如何使用 table 2 中的信息重新编码 table 1 中的变量（在 SAS 中）
How to recode variables in table 1 using info from table 2 (in SAS)
The overal goal is to stratify quantitative variables based on their percentile. I would like to break it up into 10 levels (e.g. 10th, 20th, ...100th percentile) and recode it as 1 if it falls into the 10th percentile, 2 if it falls into the 20th percentile, etc. This method needs to be applicable across any data set I plug in and I want this process to be as automated as possible. Below I have generated some test data:
data test (drop=i);
do i=1 to 1000;
a=round(uniform(1)*4,.01);
b=round(uniform(1)*10,.01);
c=round(uniform(1)*7.5,.01);
output;
end;
stop;
run;
The following macro is used to create a table of values that tells you the cut off for the 10 percentiles of each variable. I have added a picture of the example output below the code.
/*Recode variables based on quartiles from boxplot*/
%macro percentiles(var);
/* Count the number of values in the strinrecode */
%let count=%sysfunc(countw(&var));
/* Loop throurecodeh the total number of values */
%do i = 1 %to &count;
%let variables=%qscan(&var,&i,%str(,));
proc univariate data=test noprint;
var &variables;
output out=pcts pctlpts = 10 20 30 40 50 60 70 80 90 100
pctlpre = &variables;
run;
proc transpose data=pcts out=&variables (rename=(col1=&variables) drop=_NAME_ _LABEL_);
run;
%end;
data percentiles (drop=i);
do i=1 to 10;
recode=i;
percentile=i*10;
output;
end;
stop;
run;
data pcts;
merge percentiles %sysfunc(tranwrd(&var.,%str(,),%str( )));
run;
%mend;
%percentiles(%str(a,b,c));
output from above macro
The following code is how I am currently recoding my variables. I use the table generated in the above macro to fill in the cut off points for each percentile for each variable. As you can see, this is very tedious and will become prohibitive if I have a large number of variables to recode. Is there a better process for this or preferably a way I could automate this part?
data test;
set test;
if a <= .415 then recode_a = 1; else if a <= .785 then recode_a = 2; else if a <= 1.255 then recode_a = 3;
else if a <= 1.61 then recode_a = 4; else if a <= 2.03 then recode_a = 5; else if a <= 2.42 then recode_a = 6;
else if a <= 2.76 then recode_a = 7; else if a <= 3.18 then recode_a = 8; else if a <= 3.64 then recode_a = 9;
else if a <= 3.99 then recode_a = 10;
if b <= .845 then recode_b = 1; else if b <= 1.88 then recode_b = 2; else if b <= 2.86 then recode_b = 3;
else if b <= 4.005 then recode_b = 4; else if b <= 5.03 then recode_b = 5; else if b <= 6.07 then recode_b = 6;
else if b <= 6.995 then recode_b = 7; else if b <= 8.035 then recode_b = 8; else if b <= 9.16 then recode_b = 9;
else if b <= 10 then recode_b = 10;
if c <= .86 then recode_c = 1; else if c <= 1.58 then recode_c = 2; else if c <= 2.34 then recode_c = 3;
else if c <= 3.15 then recode_c = 4; else if c <= 3.85 then recode_c = 5; else if c <= 4.615 then recode_c = 6;
else if c <= 5.315 then recode_c = 7; else if c <= 5.96 then recode_c = 8; else if c <= 6.75 then recode_c = 9;
else if c <= 7.5 then recode_c = 10;
run;
proc print data=test (obs=5);
run;
sample of desired output
以下内容无需硬编码即可动态地为您工作——我进行了编辑以将其压缩为单个宏。本质上，它将您想要的变量放入一个列表中，使用您的输出创建一个数据集，然后使用变量内容将您的数据步骤放入长字符串中。然后将这些字符串放入一个宏变量中，您可以在最后的数据步骤中调用它。同样，不涉及硬编码。
