Numpy

Question 1

compare two numpy arrays using
And
Or
Not

Answer 1

a = np.array([True,True,False])
b = np.array([True,False,True])

np.logical_and(a,b)
result = [True,False,False]

np. logical_or
np. logical_not

Question 2

return DataFrame rows tha satisfy two conditons - larger than 10 and smaller than 20.

Answer 2

selection = np.logical_and(df.loc[:,’my_col’] > 10, df.loc[:,’my_col’] < 10)

df[selection]

Question 3

Find is the probability to get to a step higher than 60, if the rules are:
throwing a dice:
1 + 1 step
2 + 1 step
3, 4, 5 - 1 step
6 + throw again and step up the thrown amount

you have 1% of slipping a step and you must start from 0.

You can’t go bellow step 0

Show the probability distribution and calculate the median and the standart deviation.

Each time you reset the system, the result must be the same.

Answer 3

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(123)

all_walks = []
for i in range(500) :
    random_walk = [0]
    for x in range(100) :
        step = random_walk[-1]
        dice = np.random.randint(1,7)
        if dice <= 2:
            step = max(0, step - 1)
        elif dice <= 5:
            step = step + 1
        else:
            step = step + np.random.randint(1,7)
        if np.random.rand() <= 0.001 :
            step = 0
        random_walk.append(step)
    all_walks.append(random_walk)

# Create and plot np_aw_t
np_aw_t = np.transpose(np.array(all_walks))

# Select last row from np_aw_t: ends
ends = np_aw_t[-1,:]

Plot histogram of ends, display plot

plt. hist(ends)
plt. show()

np. average(ends)
np. std(ends)