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So I come back to this lecture about Jupyter Notebook.

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I would say Jupyter Notebook is the most easy way to learn and to use Python, especially when you are

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beginning.

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So we just click on launch and is Jupyter Notebook Panel here?

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And what it does is it opens up your standard browser, which for me is Google Chrome.

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So here you just start in your personal directory.

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You can, of course, navigate here to different directories.

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But what I'm going to do is I will just create a new file right here in this directory.

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And here you can select the Python kernel that you want to use.

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So if you just have installed Anaconda, as I explained in the previous lecture, you will just have

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Python three here and nothing else.

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But maybe you have several installations of Python.

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So maybe here are more of these kernels.

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So I select Python three.

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It opens up a new tab and a new notebook, which we can save, and in this case, it will be saved right

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in this directory.

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And it's titled Untitled.

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Of course, you can also give it a name.

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And unlike in the previous lecture, I've used the command line tool.

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You can now go ahead and calculate just some basic stuff.

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Yeah, and eight plus three gives 11.

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Just the first comment here when I just press enter.

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It will not run the cell, but adds new lines.

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So to run the cell, I have to click Shift Plus enter.

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So what is special about Jupyter Notebook?

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Well, maybe you can see it already.

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We have something called cells.

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So here we have a first cell which contains this code and the output, and then we can just make or

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write and in the second cell or even add new cells.

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And here we can write additional stuff.

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For example, we could write is equal to one.

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Then we must, of course, run the cell and then we can write two times a plus one.

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But we can also write several commands in the same cell.

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We could, for example, then write three times a plus.

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And in this case, it just gives you the last output as the output of the cell.

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So what else can we do?

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We can delete this, of course, again, and then we can also redefine a in this cell.

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The bottom here and then we can click back in here and rerun the cell, and then it gives us a different

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result.

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So the important thing here is that it really matters in which order you run the cells.

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And this is very different from conventional program.

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For example, if you have some C code, for example, you just have one file and it runs from top to

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bottom.

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And here, if you have such a notebook, this is not necessarily the case.

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You can run these cells in any order you like.

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And for example, we can click here on kernel and we can restart and clear the output.

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So this will basically delete all of our results that we have gotten.

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And when I now just run this cell two times a plus one, it will give me an error because the variable

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A has not been defined yet, even though here a is defined in the previous cell.

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But we didn't run it yet, which you can see at the fact that this is here still empty.

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So now I run it, and now it gives us a results.

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So if you have a long code, it's very tedious to click in every cell and run every cell after another.

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So what you can do then, is you can focus on the click here, restart and run all.

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So that's sometimes a good idea to restart the kernel, to get rid of all of the old stuff and then

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run all cells.

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And then you see one to three four.

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All of these cells have been executed.

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So what additional information that I have to tell you is that these Jupyter notebooks are not the native

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Python files, which you can see at the fact that this this file here is labeled Untitled Todd IPY and

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B and a python file is labeled dot p y.

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So this is something else.

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It's a Jupyter notebook file.

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And the only difference between Jupyter Notebook File and the Python file is that a Python file is just

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a text consisting of lines of code, and the Jupyter Notebook file contains these individual cells,

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which then themselves contain Python code.

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So this makes it really easy to test stuff and to change variables and really do some quick programming.

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And this is why we are going to use this here in the majority of the course.

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But of course, if you want to write a very long code, or for example, if you want to run your code

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on the supercomputer cluster, then of course, it's probably better to use a conventional python file

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where you just have all of your lines of codes and you do not have these cells.

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But as I mentioned for learning, I think Jupyter Notebook is perfect.