How can I make this code attached run faster?

[guest1994]

Hi,

I currently have a SAS project that takes around 3 days to run- I'm looking to reduce this time as much as possible by (hopefully) making the code more efficient. Is there anything I can change to make this code run faster?

/* Means analysis using a format for each variable */
%macro Percentile_Summary;
	/* If the count is populated, then run the percentile summary */
	%if (%eval(&COUNT_ANLY_1.) ne 0) %then %do;

		/* Kill means datasets in the WORK tempspace that may exist from previous runs */
		proc datasets lib=work nolist;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 1/4";
			delete 	Percentile_Summary Anly_1_Summary;
		run;

		/* Run proc means for individual variables, using custom made formats for variable */
		%do k = 1 %to &COUNT_ANLY_1.;
			/* Create format for use in the proc means step below */
			%Percentile(dsn=refi_lib.&Refi_DSN., var=&&ANLY_IND_1_VAR&k..);
			%sleep(60);		/* Test whether the system should go into sleep mode or not */

			/* Analysis: PROC MEANS function for all numeric continuous data, at fine and total level */
			PROC MEANS DATA = ranked_out noprint missing chartype COMPLETETYPES;
				SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
				VAR &&ANLY_IND_1_VAR&k..;
				CLASS VAR_SEG;
					OUTPUT OUT = Anly_1_Summary (rename=(VAR_SEG=GROUPING))
						N= N
						NMISS= NMISS
						MIN= MIN
						MAX= MAX
						MEAN= MEAN
						SUM= SUM
						STD= STD /noinherit;
			RUN;

			data Percentile_Summary;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";

				/* Set original datastep and additions - N ne 1*/
				%if &k. ne 1 %then %do;
					set Percentile_Summary Anly_1_Summary;
				%end;

				/* Create variables and set lengths/labels. Set first batch of data available */
				%else %if &k. eq 1 %then %do;
					/* Assign Lengths and Formats*/
					LENGTH ID 4 VARIABLE $32 GROUPING $11;

					/* Assign Labels */
				    label
						ID="ID Number"
				        VARIABLE="Classification Variable Name"
				        GROUPING="Classification Grouping"
					;

					/* Initialise with missing */
					GROUPING = .;
					set Anly_1_Summary;
				%end;

				/* Create column with relevant variable name and ID */
				if ID = . then ID = &k.;
				if VARIABLE = "" then VARIABLE = "&&ANLY_IND_1_VAR&k..";
				if _TYPE_ = "0" then GROUPING = "Overall";
			run;
		%end;

		/* Left join label onto dataset */
		Proc SQL;
		Create table output.Percentile_Summary (label="Expln=&Expiry_Months.m" Alter="IB") as
		Select 	 A.*
				,B.Label

		From Percentile_Summary 				A
		Left Join output.Contents_Summary 	B
			on A.Variable = B.Variable
			;
		Quit;

		proc datasets library=work nolist;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 4/4";
			delete Anly_1_SUMMARY ranked ranked_out;
		run;
	%end;
%mend Percentile_Summary;

/* Macro to calculate the cutpoints for percentiles */
%Macro Percentile(
				dsn /* Libname and dataset name - lib.dsetname */,
				var /* Variable name to create percentiles on */);

	/* Rank variable in question to create percentiles*/
	proc rank data=&dsn.(keep=&var.) out=ranked ties=low;
		SYSECHO "Formatting 1/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		var &var.;
		ranks Var_Rank;
	run;

	/* Sort data into ascending order using the ranked variable created above */
	proc sort data=ranked;
		SYSECHO "Formatting 2/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		by Var_Rank;
	run;

	/* Add counter and determine splits for percentile calculation */
	DATA ranked;
		SYSECHO "Formatting 3/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		/* Set non-missing values then missing values, so missing values are at the bottom*/
		SET ranked(where=(Var_Rank ne .)) ranked(where=(Var_Rank eq .));

		N = _N_;							/* Counter */
		IF (Var_Rank eq .) THEN N = .;	/* Set N to missing for missing values */
	RUN;

	/* Step to create the segmentation for percentiles. See formatting in monitoring program */
	PROC SQL;
	SYSECHO "Formatting 4/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
	CREATE TABLE ranked_out(drop=N Var_Rank) AS	
		SELECT 	*,
				CASE	WHEN N = . THEN 'Missing'
						WHEN N <= CEIL(MIN(N) + (MAX(N) - MIN(N) + 1)*  1/100 - 1)  THEN '0% to 1%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)*  5/100 - 1  		THEN '1% to 5%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 10/100 - 1  		THEN '5% to 10%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 25/100 - 1  		THEN '10% to 25%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 50/100 - 1  		THEN '25% to 50%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 75/100 - 1 		THEN '50% to 75%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 90/100 - 1  		THEN '75% to 90%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 95/100 - 1  		THEN '90% to 95%'
						WHEN N <= FLOOR(MIN(N) + (MAX(N) - MIN(N) + 1)* 99/100 - 1) THEN '95% to 99%'
						ELSE '99% to 100%'
	  		END AS VAR_SEG			/* Percentile Segmentation variable */		
		FROM ranked
		;
	QUIT;
%Mend Percentile;

/* Macro to create 1-way summaries */
%Macro one_way_summary(
	dsetin /* Library and dataset name - lib.dset_name */,
	varlist /* List of vars to feed through the proc freq procedure */,
	dsetout /* Output library and dataset name - lib.dset_name */,
	type /* ANLY_IND value */)  /mindelimiter=',';

	%sleep(60);		/* Test whether the system should go into sleep mode or not */

	/* Count the number of variables within the table matching the ANLY_IND = &type. criteria */
	Proc Sql noprint;
		SYSECHO "One Way Summary - ANLY_IND &type. - Step 1/4";
		Select Count(*)
			into :COUNT_ANLY_&type.
		From output.Contents_Summary
			where ANLY_IND=&type.;
	Quit;

	/* If the count is populated, then run the one way summary */
	%if (%eval(&&COUNT_ANLY_&type..) ne 0) %then %do;

		/* Housekeeping - Delete datasets */
		proc datasets nodetails nolist;
			SYSECHO "One Way Summary - ANLY_IND &type. - Step 2/4";
		    delete &dsetout.;
		quit;

		/* Create population format */
		%if (&type. in (1, 5)) %then %do;
			proc format;
			value POP_FMT (multilabel)
				. = "Missing"
				other = "Populated"
			;
			run;
		%end;
		%else %if (&type. = 4) %then %do;
			proc format;
			value $ POP_FMT (multilabel)
				' ' = "Missing"
				other = "Populated"
			;
			run;
		%end;

		*loop through variable list;
		%let i=1;
		%do %while (%scan(&varlist., &i., " ") ^=%str());
			%let var=%scan(&varlist., &i., " ");  

			%put &i. &var.; 

			    *Cross tab;
			    proc freq data=&dsetin. noprint;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
				    table &var./ out=temp1 missing;
					%if (&type. in (1, 5)) %then %do;
						format &var. POP_FMT.;
					%end;
					%else %if (&type. = 4) %then %do;
						format &var. $POP_FMT.;
					%end;
			    run;

			    *Get variable name as variable name;
			    data _null_;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			        set &dsetin. (obs=1);
			        call symput('var_name', vname(&var.));
			    run;
			    %put &var_name.;

			    *Add in variable name and label and store the levels as a text field;
			    data temp2;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
					length ANLY_IND $1. Variable $32. Grouping $50. Count 8. Percent 8.;
					ANLY_IND = "&type.";
					Variable = "&var_name.";
			        set temp1;
			        Grouping=input(&var., $50.);
					%if (&type. in (1, 4, 5)) %then %do;
						if grouping = "" then grouping = "Missing";
						else grouping = "Populated";
					%end;
			        percent=percent/100; * Stored as decimals instead of numbers, with format applied;
			        format percent PERCENTN12.4;
			        drop &var.;
			    run;

			    %put &var_name;
			    *Append datasets;
			    proc append data=temp2 base=&dsetout. force;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			    run;

			    /* drop temp tables */
			    proc datasets nodetails nolist;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			        delete temp1 temp2;
			    quit;

			*Increment counter;
			%let i=%eval(&i.+1);
		%end;

		/* Left join label onto dataset and store in perm location */
		Proc SQL;
		SYSECHO "One Way Summary - ANLY_IND &type. - Step 4/4";
		Create table output.&dsetout. (label="Expln=&Expiry_Months.m" Alter="IB") as
		Select 	 A.*
				,B.Label

		From &dsetout. 							A
		Left Join output.Contents_Summary 	B
			on A.Variable = B.Variable
			;
		Quit;
	%end;
%Mend;

%Macro Combine_Datasets;
	proc format;
	value $ Grouping_FMT (multilabel)
		' ' = "Missing"
	;
	run;

	data output.Frequency_Summary (label="Expln=&Expiry_Months.m" Alter="IB");
	SYSECHO "Combine Datasets - Step 1/1";
	length ANLY_IND $1. Variable $32. Label $256. Grouping $50. Count 8. Percent 8.;
		set
		%do i = 2 %to 6;
			%if %sysfunc(exist(output.Frequency_&i)) %then %do;
				output.Frequency_&i
			%end;
			%else %put Dataset Frequency_&i does not exist.;
		%end;
		;
		
		Format Grouping Grouping_FMT.;
	run;
%Mend Combine_Datasets;

%Macro Sleep(Buffer /* Number of minutes before 21:00 to pause code */);
	%if %sysfunc(upcase(&sleep.)) = Y %then %do;
		/* Sleep Code to remove change of 9pm error when running in nightqueue */
		data _null_;
			SYSECHO "Night Queue Test - &sleep.mins before 9:00pm";
			timediff=input('22:00:00',time8.)-datetime()+date()*24*60*60;
			timediff_nine=(input('21:00:00',time8.)-datetime()+date()*24*60*60)/60;

			/* If Mins to 9:00 pm Less than the Buffer then sleep until 10:00 pm */
			IF timediff_nine <= &Buffer. then
				do;
					sleeptime=timediff;
					call sleep(sleeptime,1);
				end;
		run;
	%end;
%Mend;

