Hello, so in all of our previous session, we had very beautiful analysis.
We have also automated our analysis by starting some blocks of code using our python function.
So in this session, I'm going to have this assignment in which I have to analyze categories of customers
on the basis of different different attributes.
These all are my different, different attributes on which I have to analyze categories of the customers
that are going to of it for a loan in a bank.
So what I have to do the very first, let me have a quick overview of what are the different different
columns in your data.
So these all are different, different columns in your data.
So let's say I'm going to define my list as, let's say, call names.
And in this, I have all the columns on which I'm going to perform analysis.
So let's see.
The columns are the very first one is exactly my security account.
So just copy from here and just based over here.
So this is exactly my very first feature.
The second one is basically my online line has been one of the things and the third one is, of course,
let me open the segment again.
The third one is account holder category and the fourth one is definitely credit card.
So Tadamon is basically account holder category.
So just copy paste over here.
And the last one is basically this credit card.
So these all of my features on which I have to perform some kind of analysis on which I have to say,
and the customers having different different categories.
So what I have to do it very first and just going to trade on this list.
So here I'm going to say for aying and just see your list, name this exactly the list name.
And on this iteration, I have to simply call a function of C one, which is known as count.
So if you are going to press shiftless tab, this is exactly the functionality of this function that
would definitely receive all these custom parameters over here.
So X, Y and you better barometer on what basis you have to split your bar or grant and then basically
you have data in which you have to postulator.
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
to split it on the basis of let's suppose the line here I'm going to see personal alone.
And once I have the spreadsheet, my data frame is basically data equals to data.
So just to execute it and you will get your beautiful calling card for all the features.
It is just returning for the last one because here is I need for all the features.
I have to set my own side so that if I'm going to say BLT don't regard you press that as well.
So you will see this is exactly Phizer.
And in this you have to set your own figure.
Let's say my silversides will be then comma five.
So again, executed and you will get your plot for each and every feature.
So this exactly is for security account.
You will see one will basically security the security account is available over there.
Similarly, this Gluba at having a personal loan and this orange bar that flows to a customer is having
some personal loan.
Similarly, in case of online, similarly in case of an account holder category with a customer having
different different categories and having different different categories in both the loan as well.
So that's a type of analysis how you can perform data by just creating on your loop.
So there are multiple ways you can go for it again and again for each and every features.
But that's the only way you can also create a function.
And in that function, you can parse each and every parameter and call that function.
So that's another handy way.
How exactly who can perform some kind of analysis on your data?
So hope you will love this analysis.
So in the upcoming session, I'm going to perform some kind of hypotheses on my data and basically I'm
also going to automate my hypothesis stuff.
So thank you.
Have a nice day.
Keep growing, keep motivating.