I am interpreting my code as a practice, but I don't know why the number 3 comes out from the result - numpy

Question

I am currently trying to roll a dice randomly and set up the case as below for the random_walk.
When a number of dice is less than or equal to 2, then you may go one step lesser than the number.
When a number of dice is less than or equal to 5, then you may go one step further than the number.
Else, then you may go 6 steps + alpha(roll a dice once again and add up the value to 6)
When I run the code, the result shows like this:
[0, 3, 4, 5, 4, 5, 6, 7, 6, 5, 4, 3, ....]
but I still do not understand why 3 comes out from the result.
For instance, if I roll the dice and get the number 2, then it should be 1 for my available steps. If I roll the dice and get the number 3, then it should be 4 for my available steps.
I don't see any room for 3 here, can you tell me where it came from?
Here is my code:
random_walk = [0]
for x in range(100) :
step = random_walk[-1]
dice = np.random.randint(1,7)
if dice <= 2:
# Replace below: use max to make sure step can't go below 0
step = max(0, step - 1)
elif dice <= 5:
step = step + 1
else:
step = step + np.random.randint(1,7)
random_walk.append(step)
print(random_walk)

Answer 1

Your current logic is to add/minus 1 from your previous step, hence getting 3 when your previous step is 2. Seems like it should be
random_walk = [0]
for x in range(100) :
step = random_walk[-1]
dice = np.random.randint(1,7)
if dice <= 2:
# Replace below: use max to make sure step can't go below 0
step = max(0, dice - 1)
elif dice <= 5:
step = dice + 1
else:
step = 6 + np.random.randint(1,7)
random_walk.append(step)
print(random_walk)
By the way your question is not related to pandas or dataframe so you should remove these tags.