/* This macro will allow you to step through the lowercase letters of	*/
/* the alphabet on a %DO loop.											*/
%macro iterm(itr /* Iteration Number to convert to letter */);
	%Global countvar_&itr.;
	%let lst=a b c d e f g h i j k l m n o p q r s t u v w x y z
		aa ab ac ad ae af ag ah ai aj ak al am an ao ap aq ar as at au av aw ax ay az;
	%let countvar_&itr. = %scan(&lst.,&itr.);
%mend;

/*----------------------------------------------------------------------------*/
/*-- Initialise User Unputs --------------------------------------------------*/
/*----------------------------------------------------------------------------*/
options obs=max fullstimer mprint symbolgen mlogic compress=binary varinitchk=error MINOPERATOR;

/* Format List Location and dataset name */
libname form "/team/basel/Capital Transformation Project/Team/Engin Tahsin/Temp" ACCESS=READONLY;
%let format_list = format_list;

	/*--------------------------------------------------------------------*
	* Dataset Location and libname type (Meta or Standard). See examples below:
	* Meta Libname:			LIBNAME ... META LIBRARY="..." METAOUT=data ACCESS=READONLY;
	* Standard Libname: 	LIBNAME ... "..." ACCESS=READONLY 
	*---------------------------------------------------------------------*/
	%let Lib_Type = standard;
	%let Refi_Libname = /team/customer/Internal_Bureau/Marts;
	%let Out_Libname = /team/decision_science/Simplification/Internal Bureau Remediation/Data/Reporting Datasets/Profiling Outputs;

	/*--------------------------------------------------------------------*
	* Dataset Name in location specified above
	*---------------------------------------------------------------------*/
	%let Refi_DSN = RLAD_PAYDAY_201609_NEW;

	/*--------------------------------------------------------------------*
	* Tag used to apply to output files - Data_Dictionary_&Tag.
	* Use &Refi_DSN. to populate with dataset name
	*---------------------------------------------------------------------*/
	%let Tag = &Refi_DSN.;

	/*--------------------------------------------------------------------*
	* Sleep switch used to toggle sleep function on and off		[Y/N]
	* Log switch used to toggle log output on and off			[Y/N]
	* Expiry Date - Number of months to keep data				[+ve integer]
	*---------------------------------------------------------------------*/
	%let sleep = N;
	%let output_log = N;
	%let Expiry_Months = 12;
	/*--------------------------------------------------------------------*
	* Below criteria decides which variables get detailed statistics.
	* The threshholds for N_Distinct and Distinct_Pct_All may need tweaking, 
	  depending on your data.
	* N_Distinct refers to the maximum number of distinct values within a 
	  variable.
	* Distinct_Pct_All refers to the maximum ratio the number of distinct 
	  values within a variable to all values in that same variable can take.
	*--------------------------------------------------------------------*/
	%let Max_N_Distinct = 25;			/* Max number of distinct values */
	%let Max_Distinct_Pct_All = 0.1;	/* Max percent unique for all rows */

/*----------------------------------------------------------------------------*/
/*-- Define where the program is located -------------------------------------*/
/*----------------------------------------------------------------------------*/

/*Store log for each run*/
%Macro Output_Log;
	%if %sysfunc(upcase(&output_log.))=Y %then %do;
		proc printto log="&Out_Libname./&Refi_DSN./&Refi_DSN..log";
		run;
	%end; 
	%else %do;
		%put No log output.;
	%end;
%Mend Output_Log;
%Output_Log;

%macro LIBNAMES;
	/*-- Setup libname locations based on the library type used --*/
	%IF %SYSFUNC(lowcase(&Lib_Type.))=standard %THEN %DO;
		LIBNAME refi_lib "&Refi_Libname." ACCESS=READONLY;
	%END;
	%ELSE %IF %SYSFUNC(lowcase(&Lib_Type.))=meta %THEN %DO;
		LIBNAME refi_lib META LIBRARY="&Refi_Libname." METAOUT=data ACCESS=READONLY;
	%END;

	/* Location of output files - this can also create a folder */
	options DLCREATEDIR;	/* Turn on function to create library if no-exist */
		LIBNAME output "&Out_Libname./&Refi_DSN.";
	options NODLCREATEDIR;	/* Turn off function to create library if exist */
%Mend LIBNAMES;
%LIBNAMES;

%sleep(120);

/*----------------------------------------------------------------------------*/
/*-- Contents of the REFI metadata and dataset -------------------------------*/
/*----------------------------------------------------------------------------*/
proc sql noprint;
	SYSECHO "Key Statistics - Step 1/21";
    %*-- List the SAS Metadata for this dataset --;
    create table Contents_Listing as
        select Name, Type, Length, strip(Format) as Format,
            strip(Informat) as InFormat, strip(Label) as Label, varnum
        from dictionary.columns
        where libname = upcase('Refi_Lib') and memname = upcase("&Refi_DSN.")
        order by upcase(Name);
    %put Dataset has &sqlobs rows;
quit;

/*-- Custom dataset contents --*/
proc print data=Contents_Listing label uniform width=minimum noobs;
	SYSECHO "Key Statistics - Step 2/21";
    title "Contents of &Refi_DSN.";
run;

/*----------------------------------------------------------------------------*/
/*-- Look for various possible key columns -----------------------------------*/
/*----------------------------------------------------------------------------*/
%let Count_All_Vars =;
proc sql noprint stimer;
	SYSECHO "Key Statistics - Step 3/21";
    %*-- Count non-missing and unique rows in the dataset. --------------------;
    %*-- Prepare the SQL statements to perform the counts. --------------------;
    %*-- Handle issue where SAS variable name would be longer than 32 chars ---;
    select "count(" || strip(Name)  || ") as N_"  ||
               substr(left(Name),1,min(29, length(strip(Name)))) ||
         ", count(distinct " || strip(Name) || ") as ND_" ||
               substr(left(Name),1,min(29, length(strip(Name))))
        into :Count_All_Vars separated by ", "
        from dictionary.columns
        where libname = upcase('Refi_Lib') and memname = upcase("&Refi_DSN");
    %put Count_All_Vars has &sqlobs rows;
quit;

/* Perform the dataset counts prepared above */
proc sql noprint stimer;
	SYSECHO "Key Statistics - Step 4/21";
    create table key_values_0 as
        select 	count(*) as All_Rows
				,&Count_All_Vars.
        from refi_lib.&Refi_DSN.
    %put Dataset has &sqlobs rows;
quit;

/*----------------------------------------------------------------------------*/
/*-- Create a more useable dataset for Key Column analysis -------------------*/
/*----------------------------------------------------------------------------*/

/*-- Exchange rows and columns --*/
proc transpose data=key_values_0 out=key_values_0_T;
	SYSECHO "Key Statistics - Step 5/21";
run;

%sleep(120);
/*-- Derive other column counts from the transposed SQL results --*/
data key_values;
	SYSECHO "Key Statistics - Step 6/21";
    /*-- Order the variables and assign labels --*/
    label
        Variable=""
        Count="Number of Rows Filled"
        Filled="Percent of Rows Filled"
        NMiss="Number of Rows Missing"
        Miss_Pct="Percent of Rows Missing"
        Unique="Number of Distinct Values"
        Unique_Pct="Unique Percentage of Filled Rows"
        Unique_Pct_All="Unique Percentage of All Rows"
        Stats="Stats"
        ;
    set key_values_0_T (rename=(_name_=Varname col1=Num));
    length Variable $ 40 Stats $ 1;
    retain Row_Count Variable Count NMiss;
    drop Row_Count Varname Num;
    format Filled Unique_Pct Miss_Pct Unique_Pct_All PERCENTN12.4;

    /*-- Default value is N = No Statistics --*/    
    Stats = "N";

    /*-- The first OBS contains the overall totals --*/
    if _N_=1 then do;
        Variable = Varname;
        Count = Num;
        Filled = 1;
        Unique = Num;
        Unique_Pct = 1;
        Unique_Pct_All = 1;
        NMiss = 0;
        Miss_Pct = 0;
        Row_Count = Num;
        output;
    end;

    /*------------------------------------------------------------------------*
     * Besides the first row, other rows contain, in order, records with the
     * non-missing count, followed by another with the unique count.
     * Other measures are derived from this data.
     *------------------------------------------------------------------------*/

    /*-- Got a new Variable ... Set the non-missing counts --*/
    if (substr(Varname, 1, 2) = "N_") then do;
        Variable = substr(Varname, 3);
        Count = Num;
        NMiss  = Row_Count - Count;
    end;
    /*-- This row has unique counts, and most measures are computed here --*/
    if (substr(Varname, 1, 3) = "ND_") then do;
        Filled = Count / Row_Count;
        Unique = Num;
        /*-- This data is NOT all Missing values --*/
        if (Count ^= 0) then do;
            Unique_Pct = Num / Count;
            Unique_Pct_All = Num / Row_Count;
            Miss_Pct = NMiss / Row_Count;
        end;
        /*-- This data IS all Missing values, and cannot be summarized --*/
        else do;
            Unique_Pct = 0;
            Unique_Pct_All = 0;
            Miss_Pct = 1;
        end;
        /*--------------------------------------------------------------------*
         * This criteria decides which variables get detailed statistics.
         * The threshholds may need tweaking (at initialisation stages), 
		   depending on your data.
         *--------------------------------------------------------------------*/
        if (Unique_Pct_All <= &Max_Distinct_Pct_All. and Unique < &Max_N_Distinct. and Count ^= 0) then
            Stats = "Y";
        output;
    end;
run;
proc sort data=key_values;
	SYSECHO "Key Statistics - Step 7/21";
    by descending Count descending NMiss descending Unique Variable;
run;

/*-- The analysis so far, before the merge with the Contents dataset --*/
proc print data=key_values label uniform width=minimum noobs;
	SYSECHO "Key Statistics - Step 8/21";
    title "Counts and Uniqueness for Variables in &Refi_DSN.";
run;

/*-- Combine the Contents dataset with the Key Values analysis above ---------*/
proc sql noprint;
	SYSECHO "Key Statistics - Step 9/21";
    create table Contents_Summary as
        select b.*, a.type, a.length, a.Format, a.InFormat, a.Label,
            a.varnum
        from Contents_Listing a, key_values b
        where upcase(a.name) = upcase(b.Variable);
    %put Dataset has &sqlobs rows;
quit; 


