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# Python random numbers in Jupyter

For many analyses, we are interested in calculating repeatable results. However, a lot of analysis relies on random numbers being used. In Python, you can set the seed for the random number generator to achieve repeatable results with the `random_seed()` function.

In this example, we simulate rolling a pair of dice and looking at the outcome.

The script we are using is this:

```import pylab
import random
random.seed(113)
samples = 1000
dice = []
for i in range(samples):
total = random.randint(1,6) + random.randint(1,6)
dice.append(total)
pylab.hist(dice, bins= pylab.arange(1.5,12.6,1.0))
pylab.show()
```

Once we have the script in Jupyter and execute it, we have this result:

I had added some more statistics. I'm not sure ...

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