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In this lecture, I'm going to talk about Jupiter notebook.

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Occasionally I get this strange question from students asking why I don't do things in Jupiter notebook.

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Let me explain why I think this is strange.

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Firstly, it's my position that it's completely unnecessary and actually doesn't change anything to

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use Jupiter notebook or not.

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Let me repeat that.

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Using Jupiter notebook is exactly the same as not using Jupiter notebook.

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There's no difference other than the fact that it looks different.

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In other words, the screen is a different color.

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Obviously such a difference is trivial in this lecture.

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I'm going to demonstrate how that's the case.

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One major reason I dislike Jupiter notebook is because it causes too many students to be unaware of

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how Python really works.

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If you're only comfortable inside notebook and when you see Python code in a text file or anywhere else

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and you get scared or intimidated, that's not good.

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That python code that's in the text file is exactly the same as what would be in the notebook.

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There's really nothing scary about it.

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Programmers working at real jobs eventually need to write code that's going to be deployed and run automatically.

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In other words, your final code is going to sit in a python file that runs by itself without you open

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a notebook.

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So if you're going to have any hope of using these skills in a real job, you had better be comfortable

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with writing Python code outside of Jupiter notebook.

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You would also better be aware that there's actually zero difference between writing code in a group

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and a notebook and writing code in Python or the console.

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Here's one example I like of how you might use Python in the quote unquote real world.

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Let's say you write a script that emails your boss to tell him you're going to be late for work.

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And let's say you don't actually want to send this email manually, but you want it to get sent automatically

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every Friday morning so that your boss doesn't yell at you for coming in to work late after you party

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too hard Thursday night.

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Well, that's very simple.

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All I have to do is on my server, create what's called a crosstab in it.

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I just enter the code for when I want this command to run.

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And then to the right of that I specify the command that I want to run.

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That's just python space.

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And then the script name, as you can see, it's simply how you would run this Python script from the

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command line.

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And now every Friday at nine forty five a.m., this script is going to send the same email to your boss.

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Tell him you'll be late.

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Well, let's not get off track here, the point of this is you really don't want to be using Jupiter

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notebook for something like this.

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I think one perceived advantage of Jupiter notebook is that you can see the results of intermediate

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calculations.

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However, this is merely a perceived advantage and not a real advantage because you can do the exact

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same thing even when you're not inside notebook.

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Firstly, as I'm sure you've seen by now, I Python also print out the results after you enter a command,

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ie Python is called a Reppel, which stands for read eval print loop.

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And that's generally what they all do, no matter what language you're in.

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So whether that's Python, Ruby, P or any other language, the keyword here is print.

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Why is that?

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Well, one of my golden rules for writing and debugging code is when in doubt, print it out.

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I can't tell you how many times I've gotten a question on the Q&A when it could have been easily answered

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by inserting a print statement into the existing code.

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Anyway, what's the point of this long discussion about printing things out?

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Well, it's that if you think Jupiter Notebook is the only program that helps you do this, you need

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to expand your horizons a little bit.

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You should, in fact, always be doing this.

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If you're not using an abundant amount of print statements while coding, you are not doing it right.

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Remember, programming is not philosophy.

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You're not supposed to be running a program in your head that's like trying to do long division in your

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head when you have a calculator in your hand.

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So just by printing things out, you can be more efficient.

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Stop trying to guess what a program will do and just let the program itself tell you what it's doing.

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The key takeaway here is you should always be printing things out.

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The fact that Jupiter notebook shows you the result of each block of code is not simply a happy surprise.

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But another important lesson here is that if you want to use Jupiter notebook, there's absolutely nothing

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stopping you from doing so.

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In other words, using Jupiter notebook is 100 percent compatible with everything we are already doing.

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In fact, if you recall, your goal in these courses is not to run my code, but to write your own code.

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And of course, since it's your code, you can write it however you want, including Jupiter Notebook

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and the rest of his lecture.

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I'm going to prove to you that you can take any script from our course repository, which we know runs

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in the console, because that's how I always demonstrate it and show you that this exact same code runs

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in Jupiter notebook.

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Let's begin.

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OK, so let's say I am in the folder Numpty class, and I'm interested in the code inside classification

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example that PI, as you can see, what I have right now is this code inside a text editor.

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Now, if you're not aware of what a text editor is, it's just a program that shows you the contents

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of a text file and lets you edit those contents.

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It's the ideal program for writing code.

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Now, occasionally, if you're writing in a language like Java or Swift, you might want to use an I.D.,

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but even then, it's totally optional.

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These days I prefer to write Java in a plain text editor like Sublime Text as well.

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In any case, normally one does not need to use an idea for writing Python code now about using a notebook.

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Well, let's start up a Jupiter notebook.

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So I'm going to go Jupiter notebook.

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All right, so now I've got Jupiter, a notebook running, so I'm going to start a new notebook.

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Also, notice that we started the notebook in the same directory as the relevant Python file, so that's

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something you want to keep in mind for the future.

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Now, at this point, what I'm going to do is I'm going to prove that everything in this Python file

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works exactly the same in the notebook as it does in the console.

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So let's start with the imports.

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Let's grab this one to.

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All right, paste that in.

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Run it so everything's fine so far.

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Now let's load in the data.

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OK, we've loaded in the data now, I'm not sure what its type is, so I can check it by using the type

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function.

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So let me try that.

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Cool, so I get Escala and utils, that bunch, so that's the type of the variable data.

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Now, previously, you recall that we did this example in Python, but as you can see, the result is

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the same in Jupiter notebook.

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Alternatively, if you wanted to run this Python file in the console, so you wanted to type.

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Let's say.

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So let's say you wanted to type in python classification example, that pie, then you could just add

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some print statements if you wanted to show those same lines while this file was running.

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Now, I'm not going to go through such elaborate detail for the rest of this example, since you've

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already seen it, so let's just get through the rest.

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Line by line.

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Let's say I want to check out the keys in the data variable.

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OK, looks good so far.

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Let's check the shape of the data attribute.

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OK, looks good so far, check the targets.

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OK, still, what we expect the target names looks good.

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Target shape, it should be 569, yeah.

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And let's check out the feature names.

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OK, that's the same as well.

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Now let's do our train to split.

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OK.

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Now let's instantiate and fit our model.

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All right, now let's check the train score.

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And the test score.

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All right.

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Now let's see how we can make new predictions.

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How have you assigned to a variable, it doesn't print the result.

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But if you have an expression, then it does print the result.

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So those are some predictions, and this was an alternative way to calculate the accuracy of the predictions,

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so we get the same answer as before.

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And we also have this other example where we can use a neural network to do the same thing.

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So let's build the model, train it and print the train score.

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And let's print the test score as well.

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All right, so everything works the exact same way as it does without using notebook.

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Now, another thing I could have done was I could have just taken this whole thing and copied and pasted

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it in and run it, so that's another possible thing you can do.

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But the downside of that is you don't get to see the intermediate outputs.

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But again, that's what print statements are for.

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All right, so what can we conclude from this exercise?

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Well, we can see that this code runs exactly the same inside group in a notebook as it does everywhere

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else.

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That's why I always say python code is python code, no matter where it is.

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If you want to use you put a notebook to run the course code.

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There's absolutely nothing stopping you from doing so.