Question code from datacamp I don't understand

[fad3r]

Hi,
I don't need any help coding anything I just really am confused on this code:

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import numpy as np np.random.seed(123) tails = [0] for x in range(10) :     coin = np.random.randint(0, 2)     tails.append(tails[x] + coin) print(tails)

It prints out: [0, 0, 1, 1, 1, 1, 1, 1, 2, 3, 3]

Supposedly this is an example of somehing called a "random walk"

I am a little confused on the tails.append line and the output. I am confused on why there are 11 items and how this manages to ignore the heads aspect. It only tracks tails. I didn't find the video very clear at all.

Thanks

[Larz60+]

tails = [0] this creates a list with a single element of 0.
When you append, it adds additional values.
start with tails = []
Then change:

1	tails.append(tails[x] + coin)

to

1	tails.append(coin)

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>>> import numpy as np >>> np.random.seed(123) >>> tails = [] >>> for x in range(10): ...     coin = np.random.randint(0, 2) ...     tails.append(coin) ... >>> tails [0, 1, 0, 0, 0, 0, 0, 1, 1, 0]

[fad3r]

What is tails[x] doing I guess?

I thought that it is coming from range tails[1], tails[2]

Is that to move us through to tails[10]?

And the idea is since zero is heads it never gets added but since tails is 1 we increase by 1 each time?

[buran]

it tracks how many times (total) you get tails when flip a coin 10 times in a row. so you have random number 0 or 1 - 1 means you get a tail, 0 - a head. Every time you get 1 (i.e. tail), it increase the last element by 1. you get 11 elements because you start from 10 and then toss the coin 10 times