Welcome to clinical data management program using SAS. In this video we will be exploring our data that we had imported In our last video that is our disease data. So in order to explore our data, we will be using two procedures that is proc contents and PROC PRINT. First we'll do prop contents. So first let us know what is proc contents procedure. proc contents procedure is used to display the descriptive portion of the data set.

That is it displays the data dictionary that is what is the name of our data set. So these are the different features that are displayed in proc condenser and many other features that are displayed but I'm just giving the example or idea or what is a descriptive version of the data set. So the name of the data set where it was created, the number of observations that are there in the data set number of variables that are there in the data set, whether there is any label to the variables or not labeled means whether there is a secondary name to a variable and not whether there are new formats, whether they're early in formats, what are the different data types of the video tables, which are numeric data types which are calculated. So these are third data dictionaries. So the descriptor portion of the data set of the data dictionary of the data set is displayed in proc contents procedure.

So let's do the proc contents procedure on our disease data sets. So we'll do prop contains data equals CDM CDM dot disease. So let's run this code. So this is our descriptive portion of the data set or data dictionary where you have the data set name, the observations member type variables, engine indexes created when was created when was it last modified observation length, deleted observations protection data set type label, detailed presentation encoding compressed, soldered weathered solder note data as it beats ice Number because it pages cause data offset data page max observations per page observations in First Data page number of data set repairs filename release created host created the alphabetical list of variables and attributes a number of variables that are there over the radio was extensive string each character This is its lead format in format available equals numeric variable This is the format informant average commute children daily intelligence use disease data birth education employment status gender ID marital status military service zip code see you have ancestry as a character variable employment status as character variable education as a character variable gender as a character variable ideas activity with marital status this activity will increase services activity when you have available vehicles average commute children that is number of children leading to reduce and zip code.

So are you and date of birth you have Six numeric variables and you have around eight categories. So total six numeric variables, and each have two variables total number of variables are 40. So this is a data dictionary or the descriptive portion of the data set. Now, let's do the proper procedure proper procedure is used to display the data portion of the data set, where the difference between the PROC PRINT and the original data set is your original data set. You do not get a serial number column or observation column. When you do PROC PRINT on the data set observation column and the serial number column gets added to your results.

So PROC PRINT basically displays data portion of the data sets. The exact data set comes in form in a tabular form in a result viewer with the observation column as the leftmost column so let's do property on our disease data set. So, see, this is a proper procedure the exact data set has come with observation number these are the variables you have ID gender, date of birth zip code, province status education marital status children ancestry, average commute, interest rate available vehicles military service and diseases that the patients are suffering from. So, basically this data set has the is deals with a patient details data. It has displayed all the details about the patient. It has got all the patient reports it has got thousands of them observations Okay, so in this video we'll be doing in here in our next video we'll be doing how to filter this data.

So how to filter data that is filtering data we'll be doing a little bit discussing in our next video. So for now, let me end this video over here. Thank you Goodbye. See what for the next week you