Hi everyone. Now we are ready to start coding. Now let's get it started. So, on screen, you will see the first Jupyter Notebook file that we created in the previous video clip. I prepared another Jupiter file that I'm going to use for this third module. So let me click it. By double-clicking, I can open that Jupyter notebook file. So in the third module, I am going to introduce basic rules and concept and I'll show you how to code in Python. So before starting coding, let me first explain the learning objectives of this third module. First, you need to get familiar with Jupyter notebook layout. I'm going to explain it first. Then primitive data types they are very important. They are building blocks, the basic building block of Python coding. That's why I'm going to explain primitive data type. And then I will also explain basic rules and mathematical operations and comparison operators that you are going to use while coding. Finally, I will also introduce a few or several built-in functions; print, type, input, integer and float. Those functions that I'm going to use while I'm introducing some examples of a coding. Now, let me explain the layer of Jupyter notebook and Jupyter Lab. In the previous video clip, I just briefly cover the key features of a Jupyter notebook. Now, let me explain a little bit in detail. So, if you look at the screen, what do you see? What you see is on the top. Here is menu bar, right? So, there are eight tabs: file, edit, view, run, kernel, tabs, settings and help. On the left side, this is the side, left sidebar, left sidebar. And on the right, this is the main working area in main working area, we are coding. And at the bottom, you will see status bar. Here is Idle. Idle mean that your Kernel is right now is on Idle state. And we are using Python 3 and saving completed. It means that your notebook current file is saved. So there are three areas. And if you want to see, if you want to make the main working area larger. You may click this file or icon. Then the left sidebar is hidden. It means that your working area becomes larger. If you want to see again that left sidebar, click this file icon. Then it will appears. Surely, in view menu, you will see this: show status bar, show left sidebar. So, you can use this menus, in order to hide or reopen those menus. So what if we unclick show left sidebar? The same thing we already did. So rather than using menu, probably better to use icon because it is easier to change. If you click file tab, there are a bunch of menus, you can choose. But probably you are not going to use a lot those menus. Probably, you use "print" sometimes if you wanna print your notebook file. "shutting down", "kernel" or "logging out" or closing this window in those case, you may use one. But in case of you are logging out, instead of clicking this one, you may choose here's "X" icon, right? We are quite familiar with that kind of opening and closing window. If you click edit, there are a bunch of functions probably you are going to use a lot of them while coding or editing your notebook file. View, some of them I already explained. So, probably I'm going to explain further as we continue, our coding. Run means that executing a cell, each block of code. A Kernel is a kind of computing function of your computer. If you make a block of code, you need to interpret that code into machine language. Then the kernel function translate the interpretation between computer and you. So restart or interrupt kernel. If kernel is continuously running and you want to interrupt, stop the kernel running, in that case, "interrupt kernel", you may use this one. Tabs, I'm going to explain it soon. Settings that I already explained: Jupyter Dark, JupyterLab Dark then the background, it becomes black. But I'm going to use the background light, so white background. So, I'm choosing JupyterLab Light. And help function is simply helpful functions provided here. So main menu are briefly explained. Also, here at the top, currently files are overlapping, right? So, there are three tabs here: launch tab, first code Jupyter file, and another Jupyter file. What about you see them at the same time, concurrently? In that case, you simply click and drag in order to divide the working area into two areas or into three areas or into four areas. So, let me show you, first click and drag if you want to see it at the bottom here. So the working area divided into two window now. But what if you want to also see 'lauch' tap? In that case, you click the second one and then drag and move to right. Then, now the whole working area is divided into three windows. Now, you see them together without overlapping. But if you want to see, eh, if you want to prefer to have the previous layout. Simply click and move, click and move. And we are going back to the previous layout. Now, one thing that I need to explain more is that here is "x" button. "x" button means that this file is saved. What about you make a change a little bit, like a [pressing tab] then I added empty space? Then, the "x" turns into a black dot. It means that your file, Jupyter Notebook file it's not saved. If you click save, it turns into "x". It means that your Jupyter Notebook file is currently saved. And here's another, a little bit bigger circle here. Currently, it is an empty hollow circle. It means that at the status, at the bottom in the status bar, is it Idle. It means that if this, a little bit larger circle on the right, if it is hollow, it means that your kernel is Idle. It is in Idle state. If the kernel is working, this hollow circle changes into solid black dot, solid black dot. It means that your kernel is busy. Simply speaking your computer is busy. So later, you will see that it changes. If you execute a block of code, it changes into black solid dot. So, by looking those two shapes, you can check the status of the computer. And then finally, I need to explain here three choices: code, Markdown and raw. Basically, we are using cells in order to code. But if you want make a kind of a note, a document, we are using Markdown. And if you want start coding, then you need to change the cell into code. Another option is raw. Raw is if you choose raw, the information contained in that cell is simply document. For example, you may write a Latex document. And when you convert your Jupyter notebook file into latex file, everything without changing it turns into latex file. So for documentation, you can use "Raw". But, in this case raw you are actually making a large or a full document. But if you want to change a cell into a document or to explain something about without having code in that cell, you choose Markdown. And here's some icons. This is the "saving" icon, this is "cutting",and this is "copying", " pasting", and "running". This one is interrupt kernel. And here's one cell, the first cell, that it is used for Markdown. So how can you see the markdown original text? Simply double-click it. Then you were, see here. Hash signs: as you add more hash the font size becomes smaller. So the largest one is the one hash. Current two, double hashes are used. But if I add one more hash, the font "Python basics" becomes smaller. And there are two under bars, those at the beginning of the sentence and at the end of the sentence. Those double under bars are used to make the font bold. And those hyphens (-) are actually items or list tool. So, if we turn this cell, so execute cell by clicking "control + enter", them, it looks pretty nice right? And here's also one more, another cell, markdown cell "1. Cells in Jupyter notebook and markdown use". So cell types that I already explained: code cell, markdown cell and raw cell. A code cell is used for coding, and on the left side, a number appears. In case of Markdown, for example, here, this is the first code cell that I created. Here's a bracket, empty bracket. Currently is empty bracket. But if I execute that cell, a number appears. An integer number appear, so, a cell number appears on the left. Markdown, Markdown is markup language for text formatting. I already showed you how to format the text. But if you want to see in detail, go to click help and here markdown reference. If you click Markdown reference, how to format document, you can see that information here, right? So, you can refer to this help document. Markdown is quite similar to HTML language, HTML is a hypertext markup language. It means that Markdown and HTML. The two editing, text editing languages are quite similar. So, in this Jupyter notebook cell, you can use HTML tag language in order to present document without using a Markdown tool. But probably a Markdown is optimized for this Jupyter Notebook. That's why it is probably better to use Markdown function instead of HTML markup language. Because they are, they are similar. And I will show you later, sometimes using HTML instead of Markdown, it is easier to resize the figure. Raw is I already explained. So here is a quiz. As I showed just a minute ago, what if, if you click this one? Oh, you can hide the cell, by clicking again you can show also the cell. So, by clicking this blue bar on the left, you can hide it or reopen it. True or False: Font size decreases with the number of a hashes. How do you think, is this statement True or False? The answer is True, that is what I already explained.