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Halaal, before going deep down into the session, let's have a quick recap of what we all have done

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in our previous session.

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So we have basically performed data cleaning and data processing on our data so that we have our pre-process

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data, so that we will perform lots of analysis on data and we will come up with some beautiful insights.

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That is exactly our main goal.

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So in this session, we have this assignment in which the very first analysis we have to perform is

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where do the guest come from?

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And after it we have to perform if patient analysis in which I have to use some kind of maps, some

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kind of global maps, or if I'm going to use for some particular country, I can use some particular

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country map.

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So we have to come up with beautiful insights at the end, because that is exactly our main goal.

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Yeah.

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So, yeah, let me remind you, this is exactly Jupiter notebook and very focused what we have to do.

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Let's see if you will observe in this in this data stream in this hotel, you have two categories,

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the resort.

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And second one is exactly your city hotel.

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It means, let's say you have to perform separately for a resort hotel.

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Yeah.

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What what if a guest or what are a guest that that comes to the resort hotel and in a similar way,

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you can perform this analysis for city order.

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So it means you need to date a friend so that if I'm going to say data of hotel, data of hotel and

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in this very first condition, I have to mention is exactly my resort hotel.

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So here I'm going to say this is nothing but.

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So either you can just copy from here and I'm just going to paste over here.

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So this is exactly my very first condition.

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And my second condition is exactly let me let me put this in my very first condition.

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And after it my second condition is exactly make sure that booking must not be canceled.

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So in this, I'm going to say here I have a feature which is exactly is canceled, which is exactly

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this one.

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So this has to 011.

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So whereas you miss the booking is not going to cancel, one means that booking is going to be canceled.

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So my very second filter is right into my very second condition is exactly my data of and here I have

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to exit.

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This is on the so-called canceled column and here I have to say this must be Mitsue.

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So this is exactly my entire filter.

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So what we have to do, we have to pass this filter in my data frame, that set of what you can do,

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you can copy this and you can paste over here this time.

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I have to say, this is exactly for my city hotel.

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So I'm going to say this is exactly for my city hotel.

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So here I'm going to say this is my auditorium and let's say this is exactly my city doorframes.

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It just executed.

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And if you are going to call, let's say, ahead on your resort, you will observe.

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This is a beautiful done film that you exactly need in case of resort.

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Similarly, if on this city, I'm going to call ahead, you will see this.

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Is that in a frame with respect to city hotels?

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So let's see if I'm going to call my ship on this resort.

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Now, you will see over here, it has that much number of rules and that number of columns.

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So let's say I have to perform this analysis.

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Where do the guest come from in both my resort as well as in my city hotel for this?

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What I am going to do, let's say that you can use your eye chart or definitely you can go ahead with

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your map or any other map.

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So let's say I'm going to use my pie chart over here.

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So let's say for better visualization, you guys can go ahead with our popular model known as Blakley.

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So if you haven't installed your A system, I'm going to say you can install this using PIP installed

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properly so it will install you in your environment, whatever environment you are using.

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So after it, I'm going to say I have to just import this and I have to import this broadly as well

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as some submodular from the Spurtle.

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So I'm going to say, which is exactly my graph underscore or be G.S., which is exactly this one second

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one, and I have to create its allies as well.

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But let's say it's Aliya's I'm going to create is nothing but let's say cool.

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And after what we have to do, let's say to plot your map, you have to import something known as I

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plot.

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So I'm going to say from my this plot, I have two very first.

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Import my submodular, which is exactly my offline model, because you have to make sure that your graph

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must be visible in your offline mode because to to showcase your visual impliedly, you have to move

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either offline or online.

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So if you have to visualize your graph in your offline mode, you have to import this offline model

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and form this offline.

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You have to import something known as a plot because you have to visualize this graph in your Jupiter

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notebook.

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So after what I'm going to do, I'm just going to say import floridly DOT Xpress.

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And from this I have to create a Aliya's, which is nothing but my de'ath to just execute it.

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Now, what I'm going to do, let's say in this resort, in this resort, if I'm going to access my country

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and on this country, if I'm going to call my, let's say, value consulate to get a pound of each and

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every country, you will see with respect to this country, it has that much number of guests with respect

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to this Dibia.

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It has that much number of guest selects.

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If you have two axis country, you guys can let's say you guys can call Jostein.

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That's all there.

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So I'm just going to say do nothing with my index.

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So just executed.

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It is a list of all your countries.

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So I'm going to say to that thing with my labels.

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So this is exactly my values with respect to each and every country.

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So I'm going to store it in value, just execute it.

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And from this you have a function which is exactly by and if you will shift plus tab over here, you

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will get exactly the documentation.

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What are the parameters that you can play with that over here?

