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Halaal, before we dive into this session, let's have a quick recap of what we all have done in all

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our previous session since the last session we have analyzed.

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This is exactly my trend for the room price per night for resort as well as for city hotels.

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And we have performed lots of analysis on data, which is exactly this box.

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We with nothing but my distribution of price of different different room categories with respect to

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my resort hotel as well as with respect to my city hotel.

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And we have this beautiful coral map as well and this beautiful pie chart as well.

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So in this session, what we have to do, we have this assignment.

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And the very first problem statement is we have to analyze a special request done by the customers.

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So let's hear let's see what I'm going to do over here.

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Let's say very first, I just need an overview of the frame, how exactly my data looks like.

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So I'm going to say nothing but just DataDot Haddo just executed.

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And this is exactly my data frame that I need.

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Now, what I am going to do, I'm just going to count the different different categories that exactly

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occurs in total number of special request for this.

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What I'm going to do, I'm just going to call this counterpart function.

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And here I have to just say data of total, which is exactly total underscore.

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You can press that as well.

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And this is exactly that feature that you need.

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And if you are going to execute it now, you will see this beautiful count plot over here.

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You will see five or has a list count, whereas the zero zero has the highest count.

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It means most of the customers are not going to give me some special request.

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Or you can say almost 50 percent of the bookings do not have any special request.

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So this is exactly that conclusion from this veto.

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So let's go ahead with our second problem, a statement in which we have to create a pivot table of

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our relationship between what exactly the relationship between this special request and this cancellation

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of the bookings.

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So what I'm going to do very first, let's hear let's say what I am going to do over here.

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I'm just going to say very first, I have to group my data on the basis of total number of especially

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good so far.

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This what I'm going to do, say I'm just going to check what definition columns you will see.

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These are all my different different columns.

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Now I'm just going to say data grabby.

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And here very first, I have to group my data on the basis of this total of special requests.

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I'm just going to copy paste.

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It's nothing fancy after it.

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I have to group my data again on the basis of this is cancel the feature here.

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I have to just pasted after it what I have to do.

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I have to aggregated for this.

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I'm going to say dot org and here whatever you have to pass, you have to pass in the form of dictionary.

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So I'm going to say here is my dictionary.

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So now what you need you need are what are my total number of customers, total number of customers

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that has this that has this zero special request that has this one number of special request with respect

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to this cancellation as well.

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So here I'm going to say let me let me just copy this.

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Let me just copy this and let me just based order.

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So on this, I have to basically call my column function.

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So here I'm going to say I have to just discount that said, if I'm going to execute it.

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Now, you see, this is a beautiful estates with respect to all of the things you will see when your

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total number of requests this month and why that is just cancel or not, then you have this much.

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Let's say let's say I have to create a pivot table of this.

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So what I'm going to do, I'm just going to select the very first I have to rename my column names.

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I have to rename my column names from this total of a special request to LATISM count.

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So for this, I'm going to say I have to just call this rhenium function, which is exactly in my PARNAS

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module.

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And here I have to say I have to pass my date in the form dictionary and I have to say a total of a

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special request.

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And after it you have to rename this.

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Let's say you have to rename it to my second column, whatever you want, whatever column name you want

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to assign, it's all up to you after what I'm going to do, like say I'm going to say I have to store

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all these things.

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So very first, I'm just going to say on this, I'm just going to call my honor stack over there to

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convert.

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All these trials in some type of pure, David, so just execute the sale and this is that beautiful

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steps that you exactly need that you will see over here, you will see over here with respect to that

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much number of customers.

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You have that much count who has this canceled booking.

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And this is those customers who did not have canceled booking and they did not give any special request

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to hotel staff.

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So this is exactly my relationship.

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What I need.

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Let's say I have to plot this data.

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So I'm going to say I have to store it somewhere else.

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I'm just going to store it and let it be looked.

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And if you are going to print your paper, you can print it as well after it.

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What I am going to do, I'm just going to say pivot, dot plot.

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And here I have a parameter which is exactly my kind parameter.

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And in this kind parameter I am going to say I just need my bar plot.

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So here you have to say just execute it.

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And this is that beautiful bar plot that you exactly need with respect to all these different, different

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special request and whether your booking is canceled or not.

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So this is that visual that you need.

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And from this visa, you can say it is just my relationship between my special request and my cancellation

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booking status.

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And you will observe over here almost half of the bookings without any special request have been canceled.

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And and in that half of them, almost another half of them have not been canceled.

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So that's a conclusion.

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That's a meaningful insight that you can get from this visual as well as from the stakeout.

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Hope you love the session.

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Thank you.

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How nice to keep learning.

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Keep growing.

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Keep practicing.