/*--------------------------------------------------------------------*
 * Pull in existing dataset and overwrite with additional indicator
 * Create the analysis indicator, which will be used to drive which 
   monitoring tests are to be carried out on each variable. See below:

 * Anly_ind = 1		Numeric - Continuous data
 * Anly_ind = 2		Numeric - Segment/Indicator data
 * Anly_ind = 3		Character - Segment/Indicator data
 * Anly_ind = 4		Character - Continuous data
 * Anly_ind = 5		Numeric - Date type data
 * Anly_ind = 6		Other - Catchall - Must Explore
 *--------------------------------------------------------------------*/

/* Macro to pull in and initialise formats from the formats table */
%macro initialise_formats;
	/* Count the number of formats within the table matching the datetime criteria */
	%global count_format;
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 10/21";
		Select Count(*)
			into :count_format
		From form.&format_list.
			where TYPE='datetime';
	Quit;

	/* Create N number of &FORMAT_i. variables to insert formats into  */
	%let count_format = %left(&count_format.);
	%do i = 1 %to &count_format.;
		%global FORMAT_&i.;
	%end;

	/* Insert formats from table into macro variables created in above process with quotation marks */
	PROC SQL NOPRINT;
		SYSECHO "Key Statistics - Step 11/21";
		Select QUOTE(STRIP(SCAN_CRITERIA))
			Into :FORMAT_1 - :FORMAT_&count_format.
		From form.&format_list.
			Where TYPE='datetime';
		;
	QUIT;
	%put Formats Assigned to Macro Variables; %put;
%mend initialise_formats;
%initialise_formats;

/* Macro to execute the find process. Kept at macro level so we can use the &i. macro variable. */
%macro find;
	/* If string cannot be found, then search = 0, else 1. */
	%do i = 1 %to &count_format.;
		search = max(find(Format, &&FORMAT_&i..), search);
	%end;
%mend find;

data output.Contents_Summary (label="Expln=&Expiry_Months.m" Alter="IB" drop=search);
	SYSECHO "Key Statistics - Step 12/21";
	set Contents_Summary;
	    label
        Anly_ind = "Data Type [Numeric/Character/Date/Other] and [Continuous/Discrete]"
        ;

	/* Initialise the search variable to 0 then invoke the find macro */
	search = 0;
	%find;

	/* Analysis indicator hierachy. This is used to determine which monitoring checks
	to perform */
	if (lowcase(type) = "num" AND search ^= 0) then Anly_ind = 5;
	else if (lowcase(type) = "num" AND upcase(Stats) = "N") then Anly_ind = 1;
	else if (lowcase(type) = "num" AND upcase(Stats) = "Y") then Anly_ind = 2;
	else if (lowcase(type) = "char" AND upcase(Stats) = "Y") then Anly_ind = 3;
	else if (lowcase(type) = "char" AND upcase(Stats) = "N") then Anly_ind = 4;
	else Anly_ind = 6;
run;


/* Steps to group variables into macro variable to be used for processing later */
%global	ANLY_IND_1_CSV ANLY_IND_1_SPACE
		ANLY_IND_2_CSV ANLY_IND_2_SPACE
		ANLY_IND_3_CSV ANLY_IND_3_SPACE
		ANLY_IND_4_CSV ANLY_IND_4_SPACE
		ANLY_IND_5_CSV ANLY_IND_5_SPACE
		ANLY_IND_6_CSV ANLY_IND_6_SPACE
		CLASS_VARS_CSV CLASS_VARS_SPACE
		COUNT_ANLY_1   COUNT_ANLY_2
		COUNT_ANLY_3   SEG_COUNT;

PROC SQL noprint;
	SYSECHO "Key Statistics - Step 13/21";
    %*-- Put all variables with ANLY_IND = 1 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_1_CSV separated by ", ",
			:ANLY_IND_1_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 1;
    %put ANLY_IND_1_CSV and ANLY_IND_1_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 2 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_2_CSV separated by ", ",
			:ANLY_IND_2_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 2;
    %put ANLY_IND_2_CSV and ANLY_IND_2_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 3 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_3_CSV separated by ", ",
			:ANLY_IND_3_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 3;
    %put ANLY_IND_3_CSV and ANLY_IND_3_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 4 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_4_CSV separated by ", ",
			:ANLY_IND_4_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 4;
    %put ANLY_IND_4_CSV and ANLY_IND_4_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 5 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_5_CSV separated by ", ",
			:ANLY_IND_5_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 5;
    %put ANLY_IND_5_CSV and ANLY_IND_5_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 6 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_6_CSV separated by ", ",
			:ANLY_IND_6_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 6;
    %put ANLY_IND_6_CSV and ANLY_IND_6_SPACE have &sqlobs rows;

    %*-- Put all class variables into macro variable for later --;
    select	Variable 
			,Variable
	into	:CLASS_VARS_CSV separated by ", ",
			:CLASS_VARS_SPACE separated by " "
	from output.Contents_Summary
        where upcase(Stats) = "Y";
    %put CLASS_VARS_CSV and CLASS_VARS_SPACE have &sqlobs rows;
QUIT;

%macro Initialise_Means_Anly_1;
	/* Count the number of variables within the table matching the STATS = "Y" criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 14/21";
		Select Count(*)
			into :SEG_COUNT
		From output.Contents_Summary
			where STATS='Y';
	Quit;

	/* Create N number of &ANLY1_i. variables to insert variable names into */
	%let SEG_COUNT = %left(&SEG_COUNT.);
	%do i = 1 %to &SEG_COUNT.;
		%global ANLY1_&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 15/21";
		Select STRIP(VARIABLE)
			Into :ANLY1_1 - :ANLY1_&SEG_COUNT.
		From output.Contents_Summary
			where STATS='Y'
		;
	QUIT;
%mend Initialise_Means_Anly_1;
%Initialise_Means_Anly_1;

%macro Anly_1_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 1 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 16/21";
		Select Count(*)
			into :COUNT_ANLY_1
		From output.Contents_Summary
			where ANLY_IND=1;
	Quit;

	/* Create N number of ANLY_IND_1_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_1 = %left(&COUNT_ANLY_1.);
	%do i = 1 %to &COUNT_ANLY_1.;
		%global ANLY_IND_1_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 17/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_1_VAR1 - :ANLY_IND_1_VAR&COUNT_ANLY_1.
		From output.Contents_Summary
			where ANLY_IND=1;
	QUIT;
%mend Anly_1_Variables;
%Anly_1_Variables;

%macro Anly_2_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 2 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 18/21";
		Select Count(*)
			into :COUNT_ANLY_2
		From output.Contents_Summary
			where ANLY_IND=2;
	Quit;

	/* Create N number of ANLY_IND_2_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_2 = %left(&COUNT_ANLY_2.);
	%do i = 1 %to &COUNT_ANLY_2.;
		%global ANLY_IND_2_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 19/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_2_VAR1 - :ANLY_IND_2_VAR&COUNT_ANLY_2.
		From output.Contents_Summary
			where ANLY_IND=2;
	QUIT;
%mend Anly_2_Variables;
%Anly_2_Variables;

%macro Anly_3_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 3 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 20/21";
		Select Count(*)
			into :COUNT_ANLY_3
		From output.Contents_Summary
			where ANLY_IND=3;
	Quit;

	/* Create N number of ANLY_IND_3_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_3 = %left(&COUNT_ANLY_3.);
	%do i = 1 %to &COUNT_ANLY_3.;
		%global ANLY_IND_3_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 21/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_3_VAR1 - :ANLY_IND_3_VAR&COUNT_ANLY_3.
		From output.Contents_Summary
			where ANLY_IND=3;
	QUIT;
%mend Anly_3_Variables;
%Anly_3_Variables;

/*----------------------------------------------------------------------------*/
/*-- E N D -------------------------------------------------------------------*/
/*----------------------------------------------------------------------------*/

/* Call macro that will perform the percentile summary. This will breakdown all variables
with an ANLY_IND = 1 value into percentiles and perform N, NMISS, MIN, MAX, SUM, STD metrics on */
%Percentile_Summary;

/* Call macro that will populate summary tables for the all variables */
/* This macro is to be used for ANLY_IND = 2,3,4,5 values */
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_2_SPACE., Frequency_2, 2);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_3_SPACE., Frequency_3, 3);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_4_SPACE., Frequency_4, 4);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_5_SPACE., Frequency_5, 5);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_6_SPACE., Frequency_6, 6);

/* This macro combines all one way analyses conducted */
%Combine_Datasets;

/*----------------------------------------------------------------------------*/
/*-- Initialise User Unputs --------------------------------------------------*/
/*----------------------------------------------------------------------------*/
options obs=max fullstimer mprint symbolgen mlogic compress=binary varinitchk=error MINOPERATOR;

/* Format List Location and dataset name */
libname form "/team/customer/Simplification/Internal Bureau Remediation" ACCESS=READONLY;
%let format_list = format_list;

	/*--------------------------------------------------------------------*
	* Dataset Location and libname type (Meta or Standard). See examples below:
	* Meta Libname:			LIBNAME ... META LIBRARY="..." METAOUT=data ACCESS=READONLY;
	* Standard Libname: 	LIBNAME ... "..." ACCESS=READONLY 
	*---------------------------------------------------------------------*/
	%let Lib_Type = standard;
	%let Refi_Libname = /team/customer/Internal_Bureau/Marts;
	%let Out_Libname = /team/customer/Simplification/Internal Bureau Remediation/Data/Profiling/Profiling Outputs;

	/*--------------------------------------------------------------------*
	* Dataset Name in location specified above
	*---------------------------------------------------------------------*/
	%let Refi_DSN = RLAD_PAYDAY_201609_NEW;

	/*--------------------------------------------------------------------*
	* Tag used to apply to output files - Data_Dictionary_&Tag.
	* Use &Refi_DSN. to populate with dataset name
	*---------------------------------------------------------------------*/
	%let Tag = &Refi_DSN.;