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So you will see it has a parameter, which is exactly my labels.

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So here I am going to say my label is nothing but the labels that I have defined over ABL.

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And after that what we have to do in this values parameter.

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I have to assign my whatever values I have given it.

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When I'm going to wear my mouth on my Veysel, I have to visualize data in the form of the label and

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presented for this.

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I'm going to say my Hoover in four in four is nothing but label plus percent.

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So this is exactly the data that you are going to see whenever you are going to hoover your closet on

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your visual.

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And let's say I am also going to say I want some text.

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So I'm going to say my text in four is nothing but let's say value after it, I'm going to store it

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and let's say Grace just executed.

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And now what I have to do for visualize this graph, you have to just pass it in your iPod plot, any

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formal list.

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So I'm just going to say the straight that's it.

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Just executed.

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It will take a couple of seconds and it will give you some beautiful picture visual.

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So this is exactly that pie chart result for which I'm talking about.

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If you are going to cover your mouth, you will see BRT has that much percentage of guest and is is

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this GBR has that much percentage of guests, whereas this E.S.P has that much percentage of this.

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Similarly, over here, you will see with respect to each and every country, you have some mark assigned

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over there, let's say if you have to perform a spatial analysis instead of this pie chart.

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So very first, I need that data so that I can visualize it on my quadruplet map because quadruply map

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in such used cases will be very handy.

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Aurier selected very first.

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I'm going to see data of very first.

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I have to add some filter which is exactly is concerned equally close to zero selected.

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This is exactly my filter and I have to pass this filter in my data.

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So now we have the data.

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And on this data, if I'm going to add to this country and on this country, if I'm going to call this

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value council or if I'm going to execute it, you will see you have all this stuff with respect to each

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and every country.

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That's I have to convert it in some way to things for this.

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You guys can call this an index just executed.

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It is exactly the data.

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Let's say I have to do some modifications over here.

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I have to play with this this column over here.

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It's very first.

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I have to store it somewhere else.

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So let's say I'm going to say it is nothing but my country on a score wise on that score, Peter just

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executed after it.

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What we have to do very first, we have to access this data frame on this.

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I will say this columns is nothing, but the very first column is exactly my country.

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The second column I have to assign is exactly my number of guest number of guests with respect to each

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and every country.

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So just execute it.

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And if I'm going to access or whatever and if I'm going to call.

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You will see this is exactly that, the frame that you need, that you need.

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So here I'm going to say, look, I have to perform I have to perform my core map over here.

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So far, this is what I am going to do in this fix, which is exactly less of your plotline.

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You have a function known as quadruplet map and just press shift tab.

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You will get all the documentation of this function.

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What data needs latitude and longitude, location, location mode and all these different different

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parameters as well.

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So the very first parameter is exactly what exactly is the frame?

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I'm just going to say my famous country is providing its data, the second parameter, which we have

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to take, which is exactly my location.

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So in this location, I'm going to say very first I have to exit this.

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And here I'm going to say whatever country I have over here, this is exactly my location.

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So this is exactly my location.

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And after it, what I'm going to do, let's say I have to assign some color.

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Let's say I have to assign color on the basis of number of guests.

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It means more the number of guest, darker the color will be.

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So here I am going to see countries called Weidensaul Data.

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And here I have to say my number of guests, which is exactly this one.

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And after it, what we have to do, let's say whenever I'm going to hover my mouse on my callback map,

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I have to I have to visualize some things here I'm going to say over underscore name.

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And in these very first, I have to exit the data frame.

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And on this, I'm just going to exit this country.

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So I'm going to exit this country unless I have to assign some titles over there.

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So that's my title is Nothing But Home.

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Country of guest home.

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Country of home, country guest.

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So this is exactly my title.

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So just execute it.

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And this is your beautiful this is a beautiful coral map that you exactly need, and this is exactly

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the color bar, which definitely gives some meaningful insight.

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So if you are going to go over your mouth, I have to zoom in.

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Let's zoom in.

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So let's see.

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This is exactly that concrete, which is my France that has that much number of guest.

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Similarly, over here somewhere here you will see here is a country which is exactly BRT and it has

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a maximum number of guests.

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It means this Portugal has the highest number of guests.

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So if I have to if I have to conclude this result, if I have to go to this visual, then I can say

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few people from all over the world are staying in basically my resort and cities hotel.

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But most of the guests are basically from Portugal and other countries in Europe, because you will

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observe from us you don't have that much number of guests from India.

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You don't have that much number of guest from paparazzi.

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You don't have that much of guest workers in case of European countries who have a higher number of

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guests.

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So that's a type of conclusion, how you get fat from your.

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So it's all about decision hopes you will love it very much.

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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.