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Halaal, before going ahead in the last session of this project, let's have a quick recap of what we

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have done in our project.

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So we have done lots of analysis, lots of conclusions, project, lots of things like that since the

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last session.

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What we have to do, we have to automate all these things.

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So in this session, we have to what we have to do, we have to visualize this confounders activities,

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recover this and all these things.

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But you have to automate all these things.

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It means you have to create a function that what we have done in the very first session.

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But here we have to write such an advance function so that we back to each country.

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I just need statistics with respect to us.

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So once I will pass us to that function, I will get into entire trend of active recovered whatever

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feature I will do.

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So that first, let's have a quick preview of data frame.

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So this is exactly what it I feel like.

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I just need this additions or in data statistics with respect to us or Brazil.

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So it means here you have four parameters or you can say you have to consider four features, the confirmed

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cases that you will recover and your active cases.

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And you have to plot all these things with respect to that.

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It means you have to consider five features, Solectron, define some columns or you can select which

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defines and functions over here.

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So here I am going to say my function is getting word my country underscored like, say, visualisations,

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whatever function name you want to define what our parameter, this function will receive.

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I'm going to define it later.

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Now, what we have to do, let's say I have to visualize with respect to us, it means I need a separate

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data frame with respect to this, with respect to this USSI, for this what I have to do, I have to

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simply create a filter over here.

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So here I am going to say that if I have to say what our data frame I have in this data frame, I have

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to simply put a condition as D of control reason equally close to us or whatever country name you are

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passing on here.

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So the very first bad and we do this function will receive the exact data from the second one.

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What is your country name.

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So and here I am going to say this country is close to country.

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So this is exactly your entire filter.

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So I have to just pass this filter in my data frame.

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So I'm going to say D.F. of all these stats.

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So it will exactly then be some better frame, say I have to store it in some data or data.

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Exactly.

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That data frame with respect to that particular country.

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Now, what I have to do in this data, in this data, which is exactly the frame, I just need five

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features, which are my date, confirm that record active.

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So for this time going to say data of location.

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And here I need all the rules and definitely some features.

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The very first feature I'm going to say, which is exactly my date.

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The second feature, I'm going to say my conformed data that I'm going to say, which is exactly my

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debts.

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And the fourth one I'm going to say my record.

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The fifth one I'm going to say, which is nothing but my active, which is over here, if you will see

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here you have but you will notice over here where I have all these features.

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So these all audio features is exactly in your group.

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Unaskable data is exactly the data frame that you have created in the very first session of your project.

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So over here you have all these parameters, your date, your gun phone cases, your that's your record

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and your activities.

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So in this, you have to access all these features.

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So if I'm going to say let's say this is my entire data frame, I'm going to name it as Lexia data to

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it's all up to you, whatever name you want to assign.

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So this is my data to on which I have to do some analysis.

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So the very first letter I have to need, I create some subclass so that if I have to import some basic

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model, some, some, some of this over here, so that if I'm going to say from my tautly so from this

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slightly I have to say I have some, some module which is exactly my supplier.

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So I'm going to say from Pratley dot subclass I have to import my make underscores subplots.

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After what we have to do, I have to import some of that since I'm going to say import Lochley dot graphs

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underscore objects as a goal.

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So just executed.

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Now what I have to do, I'm going to say I have two very first caller func.

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Which is exactly makes applause, because on each and every plot I have to plot four confirmed cases,

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I had to plot for tax cases, I have to cut for the court cases and I have to plot four active cases.

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It means I need four guards.

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So here I am going to say, if you will stab, you will look at the entire documentation on this function.

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The number of roles, a number of columns you want to see, Rose, is nothing more like, say, one,

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and let's say columns are nothing but four, because here I have four features that I have to visualize.

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So here now and here you have some custom parameters over here, but you will see the parameters exactly

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your subplot under the score title, which is exactly this one.

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So here I'm going to say this parameter is nothing but subplot and titles.

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And here you have to say you have to just assign your values to the very first value you have to assign

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to your very first thought is exactly the same confirmed.

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And the second one is, let's say, active and active.

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This is active.

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The third that you have to assign to third thought is exactly or recover.

