My basic approach would be to add a GROUP variable for the range of values and a DATTRMAP data set since that is the easiest way to set multiple plot options .   Depending on your current ODS style the thickness numbers you specified may not have much visible difference.   Here is my approach: data toplot; do x= 0 to (6*constant('PI')) by 0.01; y=sin(x); if 0 le x lt (2*constant('PI')) then band=1; else if (2*constant('PI')) le x le (5*constant('PI')) then band=2; else band=3; output; end; run; data sinattrplot; input id $ value $ linecolor $ linethickness; datalines; sin_base 1 red 1.5 sin_base 2 lime 2.0 sin_base 3 green 1.0 ; proc sgplot data=toplot dattrmap=sinattrplot; series x=x y=y / attrid=sin_base group=band; run; Note that the names of variables in the attribute map data sets are set for the actual attributes involved and change between discrete, DATTRMAP data set, and ranged attributes, RATTRMAP data set. ... View more

Which interval does 2*pi actually belong? The way you have stated the first two intervals with closed end it is defined as belonging to both intervals. One of the intervals needs to be open.   @hellohere wrote: Say here is one single line y=sin(x). need to plot [0,2*pi] with color=red and thickness=1.5 [2*pi,5*pi] with color=lime and thickness=2.0 OW color=green and thickness=1   How to do it?!   And what attributes for x less than 0? Is that included in the OW, which I have to guess means "otherwise"? ... View more

Your original data structure is probably best for determining "most recent" visit. Sort the data by patient id and descending visit date. The first visit will then be the most recent. Intervals as well using the Intck and Retain functions. Proc sort data=Pt_visits out=sorted_visits; by patient descending visit_date; run; data visit_interval; set sorted_visits; by patient; retain most_recent; format most_recent mmddyy10.; if first.patient then do; most_recent=visit_date; date_interval=0; end; else date_interval = intck('day',visit_date,most_recent); /* drop most_recent;*/ run; RETAIN keeps the value of the specified variable(s) across the data step boundary until reset. In this case using BY patient allows us to use the FIRST.<by variable name> construct to identify the first patient record and set the most_recent visit date from the sorted values. INTCK yields interval counts between two date variables. The order of the the two dates is important. Please read the documentation. Date and/or time intervals are usually best worked with the functions INTCK, for returning interval between, and INTNX to increment dates. You can get intervals such as week, month, quarter or year (and others) for example as needed and let the staff at SAS do the background programming.   Unless there is something else needed then the VisitN variable isn't needed though could be build in the step that uses the sorted data. Note that if multiple FACILITIES are to be used then you may want to sort by patient and facility and use similar logic using First.Facility to hand the most recent and interval per patient facility combination if needed. Or a treatment code, doctor or similar seen by the patient, etc.  Uncomment the Drop statement if the most_recent visit variable is not needed later.   Often making "wide" data such as your transposes is not needed. If you are careful with your variable names you can use  MAX (of varname: ) which will use all of the variables whose names start with VARNAME . So if the only variable starting with listed characters are what you need the : list indentifier simplifies the code and will handle the results of Proc Transpose output without having to change the code. ... View more