%MACRO stratify(library=,input=,output=);
%local varlist varlist_space data_step_list;
** get vars into comma-separated list and space-separated list **;
proc sql noprint;
select NAME
into: varlist separated by ","
from dictionary.columns
where libname=upcase("&library.") and memname=upcase("&input.");
select NAME
into: varlist_space separated by " "
from dictionary.columns
where libname=upcase("&library.") and memname=upcase("&input.");
quit;
%percentiles(%bquote(&varlist.));
** put data into long format **;
proc transpose data = pcts out=pcts_long;
by recode percentile;
var &varlist_space.;
run;
** sort to get if-else order **;
proc sort data = pcts_long;
by _NAME_ percentile;
run;
** create your if-then strings using data itself **;
data str;
length STR 0;
set pcts_long;
bin = percentile/10;
by _NAME_;
if first._NAME_ then do;
STR = "if "||strip(_NAME_)||" <= "||strip(put(COL1,best.))||" then "||catx("_","recode",_NAME_)||" = "||strip(put(bin,best.))||";";
end;
else do;
STR = "else if "||strip(_NAME_)||" <= "||strip(put(COL1,best.))||" then "||catx("_","recode",_NAME_)||" = "||strip(put(bin,best.))||";";
end;
run;
** put strings into a list **;
proc sql noprint;
select STR
into: data_step_list separated by " "
from STR;
quit;
** call data step list in final data **;
data &output.; set &input.;
&data_step_list.;
run;
proc print data = &output.(obs=5);
run;
%MEND;
%stratify(library=work,input=test,output=final);
不需要所有的代码生成。只需使用一个数组。基本上将 PROC UNIVARIATE 生成的数据集中的百分位数加载到二维数组中，然后找到实际值的十分位数。
%macro stratify(varlist,in=,out=,pcts=pcts);
%local nvars pctls droplist recodes ;
%let varlist=%sysfunc(compbl(&varlist));
%let nvars=%sysfunc(countw(&varlist));
%let pctls=pctl_%sysfunc(tranwrd(&varlist,%str( ),%str( pctl_)));
%let droplist=pctl_%sysfunc(tranwrd(&varlist,%str( ),%str(: pctl_))):;
%let recodes=recode_%sysfunc(tranwrd(&varlist,%str( ),%str( recode_)));
proc univariate data=&in noprint ;
var &varlist;
output out=&pcts pctlpre=&pctls
pctlpts = 10 20 30 40 50 60 70 80 90 100
;
run;
data want ;
if _n_=1 then set &pcts ;
array _pcts (10,&nvars) _numeric_;
set test;
array _in &varlist ;
array out &recodes ;
do i=1 to dim(_in);
do j=1 to 10 while(_in(i) > _pcts(j,i));
end;
out(i)=j;
end;
drop i j &droplist;
run;
%mend stratify;
因此，如果我使用您生成的样本，这里是打开 MPRINT 选项后日志的样子。
1093 %stratify(a b c,in=test,out=want);
MPRINT(STRATIFY): proc univariate data=test noprint ;
MPRINT(STRATIFY): var a b c;
MPRINT(STRATIFY): output out=pcts pctlpre=pctl_a pctl_b pctl_c pctlpts = 10 20 30 40 50
60 70 80 90 100 ;
MPRINT(STRATIFY): run;
NOTE: The data set WORK.PCTS has 1 observations and 30 variables.
NOTE: PROCEDURE UNIVARIATE used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
MPRINT(STRATIFY): data want ;
MPRINT(STRATIFY): if _n_=1 then set pcts ;
MPRINT(STRATIFY): array _pcts (10,3) _numeric_;
MPRINT(STRATIFY): set test;
MPRINT(STRATIFY): array _in a b c ;
MPRINT(STRATIFY): array out recode_a recode_b recode_c ;
MPRINT(STRATIFY): do i=1 to dim(_in);
MPRINT(STRATIFY): do j=1 to 10 while(_in(i) > _pcts(j,i));
MPRINT(STRATIFY): end;
MPRINT(STRATIFY): out(i)=j;
MPRINT(STRATIFY): end;
MPRINT(STRATIFY): drop i j pctl_a: pctl_b: pctl_c:;
MPRINT(STRATIFY): run;
NOTE: There were 1 observations read from the data set WORK.PCTS.
