 will continue with our health care case which is discussing oncology or cancer so we will continue with it now we have further input we have 31 columns first we had 33 columns now we have reduced 2 columns which may not be very relevant after that you have to take the unique columns in the diagnosis now you have further output now we have 8 rows and 30 columns so we are reducing the dimensions step by step that we have taken 31, 32 and now we have taken 30 now we can see the further code now we have discussed one more thing that was outlier detection outlier we have studied already that there is an average of anything where most of the data is lying and there is one thing which is outside which you can immediately recognize you can recognize it in tables, graphs and charts and even naked eyes also get to know that as soon as your average temperature of the body is 98.6 or something but as soon as it goes higher then you can immediately recognize it without looking at the thermometer similarly all other parameters you can see them in this way now you can see that the different columns or the different dimensions now they are in the form of graphs and if you remember we had seen a matplot there were two visualizations of Python libraries so using one of them this table or this graph this is in front of you in this you can see that smoothness is an assist basically it is a cancer you can also call it as a gudood there are multiple names so how is its texture smoothness is compact it is pressed, it is hard inside it there is smoothness what is that now there are different ways in particular there is a fine needle access test by injecting or you can say that in Urdu it is also called as gudood it is also called as cancer by injecting the smoothness in it they are tested so this is one way the other way is biopsy that the rest of your assist by injecting then it is tested or analyzed so this particular data is taken by FNA fine needle access test so these are the different parameters of which point symmetry is there fractal dimensions are there so all these things you can see this is average this is outlier immediately you can see that these may be cancer cells these are cancer cells which are in the human body and that which is your assist it spreads out and in this way it spreads all over the body so from this you can see how far it is on the edges and how it can be controlled another concept is benign or malign benign is the normal your assist or gudood it is not a cancer cell but malign or malign it is a cancer cell so you can see how many patients or how many patients are in this how many are in this how many are in this how many were in this how many were in this again these are two colors yellow or orange or blue they represent this this is another way of the margins and the distribution of features the margins are technical but I will try to explain because this concept is very important to understand then in this way we find the correlation the different parameters the different dimensions what is the correlation what is the degree the second stage of cancer the value of different parameters the size the surface the edges are linked so in this way you build the correlation it will also help you to further study and based on this you can do your diagnosis and the recommendation for the patient so we will move to the next session