	/*--------------------------------------------------------------------*
	* Sleep switch used to toggle sleep function on and off		[Y/N]
	* Log switch used to toggle log output on and off			[Y/N]
	* Expiry Date - Number of months to keep data				[+ve integer]
	*---------------------------------------------------------------------*/
	%let sleep = N;
	%let output_log = N;
	%let Expiry_Months = 18;
	/*--------------------------------------------------------------------*
	* Below criteria decides which variables get detailed statistics.
	* The threshholds for N_Distinct and Distinct_Pct_All may need tweaking, 
	  depending on your data.
	* N_Distinct refers to the maximum number of distinct values within a 
	  variable.
	* Distinct_Pct_All refers to the maximum ratio the number of distinct 
	  values within a variable to all values in that same variable can take.
	*--------------------------------------------------------------------*/
	%let Max_N_Distinct = 25;			/* Max number of distinct values */
	%let Max_Distinct_Pct_All = 0.1;	/* Max percent unique for all rows */

/*----------------------------------------------------------------------------*/
/*-- Initialise Macros -------------------------------------------------------*/
/*----------------------------------------------------------------------------*/
	/* Means analysis using a format for each variable */
%macro Percentile_Summary;
	/* If the count is populated, then run the percentile summary */
	%if (%eval(&COUNT_ANLY_1.) ne 0) %then %do;

		/* Kill means datasets in the WORK tempspace that may exist from previous runs */
		proc datasets lib=work nolist;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 1/4";
			delete 	Percentile_Summary Anly_1_Summary;
		run;

		/* Run proc means for individual variables, using custom made formats for variable */
		%do k = 1 %to &COUNT_ANLY_1.;
			/* Create format for use in the proc means step below */
			%Percentile(dsn=refi_lib.&Refi_DSN., var=&&ANLY_IND_1_VAR&k..);
			%sleep(60);		/* Test whether the system should go into sleep mode or not */

			/* Analysis: PROC MEANS function for all numeric continuous data, at fine and total level */
			PROC MEANS DATA = ranked_out noprint missing chartype COMPLETETYPES;
				SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
				VAR &&ANLY_IND_1_VAR&k..;
				CLASS VAR_SEG;
					OUTPUT OUT = Anly_1_Summary (rename=(VAR_SEG=GROUPING))
						N= N
						NMISS= NMISS
						MIN= MIN
						MAX= MAX
						MEAN= MEAN
						SUM= SUM
						STD= STD /noinherit;
			RUN;

			data Percentile_Summary;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";

				/* Set original datastep and additions - N ne 1*/
				%if &k. ne 1 %then %do;
					set Percentile_Summary Anly_1_Summary;
				%end;

				/* Create variables and set lengths/labels. Set first batch of data available */
				%else %if &k. eq 1 %then %do;
					/* Assign Lengths and Formats*/
					LENGTH ID 4 VARIABLE $32 GROUPING $11;

					/* Assign Labels */
				    label
						ID="ID Number"
				        VARIABLE="Classification Variable Name"
				        GROUPING="Classification Grouping"
					;

					/* Initialise with missing */
					GROUPING = .;
					set Anly_1_Summary;
				%end;

				/* Create column with relevant variable name and ID */
				if ID = . then ID = &k.;
				if VARIABLE = "" then VARIABLE = "&&ANLY_IND_1_VAR&k..";
				if _TYPE_ = "0" then GROUPING = "Overall";
			run;
		%end;

		/* Left join label onto dataset */
		Proc SQL;
		Create table output.Percentile_Summary (label="Expln=&Expiry_Months.m" Alter="IB") as
		Select 	 A.*
				,B.Label

		From Percentile_Summary 				A
		Left Join output.Contents_Summary 	B
			on A.Variable = B.Variable
			;
		Quit;

		proc datasets library=work nolist;
			SYSECHO "Percentile Analysis - ANLY_IND 1 - Step 4/4";
			delete Anly_1_SUMMARY ranked ranked_out;
		run;
	%end;
%mend Percentile_Summary;

/* Macro to calculate the cutpoints for percentiles */
%Macro Percentile(
				dsn /* Libname and dataset name - lib.dsetname */,
				var /* Variable name to create percentiles on */);

	/* Rank variable in question to create percentiles*/
	proc rank data=&dsn.(keep=&var.) out=ranked ties=low;
		SYSECHO "Formatting 1/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		var &var.;
		ranks Var_Rank;
	run;

	/* Sort data into ascending order using the ranked variable created above */
	proc sort data=ranked;
		SYSECHO "Formatting 2/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		by Var_Rank;
	run;

	/* Add counter and determine splits for percentile calculation */
	DATA ranked;
		SYSECHO "Formatting 3/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
		/* Set non-missing values then missing values, so missing values are at the bottom*/
		SET ranked(where=(Var_Rank ne .)) ranked(where=(Var_Rank eq .));

		N = _N_;							/* Counter */
		IF (Var_Rank eq .) THEN N = .;	/* Set N to missing for missing values */
	RUN;

	/* Step to create the segmentation for percentiles. See formatting in monitoring program */
	PROC SQL;
	SYSECHO "Formatting 4/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
	CREATE TABLE ranked_out(drop=N Var_Rank) AS	
		SELECT 	*,
				CASE	WHEN N = . THEN 'Missing'
						WHEN N <= CEIL(MIN(N) + (MAX(N) - MIN(N) + 1)*  1/100 - 1)  THEN '0% to 1%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)*  5/100 - 1  		THEN '1% to 5%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 10/100 - 1  		THEN '5% to 10%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 25/100 - 1  		THEN '10% to 25%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 50/100 - 1  		THEN '25% to 50%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 75/100 - 1 		THEN '50% to 75%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 90/100 - 1  		THEN '75% to 90%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 95/100 - 1  		THEN '90% to 95%'
						WHEN N <= FLOOR(MIN(N) + (MAX(N) - MIN(N) + 1)* 99/100 - 1) THEN '95% to 99%'
						ELSE '99% to 100%'
	  		END AS VAR_SEG			/* Percentile Segmentation variable */		
		FROM ranked
		;
	QUIT;
%Mend Percentile;

/* Macro to create 1-way summaries */
%Macro one_way_summary(
	dsetin /* Library and dataset name - lib.dset_name */,
	varlist /* List of vars to feed through the proc freq procedure */,
	dsetout /* Output library and dataset name - lib.dset_name */,
	type /* ANLY_IND value */)  /mindelimiter=',';

	%sleep(60);		/* Test whether the system should go into sleep mode or not */

	/* Count the number of variables within the table matching the ANLY_IND = &type. criteria */
	Proc Sql noprint;
		SYSECHO "One Way Summary - ANLY_IND &type. - Step 1/4";
		Select Count(*)
			into :COUNT_ANLY_&type.
		From output.Contents_Summary
			where ANLY_IND=&type.;
	Quit;

	/* If the count is populated, then run the one way summary */
	%if (%eval(&&COUNT_ANLY_&type..) ne 0) %then %do;

		/* Housekeeping - Delete datasets */
		proc datasets nodetails nolist;
			SYSECHO "One Way Summary - ANLY_IND &type. - Step 2/4";
		    delete &dsetout.;
		quit;

		/* Create population format */
		%if (&type. in (1, 5)) %then %do;
			proc format;
			value POP_FMT (multilabel)
				. = "Missing"
				other = "Populated"
			;
			run;
		%end;
		%else %if (&type. = 4) %then %do;
			proc format;
			value $ POP_FMT (multilabel)
				' ' = "Missing"
				other = "Populated"
			;
			run;
		%end;

		*loop through variable list;
		%let i=1;
		%do %while (%scan(&varlist., &i., " ") ^=%str());
			%let var=%scan(&varlist., &i., " ");  

			%put &i. &var.; 

			    *Cross tab;
			    proc freq data=&dsetin. noprint;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
				    table &var./ out=temp1 missing;
					%if (&type. in (1, 5)) %then %do;
						format &var. POP_FMT.;
					%end;
					%else %if (&type. = 4) %then %do;
						format &var. $POP_FMT.;
					%end;
			    run;

			    *Get variable name as variable name;
			    data _null_;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			        set &dsetin. (obs=1);
			        call symput('var_name', vname(&var.));
			    run;
			    %put &var_name.;

			    *Add in variable name and label and store the levels as a text field;
			    data temp2;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
					length ANLY_IND $1. Variable $32. Grouping $50. Count 8. Percent 8.;
					ANLY_IND = "&type.";
					Variable = "&var_name.";
			        set temp1;
			        Grouping=input(&var., $50.);
					%if (&type. in (1, 4, 5)) %then %do;
						if grouping = "" then grouping = "Missing";
						else grouping = "Populated";
					%end;
			        percent=percent/100; * Stored as decimals instead of numbers, with format applied;
			        format percent PERCENTN12.4;
			        drop &var.;
			    run;

			    %put &var_name;
			    *Append datasets;
			    proc append data=temp2 base=&dsetout. force;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			    run;

			    /* drop temp tables */
			    proc datasets nodetails nolist;
					SYSECHO "One Way Summary - ANLY_IND &type. - Step 3/4 - Sub Step &i./&&COUNT_ANLY_&type..";
			        delete temp1 temp2;
			    quit;

			*Increment counter;
			%let i=%eval(&i.+1);
		%end;

		/* Left join label onto dataset and store in perm location */
		Proc SQL;
		SYSECHO "One Way Summary - ANLY_IND &type. - Step 4/4";
		Create table output.&dsetout. (label="Expln=&Expiry_Months.m" Alter="IB") as
		Select 	 A.*
				,B.Label

		From &dsetout. 							A
		Left Join output.Contents_Summary 	B
			on A.Variable = B.Variable
			;
		Quit;
	%end;
%Mend;

%Macro Combine_Datasets;
	proc format;
	value $ Grouping_FMT (multilabel)
		' ' = "Missing"
	;
	run;

	data output.Frequency_Summary (label="Expln=&Expiry_Months.m" Alter="IB");
	SYSECHO "Combine Datasets - Step 1/1";
	length ANLY_IND $1. Variable $32. Label $256. Grouping $50. Count 8. Percent 8.;
		set
		%do i = 2 %to 6;
			%if %sysfunc(exist(output.Frequency_&i)) %then %do;
				output.Frequency_&i
			%end;
			%else %put Dataset Frequency_&i does not exist.;
		%end;
		;
		