@Stephen_Shell  Best practice for this forum is that you start your own post and possibly reference this one as related. Readers wont have to wade through the original posts to find the details of your question and responses to questions about your problem. Also when a solution is reached you can indicate which answer fits your problem. Also, you want to post code in a code box opened with the </> or "running man" icon on this forum. Pasting code in the main message will get reformatted by the forum software. As posted, your data step reading the data throws errors because column 22, which is supposed to part of the Company from your input statement actually includes the start of the Debt variable and Town starts in column 31 not 39. The forum likely removed repeated blanks. An example from the log running your posted code: 1 Data Company; input Company $ 1-22 Debt 25-30 Number 33-36 Town $ 1 ! 39-51; 2 datalines; NOTE: Invalid data for Number in line 3 33-36. RULE: ----+----1----+----2----+----3----+----4----+----5----+----6---- 3 Ice Cream Delight 299.98 2310 Holly Springs Company=Ice Cream Delight 299. Debt=2310 Number=. Town=rings _ERROR_=1 _N_=1 NOTE: Invalid data for Number in line 4 33-36. 4 Ice Cream Delight 299.98 2210 Holly Springs Company=Ice Cream Delight 299. Debt=2210 Number=. Town=rings _ERROR_=1 _N_=2 NOTE: Invalid data for Number in line 5 33-36. 5 Ice Cream Delight 299.98 2310 Holly Springs Company=Ice Cream Delight 299. Debt=2310 Number=. Town=rings _ERROR_=1 _N_=3 NOTE: Invalid data for Number in line 6 33-36. 6 Ice Cream Delight 300.98 2310 Holly Springs Company=Ice Cream Delight 300. Debt=2310 Number=. Town=rings _ERROR_=1 _N_=4 NOTE: Invalid data for Number in line 7 33-36. 7 Ice Cream Delight 300.98 2510 Holly Springs Company=Ice Cream Delight 300. Debt=2510 Number=. Town=rings _ERROR_=1 _N_=5 NOTE: Invalid data for Number in line 8 33-36. 8 Ice Cream Delight 300.98 2510 Nolly Springs Company=Ice Cream Delight 300. Debt=2510 Number=. Town=rings _ERROR_=1 _N_=6 NOTE: Invalid data for Number in line 9 33-36. 9 Ice Cream Delight 300.98 2510 Nolly Springs Company=Ice Cream Delight 300. Debt=2510 Number=. Town=rings _ERROR_=1 _N_=7 NOTE: Invalid data for Number in line 10 33-36. 10 Ice Cream Delight 300.98 2510 Nolly Springs Company=Ice Cream Delight 300. Debt=2510 Number=. Town=rings _ERROR_=1 _N_=8 NOTE: The data set WORK.COMPANY has 8 observations and 4 variables. NOTE: DATA statement used (Total process time): real time 0.06 seconds cpu time 0.00 seconds Hint: at least for examples on this forum it may be better to use simple input statement with numeric values instead of specifying columns.   Then provide a few more details as to what exactly you need for output. You say your problem is "similar" to the topic in this thread but are not particularly clear about the differences other than mentioning "51 variables". There would be no way for us to determine what an "error" might be without rules defining what an error is. Differences might be easier using Proc Compare which is designed for comparing two data sets (or one set with itself).   I would submit that a variable such as "debt" (or price, balance, number in inventory etc) is very likely to be time dependent and comparisons likely should be compared based on some date measure. If you are looking for potential differences in Number (an address component? store indentification? descriptions help) and City where you expect only one value of Number per City for a given country a diagnostic tool that may be helpful is proc freq with the list option: Consider: Proc freq data=company; table company *town *number/list; run; The company data set would not require sorting though if very large sorting might improve the run time for the proc freq. The LIST option gives a count of the combinations of the variables on a single line and you can tell how many values of NUMBER you get for each combination of Company and Town easily.  You could also inlcude table company * number * town / list; Which would clearly show if number was associated with multiple towns.   I had a data source that had, and required reporting on by, city, county and Zipcode. However the data entry folks were more than a bit sloppy and would enter the county in the city field, or the State in the County field. The state name was also the name of one of the counties and several county names were the same as cities, a not uncommon occurence. So I used this technique to find counties not associated with the city name and vice versa. And the Zipcode because those would often have reversed digits or other inconsistencies. This step using proc freq was after use the SASHELP.ZIPCODE data set to identify likely errors involving Zipcodes. Caution: Zipcodes may cross county lines and frequently do in rural areas. ... View more

Typiclly SYSCC will be 4 when a WARNING occurs. There are some interactions with the ERRORCHECK system setting and some specific statements such as LIBNAME , FILENAME and %INCLUDE statements. You should read the online help for SYSCC for details.   These statements are likely just one reason that setting your own global macro variable might be a good idea. ... View more

For what very little it may be worth, I noticed that using the USB connection on the front of my desktop is much slower to charge my cell phone than that using one of the ports on the back of the machine as well ... View more

@palolix wrote: Yes, but I would like to have the starlines like in the first graph, they look weird in the second graph.   Thanks   They look like they have the radius value you requested to be plotted. If you want to plot a different radius value then you need to provide one. Or remove the values from the plot set close to 0 if I understand what appearance you want.   ... View more

The second graph is using 0 at the center of the graph. So I am not sure what you expecting/wanting that is not occuring. ... View more

I ran your code as posted and the log for the Gradar part shows: NOTE: Processing beginning for CHART statement number 1. WARNING: Negative or zero value encountered for FREQ= variable. WARNING: These observations are not processed. NOTE: 27 nonmissing values of texture_label are processed. NOTE: Radar categories are sorted in the order determined by the classification cell corresponding to DM_range=15-20. WARNING: One or more overlay values is missing. NOTE: 67846 bytes written to C:\Users\Owner\AppData\Local\Temp\SAS Temporary Files\_TD16884_DESKTOP-C36D7SF_\radar.png. 68 quit; NOTE: PROCEDURE GRADAR used (Total process time): real time 0.36 seconds cpu time 0.15 seconds You may want to consider if these warnings about values are affecting the plot.   I am not sure what you want when you say you want the "plot to start from 0".   If you want 0 at the center of the plot you will have some lines spike inward has you have values in plot your plot set like 0.94, 1.79 and 1.53 which with the scale of values you show will approach the center. So perhaps a better description of what you actually want for appearance will help.   I will admit that it has been a long time since I used GRADAR regularly, like 1996, and then mostly for windroses as I was dealing with wind directions. Are you sure that you want to use a FREQ variable? There are a few places where non-integer Freqs behave a bit oddly and that may be the cause of the warnings.  I also seem to remember that having numeric values was best for controlling orders of appearance.   ... View more

