Anh-Thi DINH
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### Python 3

Posted on 05/09/2018, in Infomation Technology.

This note continues the first python note. Check out the full list of notes in python.

## Random walk

### Visualize the walk

The current walk depends on the previous one.

import numpy as np
np.random.seed(123)
random_walk = [0] # initial

for x in range(100): # 100 walks
step = random_walk[-1] # take the last step
dice = np.random.randint(1,7) # from 1 to 6

if dice <= 2:
step = max(0, step - 1) # prevent back to less than 0
elif dice <= 5:
step += 1
else:
step += np.random.randint(1,7)

random_walk.append(step)

import matplotlib.pyplot as plt
plt.plot(random_walk)
plt.show()


### Distribution

• Question: random walk go up/down (of tails) but what is the chance to go up to 65, for example?
• Idea: run 100 times the algorithm of random walk to get the last “tails” and then see the distribution of this final tail and guest the chance. Using histogram to visualize the distribution.
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