		Format Grouping Grouping_FMT.;
	run;
%Mend Combine_Datasets;

%Macro Sleep(Buffer /* Number of minutes before 21:00 to pause code */);
	%if %sysfunc(upcase(&sleep.)) = Y %then %do;
		/* Sleep Code to remove change of 9pm error when running in nightqueue */
		data _null_;
			SYSECHO "Night Queue Test - &sleep.mins before 9:00pm";
			timediff=input('22:00:00',time8.)-datetime()+date()*24*60*60;
			timediff_nine=(input('21:00:00',time8.)-datetime()+date()*24*60*60)/60;

			/* If Mins to 9:00 pm Less than the Buffer then sleep until 10:00 pm */
			IF timediff_nine <= &Buffer. then
				do;
					sleeptime=timediff;
					call sleep(sleeptime,1);
				end;
		run;
	%end;
%Mend;

/* This macro will allow you to step through the lowercase letters of	*/
/* the alphabet on a %DO loop.											*/
%macro iterm(itr /* Iteration Number to convert to letter */);
	%Global countvar_&itr.;
	%let lst=a b c d e f g h i j k l m n o p q r s t u v w x y z
		aa ab ac ad ae af ag ah ai aj ak al am an ao ap aq ar as at au av aw ax ay az;
	%let countvar_&itr. = %scan(&lst.,&itr.);
%mend;

/*----------------------------------------------------------------------------*/
/*-- Define where the program is located -------------------------------------*/
/*----------------------------------------------------------------------------*/

/*Store log for each run*/
%Macro Output_Log;
	%if %sysfunc(upcase(&output_log.))=Y %then %do;
		proc printto log="&Out_Libname./&Refi_DSN./&Refi_DSN..log";
		run;
	%end; 
	%else %do;
		%put No log output.;
	%end;
%Mend Output_Log;
%Output_Log;

%macro LIBNAMES;
	/*-- Setup libname locations based on the library type used --*/
	%IF %SYSFUNC(lowcase(&Lib_Type.))=standard %THEN %DO;
		LIBNAME refi_lib "&Refi_Libname." ACCESS=READONLY;
	%END;
	%ELSE %IF %SYSFUNC(lowcase(&Lib_Type.))=meta %THEN %DO;
		LIBNAME refi_lib META LIBRARY="&Refi_Libname." METAOUT=data ACCESS=READONLY;
	%END;

	/* Location of output files - this can also create a folder */
	options DLCREATEDIR;	/* Turn on function to create library if no-exist */
		LIBNAME output "&Out_Libname./&Refi_DSN.";
	options NODLCREATEDIR;	/* Turn off function to create library if exist */
%Mend LIBNAMES;
%LIBNAMES;

%sleep(120);

/*----------------------------------------------------------------------------*/
/*-- Contents of the REFI metadata and dataset -------------------------------*/
/*----------------------------------------------------------------------------*/
proc sql noprint;
	SYSECHO "Key Statistics - Step 1/21";
    %*-- List the SAS Metadata for this dataset --;
    create table Contents_Listing as
        select Name, Type, Length, strip(Format) as Format,
            strip(Informat) as InFormat, strip(Label) as Label, varnum
        from dictionary.columns
        where libname = upcase('Refi_Lib') and memname = upcase("&Refi_DSN.")
        order by upcase(Name);
    %put Dataset has &sqlobs rows;
quit;

/*-- Custom dataset contents --*/
proc print data=Contents_Listing label uniform width=minimum noobs;
	SYSECHO "Key Statistics - Step 2/21";
    title "Contents of &Refi_DSN.";
run;

/*----------------------------------------------------------------------------*/
/*-- Look for various possible key columns -----------------------------------*/
/*----------------------------------------------------------------------------*/
%let Count_All_Vars =;
proc sql noprint stimer;
	SYSECHO "Key Statistics - Step 3/21";
    %*-- Count non-missing and unique rows in the dataset. --------------------;
    %*-- Prepare the SQL statements to perform the counts. --------------------;
    %*-- Handle issue where SAS variable name would be longer than 32 chars ---;
    select "count(" || strip(Name)  || ") as N_"  ||
               substr(left(Name),1,min(29, length(strip(Name)))) ||
         ", count(distinct " || strip(Name) || ") as ND_" ||
               substr(left(Name),1,min(29, length(strip(Name))))
        into :Count_All_Vars separated by ", "
        from dictionary.columns
        where libname = upcase('Refi_Lib') and memname = upcase("&Refi_DSN");
    %put Count_All_Vars has &sqlobs rows;
quit;

/* Perform the dataset counts prepared above */
proc sql noprint stimer;
	SYSECHO "Key Statistics - Step 4/21";
    create table key_values_0 as
        select 	count(*) as All_Rows
				,&Count_All_Vars.
        from refi_lib.&Refi_DSN.
    %put Dataset has &sqlobs rows;
quit;

/*----------------------------------------------------------------------------*/
/*-- Create a more useable dataset for Key Column analysis -------------------*/
/*----------------------------------------------------------------------------*/

/*-- Exchange rows and columns --*/
proc transpose data=key_values_0 out=key_values_0_T;
	SYSECHO "Key Statistics - Step 5/21";
run;

%sleep(120);
/*-- Derive other column counts from the transposed SQL results --*/
data key_values;
	SYSECHO "Key Statistics - Step 6/21";
    /*-- Order the variables and assign labels --*/
    label
        Variable=""
        Count="Number of Rows Filled"
        Filled="Percent of Rows Filled"
        NMiss="Number of Rows Missing"
        Miss_Pct="Percent of Rows Missing"
        Unique="Number of Distinct Values"
        Unique_Pct="Unique Percentage of Filled Rows"
        Unique_Pct_All="Unique Percentage of All Rows"
        Stats="Stats"
        ;
    set key_values_0_T (rename=(_name_=Varname col1=Num));
    length Variable $ 40 Stats $ 1;
    retain Row_Count Variable Count NMiss;
    drop Row_Count Varname Num;
    format Filled Unique_Pct Miss_Pct Unique_Pct_All PERCENTN12.4;

    /*-- Default value is N = No Statistics --*/    
    Stats = "N";

    /*-- The first OBS contains the overall totals --*/
    if _N_=1 then do;
        Variable = Varname;
        Count = Num;
        Filled = 1;
        Unique = Num;
        Unique_Pct = 1;
        Unique_Pct_All = 1;
        NMiss = 0;
        Miss_Pct = 0;
        Row_Count = Num;
        output;
    end;

    /*------------------------------------------------------------------------*
     * Besides the first row, other rows contain, in order, records with the
     * non-missing count, followed by another with the unique count.
     * Other measures are derived from this data.
     *------------------------------------------------------------------------*/

    /*-- Got a new Variable ... Set the non-missing counts --*/
    if (substr(Varname, 1, 2) = "N_") then do;
        Variable = substr(Varname, 3);
        Count = Num;
        NMiss  = Row_Count - Count;
    end;
    /*-- This row has unique counts, and most measures are computed here --*/
    if (substr(Varname, 1, 3) = "ND_") then do;
        Filled = Count / Row_Count;
        Unique = Num;
        /*-- This data is NOT all Missing values --*/
        if (Count ^= 0) then do;
            Unique_Pct = Num / Count;
            Unique_Pct_All = Num / Row_Count;
            Miss_Pct = NMiss / Row_Count;
        end;
        /*-- This data IS all Missing values, and cannot be summarized --*/
        else do;
            Unique_Pct = 0;
            Unique_Pct_All = 0;
            Miss_Pct = 1;
        end;
        /*--------------------------------------------------------------------*
         * This criteria decides which variables get detailed statistics.
         * The threshholds may need tweaking (at initialisation stages), 
		   depending on your data.
         *--------------------------------------------------------------------*/
        if (Unique_Pct_All <= &Max_Distinct_Pct_All. and Unique < &Max_N_Distinct. and Count ^= 0) then
            Stats = "Y";
        output;
    end;
run;
proc sort data=key_values;
	SYSECHO "Key Statistics - Step 7/21";
    by descending Count descending NMiss descending Unique Variable;
run;

/*-- The analysis so far, before the merge with the Contents dataset --*/
proc print data=key_values label uniform width=minimum noobs;
	SYSECHO "Key Statistics - Step 8/21";
    title "Counts and Uniqueness for Variables in &Refi_DSN.";
run;

/*-- Combine the Contents dataset with the Key Values analysis above ---------*/
proc sql noprint;
	SYSECHO "Key Statistics - Step 9/21";
    create table Contents_Summary as
        select b.*, a.type, a.length, a.Format, a.InFormat, a.Label,
            a.varnum
        from Contents_Listing a, key_values b
        where upcase(a.name) = upcase(b.Variable);
    %put Dataset has &sqlobs rows;
quit; 


/*--------------------------------------------------------------------*
 * Pull in existing dataset and overwrite with additional indicator
 * Create the analysis indicator, which will be used to drive which 
   monitoring tests are to be carried out on each variable. See below:

 * Anly_ind = 1		Numeric - Continuous data
 * Anly_ind = 2		Numeric - Segment/Indicator data
 * Anly_ind = 3		Character - Segment/Indicator data
 * Anly_ind = 4		Character - Continuous data
 * Anly_ind = 5		Numeric - Date type data
 * Anly_ind = 6		Other - Catchall - Must Explore
 *--------------------------------------------------------------------*/

/* Macro to pull in and initialise formats from the formats table */
%macro initialise_formats;
	/* Count the number of formats within the table matching the datetime criteria */
	%global count_format;
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 10/21";
		Select Count(*)
			into :count_format
		From form.&format_list.
			where TYPE='datetime';
	Quit;

	/* Create N number of &FORMAT_i. variables to insert formats into  */
	%let count_format = %left(&count_format.);
	%do i = 1 %to &count_format.;
		%global FORMAT_&i.;
	%end;

