
``` Total running time of the script: (0 minutes 24.203 seconds)

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