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Long before going deep dive into the session, let's have a quick recap of what we have done in our

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previous session.

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So no previous session, we have this distribution, which is nothing but a distribution of price of

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each and every room type tonight and per person.

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So this is exactly the distribution that we have come of it in a similar way.

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We have this analysis, which is exactly a room price per night over the air with respect to my resort

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hotel as well as Cost City Hotel as so in the session.

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We have this assignment in which I have to find what is our distribution of nights spent at hotels by

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different different market segment and hotel type Lexcen.

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Let's see if I'm going to call our pad on my date of now.

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You will see over here, this is the data fee that you have to consider for your analysis purposes.

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So here you have a column, Naem, which is exactly something known as market segment, which is exactly

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this one, which is exactly this one.

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And this is exactly your second column, which is my stays in weekend.

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And it means it means you have to find a distribution of each and every market segment or you can say

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you have to find distribution of it stays in weekend night in each and every market segment.

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So for this, we have a very handy plot.

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So I'm going to say asanas dot box plot.

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And in this box plot, I have to play with different different parameters.

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So here I'm going to say on X axis, I have this I have this feature.

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So here I'm just going to do copy paste and basically on y axis or y axis, I have this column, so

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I have to just copy.

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I have to just paste over there.

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Let me remove the special character and after it, what I have to do, I have to say what exactly is

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my little frame, which is my data and simple.

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I had to split this box plot on the basis of this hotel, on this basis, all on the basis of this hotel

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and after it.

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What I have to do, let's say I have to set my own window site for this.

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I'm going to say Paltalk figure.

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And here I have something which is exactly Fixit and I have to assign my physical side of that Cifas

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Kincumber 10.

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So after what I have to do, I have to just execute it.

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And this is exactly your box plot with respect to each and every different different market segment

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you will see with respect to this stock market segment.

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You have this distribution, whereas with respect to all these different, different kind of market

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segments, you have this kind of situation.

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So from this, if I have to conclude that, I can say almost most of the groups are normally distributed.

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Yeah, some of have some skewness.

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You will see this this data point, which are exactly outliers.

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It means some of have some positive skewness in my data.

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So if looking at this box plot or I can see looking at the distribution, I can see most people do not

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seem to prefer to stay at the hotel more than one weeks.

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And you will observe over here in case of resolved people are going to stay more.

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It means it is always that whenever people go to resort hotels, they prefer to stay more.

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So that's a basic conclusion, how you can fetch from your data.

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So let's go ahead with our second problem statement, which is I have to analyze preference of guest

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what they basically prefer.

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So I have to analyze their behavior, what basically the PAFA.

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So here I'm going to say let's say, well, let me show you a thing.

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So very first, I have to excuse my middle column.

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And on this, I have to say I could just call this the loop, because you will see over here this this

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Beeby has highest count.

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It means most of the guests are basically going to prep for this meeting.

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Let me show this thing.

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Let me show this thing.

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Why am I pie chart?

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Or you can use some handy personal picture like me, use Pockley.

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So I'm going to say B X dot by and in this, if you will, plus tab, you will get all your stuff.

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So here what I'm going to do very first, I have to pass my Netafim, which is exactly my data.

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After what I have to do here in my names, I have to just copy this and I have to just paste over there

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and.

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In this index, I have to say DOT index of this one, and after what I have to do, are likely brashest

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plus tapu check all the parameters.

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It has names.

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So let me just do some modifications.

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And this is exactly my names.

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It is not index.

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So here I'm going to say it is nothing, but it is just my values.

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And if you will shift crosstab, you will see here you have name, here you have values.

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And let's say I have to use something known as donor chart.

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So for this I have to just blow this whole parameter.

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And in this whole parameter I have to set some value.

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Let's say I have to set a value of five five.

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And if you will, execute the self executed and this is your beautiful donnacha and if you will hold

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your mouth, you will see all these have this discount.

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So you will see this this breakfast has that much higher ground.

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And if you have to conclude from this visual, you will see this is exactly on a chart.

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And almost 90 percent of the bookings are definitely reserved for breakfast.

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So that's the type of analysis that's type of conclusion you can fetch from data.

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You can also consider your pie chart instead of this chart.

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You can also consider Barcia, but you done it and by will play a very handy role whenever you have

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some left number of Category four.

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The idea behind when to use a lot means that that's all up to what scenario text all up to what use

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we have.

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So I hope you love the session 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 practicing.