	/* Insert formats from table into macro variables created in above process with quotation marks */
	PROC SQL NOPRINT;
		SYSECHO "Key Statistics - Step 11/21";
		Select QUOTE(STRIP(SCAN_CRITERIA))
			Into :FORMAT_1 - :FORMAT_&count_format.
		From form.&format_list.
			Where TYPE='datetime';
		;
	QUIT;
	%put Formats Assigned to Macro Variables; %put;
%mend initialise_formats;
%initialise_formats;

/* Macro to execute the find process. Kept at macro level so we can use the &i. macro variable. */
%macro find;
	/* If string cannot be found, then search = 0, else 1. */
	%do i = 1 %to &count_format.;
		search = max(find(Format, &&FORMAT_&i..), search);
	%end;
%mend find;

data output.Contents_Summary (label="Expln=&Expiry_Months.m" Alter="IB" drop=search);
	SYSECHO "Key Statistics - Step 12/21";
	set Contents_Summary;
	    label
        Anly_ind = "Data Type [Numeric/Character/Date/Other] and [Continuous/Discrete]"
        ;

	/* Initialise the search variable to 0 then invoke the find macro */
	search = 0;
	%find;

	/* Analysis indicator hierachy. This is used to determine which monitoring checks
	to perform */
	if (lowcase(type) = "num" AND search ^= 0) then Anly_ind = 5;
	else if (lowcase(type) = "num" AND upcase(Stats) = "N") then Anly_ind = 1;
	else if (lowcase(type) = "num" AND upcase(Stats) = "Y") then Anly_ind = 2;
	else if (lowcase(type) = "char" AND upcase(Stats) = "Y") then Anly_ind = 3;
	else if (lowcase(type) = "char" AND upcase(Stats) = "N") then Anly_ind = 4;
	else Anly_ind = 6;
run;


/* Steps to group variables into macro variable to be used for processing later */
%global	ANLY_IND_1_CSV ANLY_IND_1_SPACE
		ANLY_IND_2_CSV ANLY_IND_2_SPACE
		ANLY_IND_3_CSV ANLY_IND_3_SPACE
		ANLY_IND_4_CSV ANLY_IND_4_SPACE
		ANLY_IND_5_CSV ANLY_IND_5_SPACE
		ANLY_IND_6_CSV ANLY_IND_6_SPACE
		CLASS_VARS_CSV CLASS_VARS_SPACE
		COUNT_ANLY_1   COUNT_ANLY_2
		COUNT_ANLY_3   SEG_COUNT;

PROC SQL noprint;
	SYSECHO "Key Statistics - Step 13/21";
    %*-- Put all variables with ANLY_IND = 1 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_1_CSV separated by ", ",
			:ANLY_IND_1_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 1;
    %put ANLY_IND_1_CSV and ANLY_IND_1_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 2 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_2_CSV separated by ", ",
			:ANLY_IND_2_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 2;
    %put ANLY_IND_2_CSV and ANLY_IND_2_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 3 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_3_CSV separated by ", ",
			:ANLY_IND_3_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 3;
    %put ANLY_IND_3_CSV and ANLY_IND_3_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 4 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_4_CSV separated by ", ",
			:ANLY_IND_4_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 4;
    %put ANLY_IND_4_CSV and ANLY_IND_4_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 5 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_5_CSV separated by ", ",
			:ANLY_IND_5_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 5;
    %put ANLY_IND_5_CSV and ANLY_IND_5_SPACE have &sqlobs rows;

    %*-- Put all variables with ANLY_IND = 6 into macro variable for later --;
    select	Variable 
			,Variable
	into	:ANLY_IND_6_CSV separated by ", ",
			:ANLY_IND_6_SPACE separated by " "
	from output.Contents_Summary
        where Anly_ind = 6;
    %put ANLY_IND_6_CSV and ANLY_IND_6_SPACE have &sqlobs rows;

    %*-- Put all class variables into macro variable for later --;
    select	Variable 
			,Variable
	into	:CLASS_VARS_CSV separated by ", ",
			:CLASS_VARS_SPACE separated by " "
	from output.Contents_Summary
        where upcase(Stats) = "Y";
    %put CLASS_VARS_CSV and CLASS_VARS_SPACE have &sqlobs rows;
QUIT;

%macro Initialise_Means_Anly_1;
	/* Count the number of variables within the table matching the STATS = "Y" criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 14/21";
		Select Count(*)
			into :SEG_COUNT
		From output.Contents_Summary
			where STATS='Y';
	Quit;

	/* Create N number of &ANLY1_i. variables to insert variable names into */
	%let SEG_COUNT = %left(&SEG_COUNT.);
	%do i = 1 %to &SEG_COUNT.;
		%global ANLY1_&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 15/21";
		Select STRIP(VARIABLE)
			Into :ANLY1_1 - :ANLY1_&SEG_COUNT.
		From output.Contents_Summary
			where STATS='Y'
		;
	QUIT;
%mend Initialise_Means_Anly_1;
%Initialise_Means_Anly_1;

%macro Anly_1_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 1 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 16/21";
		Select Count(*)
			into :COUNT_ANLY_1
		From output.Contents_Summary
			where ANLY_IND=1;
	Quit;

	/* Create N number of ANLY_IND_1_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_1 = %left(&COUNT_ANLY_1.);
	%do i = 1 %to &COUNT_ANLY_1.;
		%global ANLY_IND_1_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 17/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_1_VAR1 - :ANLY_IND_1_VAR&COUNT_ANLY_1.
		From output.Contents_Summary
			where ANLY_IND=1;
	QUIT;
%mend Anly_1_Variables;
%Anly_1_Variables;

%macro Anly_2_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 2 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 18/21";
		Select Count(*)
			into :COUNT_ANLY_2
		From output.Contents_Summary
			where ANLY_IND=2;
	Quit;

	/* Create N number of ANLY_IND_2_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_2 = %left(&COUNT_ANLY_2.);
	%do i = 1 %to &COUNT_ANLY_2.;
		%global ANLY_IND_2_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 19/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_2_VAR1 - :ANLY_IND_2_VAR&COUNT_ANLY_2.
		From output.Contents_Summary
			where ANLY_IND=2;
	QUIT;
%mend Anly_2_Variables;
%Anly_2_Variables;

%macro Anly_3_Variables;
	/* Count the number of variables within the table matching the ANLY_IND = 3 criteria */
	Proc Sql noprint;
		SYSECHO "Key Statistics - Step 20/21";
		Select Count(*)
			into :COUNT_ANLY_3
		From output.Contents_Summary
			where ANLY_IND=3;
	Quit;

	/* Create N number of ANLY_IND_3_VAR&i. variables to insert variable names into */
	%let COUNT_ANLY_3 = %left(&COUNT_ANLY_3.);
	%do i = 1 %to &COUNT_ANLY_3.;
		%global ANLY_IND_3_VAR&i.;
	%end;

	/* Inserts Variable from table into macro variables created in above process */
	PROC SQL noprint;
		SYSECHO "Key Statistics - Step 21/21";
		Select 	STRIP(VARIABLE)
		Into	:ANLY_IND_3_VAR1 - :ANLY_IND_3_VAR&COUNT_ANLY_3.
		From output.Contents_Summary
			where ANLY_IND=3;
	QUIT;
%mend Anly_3_Variables;
%Anly_3_Variables;

/* Call macro that will perform the percentile summary. This will breakdown all variables
with an ANLY_IND = 1 value into percentiles and perform N, NMISS, MIN, MAX, SUM, STD metrics on */
%Percentile_Summary;

/* Call macro that will populate summary tables for the all variables */
/* This macro is to be used for ANLY_IND = 2,3,4,5 values */
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_2_SPACE., Frequency_2, 2);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_3_SPACE., Frequency_3, 3);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_4_SPACE., Frequency_4, 4);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_5_SPACE., Frequency_5, 5);
%one_way_summary(refi_lib.&Refi_DSN., &ANLY_IND_6_SPACE., Frequency_6, 6);

/* This macro combines all one way analyses conducted */
%Combine_Datasets;

/*----------------------------------------------------------------------------*/
/*-- E N D -------------------------------------------------------------------*/
/*----------------------------------------------------------------------------*/

options obs=max fullstimer mprint symbolgen mlogic compress=binary varinitchk=error MINOPERATOR;

/* Input data */
%let Start_Date=01APR2019;			/* Start date to loop data through */
%let Mth_Count=2;					/* Number of months to monitor */

%let dset_name = strategic_data_YYYYMM;	/* Case sensitive when creating libnames */
%let replace_string = YYYYMM;		/* Specify what part of string above to replace with date */

%let Tag = strategic_data;				/* Output Dataset Name */

/* Setup locations */
%let Location = /team/customer/James/Final_Strategic_data_04; /* Input Dataset Locations */
%let Out_Location = /team/customer/James/MARCH_APRIL; /* Output Dataset Location */

/* Libname setup for MoM analysis */
%Macro Libsetup;
	/*	Setup input locations for each month*/
	%do i = 1 %to &Mth_Count.;
		%let Date_ddmmmyyyy = %SysFunc(Putn(%SysFunc(INTNX(Month,"&Start_Date."d,%eval(1-&i.))),date9.));
		%let Date_yyyy = %eval(%sysfunc(putn(%SYSFUNC(INTNX(MONTH,"&Date_ddmmmyyyy."d,0)),yymmn6.)));

		%global dset_name_&i.;
		%let dset_name_&i. = %SYSFUNC(TRANWRD(&dset_name., &replace_string., &Date_yyyy.));

		Libname Lib_&i. "&Location./&&dset_name_&i.." ACCESS=READONLY;
	%end;

	/* Setup output location */
	Libname lib_out "&Out_Location.";
%Mend Libsetup;
%Libsetup;

/* Pull all variables and groupings into one dataset and de-duplicate. This is to ensure all 
variables and groupings are captured, despite if they exist on one dataset and not on another */
%Macro Contents_Dedup;
	/* Pull in all data from different datasets */
	data Contents_data;
		set 
		%do i = 1 %to &Mth_Count.;
			Lib_&i..contents_summary (keep=Variable Label) 
		%end;
		;
		Variable = UPCASE(Variable);
	run;

	/* De-duplicate data and sort by variable */
	proc sort data=Contents_data nodupkey
		Out=Contents_deduped;
		by Variable;
	run;
%Mend Contents_Dedup;
%Contents_Dedup;

