Welcome to clinical data management program using SAS. In this video we will be doing how to we will be doing the filtering portion of our data. That is we'll be discussing how to filter our data you can also see how the subsidy subsidy. So, for filtering data, we are going to use the same procedure that is really the proper procedure. First filtering that we are going to do is we will be displaying only those observations there are diseases equal to multiple sclerosis. So let's see how to do that.

I hope you remember that our library the library that we had created was CDM. And the data set that we created was disease we had already created our data set. We had already imported our data set in our last videos using the new segment and import statement and we are using the same data set to explain the concept of filtering data. Here we are going to display only those observations there are diseases equal to multiple sclerosis. So let's see All blue we are going to use the proper procedure, PROC PRINT data equals CD or disease where disease equal to multiple sclerosis. So, we want only those observations to be displayed where disease is equal to multiple sclerosis and colon and then we use a statement to filter our data to subset our data.

So, this let me close this result viewer if we run this book, see only these many observations are there. That is these many number of patients out there who are having multiple steps. These are the observation numbers of each and every patient. You want to know that how many observations were displayed, you can just see the lock there. Hundred 30 observations that are displayed from the CDN or disease data set. So there are 130 patients who are suffering from this disease multiple stress.

The next type of filtering that we are going to do is we are going to filter or we want to display those observations where diseases equal to multiple classes or diseases equal to skin cancer or diseases equal to hypertension. So for that also we are going to use the same procedure the disrupted doctrine later equals CDM dot disease. The disease in multiple sclerosis in Cancer Institute helps you to incident is basically substantive or it is like multiple sclerosis, or skin cancer that is you can write in one line and does a shorter statement. That means rather than writing or rather than using or incident is obviously preferable than writing one line as a shorter statement c hyperedge. So, we want to display those patients data, those observations are diseases equal to multiple sclerosis or skin cancer or hypertension then let's run this code title hypertension, multiple sclerosis or skin cancer.

Those observations are really district who are suffering from are those patient details are displayed for suffering from skin cancer or hypertension. A number of observations are 644. So out of me, my data had actually thousand observations out of that 644 observations had fulfilled our condition had locations are suffering from multiple sources of skin cancer. The next type of filtering that we are the data using observation numbers that we say we want to display the observations from 11 to 15. We are going to display how we want to display those observations starting from observation number 11. That is from 11th observation, observation.

So for that also we will use the same procedure PROC PRINT data only our keywords will be different Cochrane data was CDA, but disease my starting observation number I'll be writing using the keyword first OBS first OBS will still ever that is to start displaying from observation OBS equal to 15. The OBS is a keyword right the ending observation which will be the last observation of my report or dissolve your starting position up here and this is denoted with those two Ending observation will be free which will be denoted by ups. And then. So let's run this code to see from the 11th observation, observation. So from the 11th patient if th patient details are are displayed, you see the law from 11th to 15th letter proven 40 observations, over 40 observations are displayed in Arizona. So in this video we'll be doing in our next video, we'll be discussing about how to format our data that is formatting data for now.

Let me end this video over here. Thank you. Good bye See what for the next video.