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Hello, so in all of our previous session, we had very beautiful analysis.

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We have also automated our analysis by starting some blocks of code using our python function.

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So in this session, I'm going to have this assignment in which I have to analyze categories of customers

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on the basis of different different attributes.

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These all are my different, different attributes on which I have to analyze categories of the customers

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that are going to of it for a loan in a bank.

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So what I have to do the very first, let me have a quick overview of what are the different different

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columns in your data.

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So these all are different, different columns in your data.

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So let's say I'm going to define my list as, let's say, call names.

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And in this, I have all the columns on which I'm going to perform analysis.

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So let's see.

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The columns are the very first one is exactly my security account.

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So just copy from here and just based over here.

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So this is exactly my very first feature.

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The second one is basically my online line has been one of the things and the third one is, of course,

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let me open the segment again.

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The third one is account holder category and the fourth one is definitely credit card.

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So Tadamon is basically account holder category.

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So just copy paste over here.

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And the last one is basically this credit card.

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So these all of my features on which I have to perform some kind of analysis on which I have to say,

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and the customers having different different categories.

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So what I have to do it very first and just going to trade on this list.

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So here I'm going to say for aying and just see your list, name this exactly the list name.

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And on this iteration, I have to simply call a function of C one, which is known as count.

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So if you are going to press shiftless tab, this is exactly the functionality of this function that

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would definitely receive all these custom parameters over here.

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So X, Y and you better barometer on what basis you have to split your bar or grant and then basically

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you have data in which you have to postulator.

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So now I'm going to say on X I have to receive data from this loop so X equals to I and then I have

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to split it on the basis of let's suppose the line here I'm going to see personal alone.

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And once I have the spreadsheet, my data frame is basically data equals to data.

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So just to execute it and you will get your beautiful calling card for all the features.

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It is just returning for the last one because here is I need for all the features.

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I have to set my own side so that if I'm going to say BLT don't regard you press that as well.

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So you will see this is exactly Phizer.

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And in this you have to set your own figure.

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Let's say my silversides will be then comma five.

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So again, executed and you will get your plot for each and every feature.

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So this exactly is for security account.

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You will see one will basically security the security account is available over there.

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Similarly, this Gluba at having a personal loan and this orange bar that flows to a customer is having

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some personal loan.

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Similarly, in case of online, similarly in case of an account holder category with a customer having

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different different categories and having different different categories in both the loan as well.

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So that's a type of analysis how you can perform data by just creating on your loop.

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So there are multiple ways you can go for it again and again for each and every features.

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But that's the only way you can also create a function.

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And in that function, you can parse each and every parameter and call that function.

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So that's another handy way.

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How exactly who can perform some kind of analysis on your data?

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So hope you will love this analysis.

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So in the upcoming session, I'm going to perform some kind of hypotheses on my data and basically I'm

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also going to automate my hypothesis stuff.

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So thank you.

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Have a nice day.

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Keep growing, keep motivating.