/* Extract all data from various folders and concatenate together */
%macro Contents_Data_Merge;
	%do i = 1 %to &Mth_Count.;
		%iterm(&i.); /* Convert do loop counter to a character */
	%end;

	/* Pull in all data into one dataset - merge onto deduped data create above */
	Proc SQL;
	Create table MoM_Contents_Merge as
		Select	Contents_deduped.Variable as Variable_0
				,Contents_deduped.Label as Label_0

			%do i = 1 %to &Mth_Count.;
				,&&countvar_&i...Variable as Variable_&i.
				,&&countvar_&i...Count as Count_&i.
				,&&countvar_&i...Filled as Filled_&i.
				,&&countvar_&i...NMiss as NMiss_&i.
				,&&countvar_&i...Miss_Pct as Miss_Pct_&i.
				,&&countvar_&i...Unique as Unique_&i.
				,&&countvar_&i...Unique_Pct as Unique_Pct_&i.
				,&&countvar_&i...Unique_Pct_All as Unique_Pct_All_&i.
				,&&countvar_&i...Anly_ind as Anly_ind_&i.
			%end;

		From Contents_deduped
			%do i = 1 %to &Mth_Count.;
				Left Join Lib_&i..contents_summary &&countvar_&i..
				  on UPCASE(Contents_deduped.Variable) = UPCASE(&&countvar_&i...Variable)
			%end;
		;
	Quit;
%mend Contents_Data_Merge;
%Contents_Data_Merge;

/* Create comparison data */
%macro Contents_Comparison;
	Data lib_out.&Tag._Contents;
	set MoM_Contents_Merge;		/* Pull in the merged data and calculate differences */

	/* Multiple do loops used below to control the output structure */
		/* Count - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Count_diff_&i. = Count_&i. - Count_%eval(&i.+1);
			label Count_diff_&i. = "Count: Number of differences";
		%end;
		%do i = 1 %to (&Mth_Count. - 1);
			Count_pct_diff_&i. = Count_diff_&i./Count_%eval(&i.+1);
			label Count_pct_diff_&i. = "Count: Percent difference";
			Format Count_pct_diff_&i. PERCENTN12.4;
		%end;

		/* Filled - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Filled_diff_&i. =  Filled_&i. - Filled_%eval(&i.+1);
			label Filled_diff_&i. = "Filled: Difference";
			Format Filled_diff_&i. PERCENTN12.4;
		%end;

		/* NMiss - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			NMiss_diff_&i. =  NMiss_&i. - NMiss_%eval(&i.+1);
			label NMiss_diff_&i. = "NMiss: Number of differences";
		%end;
		%do i = 1 %to (&Mth_Count. - 1);
			NMiss_pct_diff_&i. = NMiss_diff_&i./NMiss_%eval(&i.+1);
			label NMiss_pct_diff_&i. = "NMiss: Percent difference";
			Format NMiss_pct_diff_&i. PERCENTN12.4;
		%end;

		/* Miss_Pct - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Miss_Pct_diff_&i. =  Miss_Pct_&i. - Miss_Pct_%eval(&i.+1);
			label Miss_Pct_diff_&i. = "Miss_Pct: Difference";
			Format Miss_Pct_diff_&i. PERCENTN12.4;
		%end;

		/* Unique - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Unique_diff_&i. =  Unique_&i. - Unique_%eval(&i.+1);
			label Unique_diff_&i. = "Unique: Number of differences";
		%end;
		%do i = 1 %to (&Mth_Count. - 1);
			Unique_pct_diff_&i. = Unique_diff_&i./Unique_%eval(&i.+1);
			label Unique_pct_diff_&i. = "Unique: Percent difference";
			Format Unique_pct_diff_&i. PERCENTN12.4;
		%end;

		/* Unique_Pct - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Unique_Pct_diff2_&i. =  Unique_Pct_&i. - Unique_Pct_%eval(&i.+1);
			label Unique_Pct_diff2_&i. = "Unique_Pct: Difference";
			Format Unique_Pct_diff2_&i. PERCENTN12.4;
		%end;

		/* Unique_Pct_All - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Unique_Pct_All_diff_&i. = Unique_Pct_All_&i. - Unique_Pct_All_%eval(&i.+1);
			label Unique_Pct_All_diff_&i. = "Unique_Pct_All: Difference";
			Format Unique_Pct_All_diff_&i. PERCENTN12.4;
		%end;

		/* Anly_ind - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Anly_ind_diff_&i. =  Anly_ind_&i. - Anly_ind_%eval(&i.+1);
			label Anly_ind_diff_&i. = "Anly_ind: Difference";
		%end;
	run;
%mend Contents_Comparison;
%Contents_Comparison;

options obs=max fullstimer mprint symbolgen mlogic compress=binary varinitchk=error MINOPERATOR;

/* Input data */
%let Start_Date=01NOV2018;			/* Start date to loop data through */
%let Mth_Count=18;					/* Number of months to monitor */

%let dset_name = values_YYYYMM;	/* Case sensitive when creating libnames */
%let replace_string = YYYYMM;		/* Specify what part of string above to replace with date */

%let Tag = VALUES;				/* Output Dataset Name */

/* Setup locations */
%let Location = /team/customer/Simplification/Internal Bureau Remediation/Data/Profiling/Profiling Outputs; /* Input Dataset Locations */
%let Out_Location = /team/customer/Simplification/Internal Bureau Remediation/Data/Monitoring/201802; /* Output Dataset Location */

/* Libname setup for MoM analysis */
%Macro Libsetup;
	/*	Setup input locations for each month*/
	%do i = 1 %to &Mth_Count.;
		%let Date_ddmmmyyyy = %SysFunc(Putn(%SysFunc(INTNX(Month,"&Start_Date."d,%eval(1-&i.))),date9.));
		%let Date_yyyy = %eval(%sysfunc(putn(%SYSFUNC(INTNX(MONTH,"&Date_ddmmmyyyy."d,0)),yymmn6.)));

		%global dset_name_&i.;
		%let dset_name_&i. = %SYSFUNC(TRANWRD(&dset_name., &replace_string., &Date_yyyy.));

		Libname Lib_&i. "&Location./&&dset_name_&i.." ACCESS=READONLY;
	%end;

	/* Setup output location */
	Libname lib_out "&Out_Location.";
%Mend Libsetup;
%Libsetup;

/* Pull all variables and groupings into one dataset and de-duplicate. This is to ensure all 
variables and groupings are captured, despite if they exist on one dataset and not on another */
%Macro Percentile_Dedup;
	/* Pull in all data from different datasets */
	data Percentile_data;
		set 
		%do i = 1 %to &Mth_Count.;
			Lib_&i..percentile_summary (keep=Variable Grouping Label) 
		%end;
		;
		Variable = UPCASE(Variable);
	run;

	/* De-duplicate data and sort by variable then grouping */
	proc sort data=Percentile_data nodupkey
		Out=Percentile_deduped;
		by Variable Grouping;
	run;
%Mend Percentile_Dedup;
%Percentile_Dedup;

/* Extract all data from various folders and concatenate together */
%macro Percentile_Data_Merge;
	%do i = 1 %to &Mth_Count.;
		%iterm(&i.); /* Convert do loop counter to a character */
	%end;

	/* Pull in all data into one dataset - merge onto deduped data create above */
	Proc SQL;
	Create table MoM_Percentile_Merge as
		Select	Percentile_deduped.Variable as Variable_0
				,Percentile_deduped.Label as Label_0
				,Percentile_deduped.Grouping as Grouping_0

			%do i = 1 %to &Mth_Count.;
				,&&countvar_&i...Variable as Variable_&i.
				,&&countvar_&i...Grouping as Grouping_&i.
				,&&countvar_&i..._TYPE_ as Type_&i.
				,&&countvar_&i..._FREQ_ as Frequency_&i.
				,&&countvar_&i...N as N_&i.
				,&&countvar_&i...NMISS as NMISS_&i.
				,&&countvar_&i...MIN as MIN_&i.
				,&&countvar_&i...MAX as MAX_&i.
				,&&countvar_&i...MEAN as MEAN_&i.
				,&&countvar_&i...SUM as SUM_&i.
				,&&countvar_&i...STD as STD_&i.
			%end;

		From Percentile_deduped
			%do i = 1 %to &Mth_Count.;
				Left Join Lib_&i..percentile_summary &&countvar_&i..
					on (UPCASE(Percentile_deduped.Variable) = UPCASE(&&countvar_&i...Variable)) AND 
					(UPCASE(Percentile_deduped.GROUPING) = UPCASE(&&countvar_&i...GROUPING))
			%end;
		;
	Quit;
%mend Percentile_Data_Merge;
%Percentile_Data_Merge;

/* Create comparison data */
%macro Percentile_Comparison;
	Data lib_out.&Tag._Percentile;
	set MoM_Percentile_Merge;		/* Pull in the merged data and calculate differences */

	/* Multiple do loops used below to control the output structure */
		/* N - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			N_diff_&i. = N_&i. - N_%eval(&i.+1);
			label N_diff_&i. = "N: Number of differences";
		%end;
		/* N - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			N_pct_diff_&i. = N_diff_&i./N_%eval(&i.+1);
			label N_pct_diff_&i. = "N: Percent difference";
			Format N_pct_diff_&i. PERCENTN12.4;
		%end;

		/* NMISS - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			NMISS_diff_&i. = NMISS_&i. - NMISS_%eval(&i.+1);
			label NMISS_diff_&i. = "NMISS: Number of differences";
		%end;
		/* NMISS - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			NMISS_pct_diff_&i. = NMISS_diff_&i./NMISS_%eval(&i.+1);
			label NMISS_pct_diff_&i. = "NMISS: Percent difference";
			Format NMISS_pct_diff_&i. PERCENTN12.4;
		%end;

		/* MIN - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MIN_diff_&i. = MIN_&i. - MIN_%eval(&i.+1);
			label MIN_diff_&i. = "MIN: Number of differences";
		%end;
		/* MIN - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MIN_pct_diff_&i. = MIN_diff_&i./MIN_%eval(&i.+1);
			label MIN_pct_diff_&i. = "MIN: Percent difference";
			Format MIN_pct_diff_&i. PERCENTN12.4;
		%end;