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The full value that you have to assign is your that once you would assign all these estos what you have

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to do, you have to Estoril subplots over here to examine the in my figure, then what you have to do,

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you have to slice each and every feature on this figure.

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So for this I'm just going to say fig dot add underscore Chris here I have a function and in this case

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what I have to do, I have to visualize this date and this confirmed.

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So here I'm going to say I have to use my scatterplot so go dot scatter.

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And here I have all the custom parameters over here in this scatterplot you will check out.

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So in this name, I am going to say here I have something which is exactly my Gunflint after it on X-axis,

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let's say I'm going to say it do nothing would be of date.

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And this name is exactly or you can see it's my title.

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And this XRX is nothing but the fourth date because you have to plot this back to date after doing all

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this stuff.

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So what I'm going to do, I have to set some value with this back to my Y-axis.

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So on Y-axis, I'm going to say dissolve all confirmed.

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So I'm going to say it's not B of it's data to.

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Yeah, because data two is your current data frame on which I have to do some sort of analysis.

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I'm going to say it is my data to and here I have to say it is exactly my confirmed.

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Once I have all these stats over here, what we have to do, we have to simply copy this, because I

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have to do this thing for my each and every features with respect to conform with respect to that,

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with respect to my record, after we have something with respect to my active this time I'm going to

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say this is let's say with respect to my dad.

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So I'm going to say with respect to my dad.

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So here I'm just going to say it does nothing but deal of that.

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So here you have to say you have to just modify this column name.

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So I'm going to say this is nothing but my div of that.

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And after doing all these things, you have to do for your record as well.

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So this is done, all these things.

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And one more thing you have to pass here.

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I'm going to say this is Stets is going to visualise, let's say, on row one or column one.

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So here I am going to say this is nothing but my role equals to one and definitely column equals to

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one.

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And in a similar way, I have to just copy this, all these things.

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And this time I have to say this is with respect to column two and this time this is with respect to

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my column three.

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And this time this will be my respect to column.

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So that's it.

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And this time what I have to do, basically, I have to visualize it for this record cases as well.

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So I'm going to say it is my record and this time it is nothing but data to of record.

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And the very last one is exactly my active cases.

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So I'm just going to say it is my active and this is nothing but my data to of active.

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So once I have all these stats, let's say I have.

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To assign subtitles for this, I'm going to say dot update on the school layout and in this, let's

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say, I have to assign some own custom height of my finger to say hi to close to six hundred and let's

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say it equals two pounds and whatever you want.

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So vertical two thousand, you can set eight hundred twelve hundred as well.

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And I have a parameter you can say tight in this context and in this context.

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I'm going to say that was says recorded cases of then I have something which is exactly my placeholder

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and I'm going to say this placeholder will get replaced by my forward function.

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And here I'm going to say format of country, whatever I will pass in my function.

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So that is exactly how I have to mind my analysis.

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And here I have some more parameters than you can play with that like system template.

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And there are tons of parameters.

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It's all up to you.

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So let's say my template nothing but let's say plotted on a score not to make my a little bit use of

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interactive.

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After doing all these things, I have to simply showcase my figures for they just go on.

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That's it.

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Now I have to simply execute all this does.

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Now what I have to do, I have to simply call this function.

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I have to just pass my door frame, which is exactly group data.

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Aleksi, I have to call this function for Brasi that say just execute the cell and you will see what

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here this is.

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You're amazing.

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And the statistics of BRAZZI, look at how this kind of confirmed cases.

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Exactly.

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Triangles, active cases.

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This is a trend of recovered cases.

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This is a trend of death cases in a similar way.

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You can call from any of the country whatever you want.

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Let's say for us, whatever country you want, let's say us or India or whatever country you want.

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So this is exactly the trend with respect to us.

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You will see how this that fluctuates or hit in a similar way.

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You can call for us, say, for Colombia for this year, for any other countries in the world.

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So that's all about the it's all about this project.

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Hope you love this session very much and how actually I have automated all the stuff over here.

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So in a similar way, you can automate all of these things by just thinking some logic, by just writing

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your own logic order.

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So that's all about this project.

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Hope you love it.

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Thank you.

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Have a nice day.

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Keep learning.

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Keep growing.

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Keep practicing.