Another board that I spend time on regularly that has nothing to do with software at all also has seen about an 80% decline in traffic over the past 4 or 5 years.   Maybe YouTube and other sites are just plain sucking up peoples time. ... View more

@RandoDando wrote: I have this code, but I am unsure it will work as intended.  data Part1 Part2 Part3 Part4 Part5 Part6 Part7 Part8 Part9 Part10; set LARGE_SET; id = mod(_n_, 10); if id = 0 then output Part1; else if id = 1 then output Part2; else if id = 2 then output Part3; else if id = 3 then output Part4; else if id = 4 then output Part5; else if id = 5 then output Part6; else if id = 6 then output Part7; else if id = 7 then output Part8; else if id = 8 then output Part9; else output Part10; drop id; run; Once upon a time we had a graduate student in the shop I worked asked how to split the "large" SAS data set into smaller pieces, though in his case it was to separate individual variables, because when it exported to Excel to do summary statistics the result was taking more than 4 hours. I asked what he was attempting and showed him that asking for the exact same summary statistics he was requesting using SAS with the existing SAS data set executed in 1 min 15 seconds.   Things like this are why we ask what your further processing involves.  Also remember that if the original data set order changes you cannot reproduce the same results if you partition it this way again.  ... View more

@Tom wrote: @RandoDando wrote: Thanks. I have a followup question: will Proc compare treat two identical date values in different formats as equal? Yes.  The value stored is not impacted by the method you have attached for how to display the value. An anecdote from data imported from Excel: I have had values that appeared as dates in Excel that had a decimal component that was kept on import. Since the SAS date formats only use the the integer portion you might not see that decimal bit until you try to match the dates and get unexpected results.    IIRC this occurred with an Excel column that contained mixed date only values and datetime values as Excel uses the decimal portion to store time of day information.   ... View more

@thomasn528 wrote: Thanks but no, that's not it. The error message claimed the *prior* nested sort hadn't worked. and had even yielded a differently sized data set!! (as SASKiwi noted.) The "rnd" is listed last, it's needed there, it's the item to be ranked in PROC RANK -- and this step had never malfunctioned before, in dozens and dozens of program runs-times-loop-iterations. Having re-run the same program on the same data without error this time, this now seems to me to have (indeed) been some kind of resource shortage/malfunction caused by running two demanding programs at the same time on my little pony of a PC. The highlighted is not what the log shows. It says that the set that Proc Rank attempted to use did not match the required sort. Not that the sort hadn't worked. Pedantic perhaps but there is a difference.   Macros and reusing of same data set names is always something to be a bit cautious of as a failure of one element can leave a data set from a previous run. I often remove "temporary" data sets at the end of a loop so this doesn't occur (and to keep disk space under control sometimes).     ... View more

    @hein68 wrote: Hello.  I wrote some proc tabulate code that is working for me with continuous outcome variables but not categorical outcome variables.  I would appreciate any help you can provide. The data is a long file where all IDs have a pre record and some IDs have a post record. Here is the code.  I cannot drop it in, sorry. proc tabulate data=data format=6.1 nosep order=internal;   class group / descending; class time; var contvar; table contvar*(n mean std nmiss),group*time; run; How would I get a table with n and % for categorical variables by group (sorted ascending) and time (pre and post) sorted descending? Thanks!   Since your Proc Tabulate code does not use any variable called ID why do you include " where all IDs have a pre record and some IDs have a post record. " That bit of trivia apparently has no obvious connection to this problem. If you are discussing the role of a variable then name the variable.   If you want Group to be ascending then why did you have the option /descending for the Group variable? The default for class variables is "ascending" but if you have a FORMAT applied to the variable(s)  things may appear as if they are not ordered.   Strong hint: provide some example data in the form of a working data step and if your actual data has custom formats applied then the definitions of the formats, or at least enough to work with the example data. ... View more

One caution with using Excel files as libraries to read data into SAS: They must be clean.   That means column headings only one cell starting on the first row, all the data in a column the same, i.e. numeric with the same type (all dates, all currency, all simple numbers, no mixing) or character. If the Excel is actually more of a report appearance then likely the library approach will lead to much frustration.   If the Excel has two or more column headings then the column will likely be treated as character. If there are one or more blank cells above the headings you will likely again have the column treated a character (and possibly records with missing values).    At one point in my working career I would say that nearly 20 percent of my work time was cleaning up Excel "data" that the creators could not, or would not, keep consistent in any structure. When the Excel library was introduced in SAS I had one project that it seemed a reasonable solution to the read the frequent files provided. Lasted 3 weeks before the first file change.   ... View more