We have a for statement where we'll introduce the name e as the variable name.

If we wanted a more exact answer, we need to use floating point division.

So I don't want my_sort() to return a copy of the list. I want, after I call my_sort() on a , if I then refer to a

So it gets the smallest and then the next smallest and then the next smallest until the list is exhausted.

People would normally write out these almost Tic Tac Toe like board.

Inserting a new element into the list and it has to stay ordered now because this is an ordered list that involves running to the list or possibly jumping around in the list.

Now we're reassigning what p points to to the original value of p, which is this, concatenated with the list 1.

So we're going to represent that by having our chart be a dictionary that maps from numbers to lists.

You're going to multiply pi with pMiss.

Now I'm going to add some debugging to see if I've gotten the right answer.

Once we've gone through every character in our source string, we return the output list.

So you don't get confused.

I can give you a list.

I can get you a full list.

In that example, I kept track of both of the best and the second best, and then it was running through the list.

We're going use this function is_list, and if p is a list, then what we are going to do is create a new list, an empty list.

If the person we're searching for is in the genealogy dictionary, we're going to do what we described previously.

So here I have the solution.

That by using mutation, by having lists that could contain other lists or any other kind of data we want, we can build very complex data structures, and we can do lots of interesting things.

If that course is in the dictionary for that hexamester, then we're going to append it to our offered list.

This is going to create a new list, because that's what the plus operator does with lists.

So this is option B.

The answer is 3, here's why the first statement creates the list with the elements 1, 2, and P refers to that list.

Assign it to a new variable that I make up called mu. So this is now inside the variance I now know the mean.

Now to get all the subsets, which is something called a power set, if you're familiar with set theory, we run it through this other function called all subsets that takes a

So to solve this problem we're going to modify partition a little bit.

So here are a few examples.

And finally the len operator that takes a list as its input and produces an output number that is the length of the list.

I'll get you a list.

Add a new task to the list.

Remove a task from the list.

Let's write the function that does that.

It also can be a recursive definition.

We've initialized the variable spy to hold the list containing 3 elements that are numbers 0, 0, 7.

Displays the high score table

What I'd like you to do is implement this function_gmaps image.

List of calls?

Okay, let's do insertion first. It does an insertion in this list. That insertion takes Θ(k).

And there's tradeoffs to doing it this way.

For every element we see, we increase the sum by 1, and if it's a sublist, we're going to do deep_count on the sublist.

The commands I have been using is I iteratively construct with a for loop the data set.

The basic idea I'll pursue is that I keep a list of notes that I wish to investigate further or, as we call it in search, expand.

If they equal the course we're looking for, we're going to append it to a list of our results.

Add new Raw files to the list

Add new RAW files to the list