		/* MAX - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MAX_diff_&i. = MAX_&i. - MAX_%eval(&i.+1);
			label MAX_diff_&i. = "MAX: Number of differences";
		%end;
		/* MAX - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MAX_pct_diff_&i. = MAX_diff_&i./MAX_%eval(&i.+1);
			label MAX_pct_diff_&i. = "MAX: Percent difference";
			Format MAX_pct_diff_&i. PERCENTN12.4;
		%end;

		/* MAX - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MAX_diff_&i. = MAX_&i. - MAX_%eval(&i.+1);
			label MAX_diff_&i. = "MAX: Number of differences";
		%end;
		/* MAX - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MAX_pct_diff_&i. = MAX_diff_&i./MAX_%eval(&i.+1);
			label MAX_pct_diff_&i. = "MAX: Percent difference";
			Format MAX_pct_diff_&i. PERCENTN12.4;
		%end;

		/* MEAN - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MEAN_diff_&i. = MEAN_&i. - MEAN_%eval(&i.+1);
			label MEAN_diff_&i. = "MEAN: Number of differences";
		%end;
		/* MEAN - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			MEAN_pct_diff_&i. = MEAN_diff_&i./MEAN_%eval(&i.+1);
			label MEAN_pct_diff_&i. = "MEAN: Percent difference";
			Format MEAN_pct_diff_&i. PERCENTN12.4;
		%end;

		/* SUM - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			SUM_diff_&i. = SUM_&i. - SUM_%eval(&i.+1);
			label SUM_diff_&i. = "SUM: Number of differences";
		%end;
		/* SUM - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			SUM_pct_diff_&i. = SUM_diff_&i./SUM_%eval(&i.+1);
			label SUM_pct_diff_&i. = "SUM: Percent difference";
			Format SUM_pct_diff_&i. PERCENTN12.4;
		%end;

		/* STD - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			STD_diff_&i. = STD_&i. - STD_%eval(&i.+1);
			label STD_diff_&i. = "STD: Number of differences";
		%end;
		/* STD - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			STD_pct_diff_&i. = STD_diff_&i./STD_%eval(&i.+1);
			label STD_pct_diff_&i. = "STD: Percent difference";
			Format STD_pct_diff_&i. PERCENTN12.4;
		%end;
	run;
%mend Percentile_Comparison;
%Percentile_Comparison;

options obs=max fullstimer mprint symbolgen mlogic compress=binary varinitchk=error MINOPERATOR;

/* Input data */
%let Start_Date=01NOV2018;			/* Start date to loop data through */
%let Mth_Count=12;					/* Number of months to monitor */

%let dset_name = values_YYYYMM;	/* Case sensitive when creating libnames */
%let replace_string = YYYYMM;		/* Specify what part of string above to replace with date */

%let Tag = VALUES;				/* Output Dataset Name */

/* Setup locations */
%let Location = /team/customer/Simplification/Internal Bureau Remediation/Data/Profiling/Profiling Outputs; /* Input Dataset Locations */
%let Out_Location = /team/customer/Simplification/Internal Bureau Remediation/Data/Monitoring/201802; /* Output Dataset Location */

/* Libname setup for MoM analysis */
%Macro Libsetup;
	/*	Setup input locations for each month*/
	%do i = 1 %to &Mth_Count.;
		%let Date_ddmmmyyyy = %SysFunc(Putn(%SysFunc(INTNX(Month,"&Start_Date."d,%eval(1-&i.))),date9.));
		%let Date_yyyy = %eval(%sysfunc(putn(%SYSFUNC(INTNX(MONTH,"&Date_ddmmmyyyy."d,0)),yymmn6.)));

		%global dset_name_&i.;
		%let dset_name_&i. = %SYSFUNC(TRANWRD(&dset_name., &replace_string., &Date_yyyy.));

		Libname Lib_&i. "&Location./&&dset_name_&i.." ACCESS=READONLY;
	%end;

	/* Setup output location */
	Libname lib_out "&Out_Location.";
%Mend Libsetup;
%Libsetup;

/* Pull all variables and groupings into one dataset and de-duplicate. This is to ensure all 
variables and groupings are captured, despite if they exist on one dataset and not on another */
%Macro frequency_Dedup;
	/* Pull in all data from different datasets */
	data frequency_data;
		set 
		%do i = 1 %to &Mth_Count.;
			Lib_&i..frequency_summary (keep=Variable Grouping Label) 
		%end;
		;
		Variable = UPCASE(Variable);
	run;

	/* De-duplicate data and sort by variable then grouping */
	proc sort data=frequency_data nodupkey
		Out=frequency_deduped;
		by Variable Grouping;
	run;
%Mend frequency_Dedup;
%frequency_Dedup;

/* Extract all data from various folders and concatenate together */
%macro Frequency_Data_Merge;
	%do i = 1 %to &Mth_Count.;
		%iterm(&i.); /* Convert do loop counter to a character */
	%end;

	/* Pull in all data into one dataset - merge onto deduped data create above */
	Proc SQL;
	Create table MoM_frequency_Merge as
		Select	frequency_deduped.Variable as Variable_0
				,frequency_deduped.Label as Label_0
				,frequency_deduped.Grouping as Grouping_0

			%do i = 1 %to &Mth_Count.;
				,&&countvar_&i...Variable as Variable_&i.
				,&&countvar_&i...Label as Label_&i.
				,&&countvar_&i...Grouping as Grouping_&i.
				,&&countvar_&i...Count as Count_&i.
				,&&countvar_&i...Percent as Percent_&i.
				,&&countvar_&i...ANLY_IND as Anly_Ind_&i.
			%end;

		From frequency_deduped
			%do i = 1 %to &Mth_Count.;
				Left Join Lib_&i..frequency_summary &&countvar_&i..
				on (UPCASE(frequency_deduped.Variable) = UPCASE(&&countvar_&i...Variable)) AND 
				(UPCASE(frequency_deduped.GROUPING) = UPCASE(&&countvar_&i...GROUPING))
			%end;
		;
	Quit;
%mend Frequency_Data_Merge;
%Frequency_Data_Merge;

/* Create comparison data */
%macro Frequency_Comparison;
	Data lib_out.&Tag._Frequency;
	set MoM_Frequency_Merge;		/* Pull in the merged data and calculate differences */

	/* Multiple do loops used below to control the output structure */
		/* Count - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Count_diff_&i. = Count_&i. - Count_%eval(&i.+1);
			label Count_diff_&i. = "Count: Number of differences";
		%end;
		/* Count - % Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Count_pct_diff_&i. = Count_diff_&i./Count_%eval(&i.+1);
			label Count_pct_diff_&i. = "Count: Percent difference";
			Format Count_pct_diff_&i. PERCENTN12.4;
		%end;

		/* Percent - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Percent_diff_&i. = Percent_&i. - Percent_%eval(&i.+1);
			label Percent_diff_&i. = "Percent: Number of differences";
			Format Percent_diff_&i. PERCENTN12.4;
		%end;

		/* Anly_ind - Differences Calculation */
		%do i = 1 %to (&Mth_Count. - 1);
			Anly_ind_diff_&i. =  Anly_ind_&i. - Anly_ind_%eval(&i.+1);
			label Anly_ind_diff_&i. = "Anly_ind: Difference";
		%end;
	run;
%mend Frequency_Comparison;
%Frequency_Comparison;

[ballardw]

Turn on: Options MPRINT Fullstimer; before running the job next time.

READ the log for the  places that take a lot of time.

You might find that a data step runs faster than

PROC SQL;
	SYSECHO "Formatting 4/4 - ANLY_IND 1 - Step 2/4 - Sub Step &k./&COUNT_ANLY_1.";
	CREATE TABLE ranked_out(drop=N Var_Rank) AS	
		SELECT 	*,
				CASE	WHEN N = . THEN 'Missing'
						WHEN N <= CEIL(MIN(N) + (MAX(N) - MIN(N) + 1)*  1/100 - 1)  THEN '0% to 1%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)*  5/100 - 1  		THEN '1% to 5%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 10/100 - 1  		THEN '5% to 10%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 25/100 - 1  		THEN '10% to 25%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 50/100 - 1  		THEN '25% to 50%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 75/100 - 1 		THEN '50% to 75%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 90/100 - 1  		THEN '75% to 90%'
						WHEN N <= MIN(N) + (MAX(N) - MIN(N) + 1)* 95/100 - 1  		THEN '90% to 95%'
						WHEN N <= FLOOR(MIN(N) + (MAX(N) - MIN(N) + 1)* 99/100 - 1) THEN '95% to 99%'
						ELSE '99% to 100%'
	  		END AS VAR_SEG			/* Percentile Segmentation variable */		
		FROM ranked
		;
	QUIT;

The above step indicates that almost every single end point of your range result appears in 2 ranges. So when yu have exactly 75% which range should a value go into?

You are apparently rerunning Proc format code multiple times to create a same named formats with values that do not change:

%if (&type. in (1, 5)) %then %do;
			proc format;
			value POP_FMT (multilabel)
				. = "Missing"
				other = "Populated"
			;
			run;
		%end;
		%else %if (&type. = 4) %then %do;
			proc format;
			value $ POP_FMT (multilabel)
				' ' = "Missing"
				other = "Populated"
			;
			run;
		%end;

Create the formats ONE time, and if you are doing this at all often then the format likely belongs in a permanent library and add that to your FMTSEARCH path and quit wasting cpu cycles on repetitive code.

I think that it might be time to actually look at what Proc summary can do in the counting multiple variables and examining _TYPE_ values. I think you are going back through the same data repeatedly to get a summary for a single variable when not needed.

What is this supposed to actually accomplish. I do not have the hours of time to try to parse code and without input data to examine what the results possibly could be...

How big is the input data set, in terms of records and variables?

SAS can easily run into IO issues and slow network, slow disks, or code that makes data read/write to the disks more often than needed can have performance issues.

I would say that I think you have considerable wasted cycles with your Iterm macro. Since it creates global macro variables that are invariate (they don't change values in any way, you may just use fewer of them at some point) then create the list ONE time in the session. You are calling that sucker in every single macro practically.