NOTE: There were 1000 observations read from the data set WORK.TEST.
NOTE: The data set WORK.WANT has 1000 observations and 6 variables
前五个观察结果是：
另一个选项 - PROC RANK。您可以将它做得更多 'automated'，但它非常简单。使用 PROC RANK，您还可以指定处理平局的不同方式。请注意，它会从 0 到 9 而不是 1 到 10，但这很容易改变。
data test (drop=i);
do i=1 to 1000;
a=round(uniform(1)*4,.01);
b=round(uniform(1)*10,.01);
c=round(uniform(1)*7.5,.01);
output;
end;
stop;
run;
proc rank data=test out=want groups=10;
var a b c;
ranks rankA rankB rankC;
run;
The overal goal is to stratify quantitative variables based on their percentile. I would like to break it up into 10 levels (e.g. 10th, 20th, ...100th percentile) and recode it as 1 if it falls into the 10th percentile, 2 if it falls into the 20th percentile, etc. This method needs to be applicable across any data set I plug in and I want this process to be as automated as possible. Below I have generated some test data:
data test (drop=i);
do i=1 to 1000;
a=round(uniform(1)*4,.01);
b=round(uniform(1)*10,.01);
c=round(uniform(1)*7.5,.01);
output;
end;
stop;
run;
The following macro is used to create a table of values that tells you the cut off for the 10 percentiles of each variable. I have added a picture of the example output below the code.
/*Recode variables based on quartiles from boxplot*/
%macro percentiles(var);
/* Count the number of values in the strinrecode */
%let count=%sysfunc(countw(&var));
/* Loop throurecodeh the total number of values */
%do i = 1 %to &count;
%let variables=%qscan(&var,&i,%str(,));
proc univariate data=test noprint;
var &variables;
output out=pcts pctlpts = 10 20 30 40 50 60 70 80 90 100
pctlpre = &variables;
run;
proc transpose data=pcts out=&variables (rename=(col1=&variables) drop=_NAME_ _LABEL_);
run;
%end;
data percentiles (drop=i);
do i=1 to 10;
recode=i;
percentile=i*10;
output;
end;
stop;
run;
data pcts;
merge percentiles %sysfunc(tranwrd(&var.,%str(,),%str( )));
run;
%mend;
%percentiles(%str(a,b,c));
output from above macro
The following code is how I am currently recoding my variables. I use the table generated in the above macro to fill in the cut off points for each percentile for each variable. As you can see, this is very tedious and will become prohibitive if I have a large number of variables to recode. Is there a better process for this or preferably a way I could automate this part?
data test;
set test;
if a <= .415 then recode_a = 1; else if a <= .785 then recode_a = 2; else if a <= 1.255 then recode_a = 3;
else if a <= 1.61 then recode_a = 4; else if a <= 2.03 then recode_a = 5; else if a <= 2.42 then recode_a = 6;
else if a <= 2.76 then recode_a = 7; else if a <= 3.18 then recode_a = 8; else if a <= 3.64 then recode_a = 9;
else if a <= 3.99 then recode_a = 10;
if b <= .845 then recode_b = 1; else if b <= 1.88 then recode_b = 2; else if b <= 2.86 then recode_b = 3;
else if b <= 4.005 then recode_b = 4; else if b <= 5.03 then recode_b = 5; else if b <= 6.07 then recode_b = 6;
else if b <= 6.995 then recode_b = 7; else if b <= 8.035 then recode_b = 8; else if b <= 9.16 then recode_b = 9;
else if b <= 10 then recode_b = 10;
if c <= .86 then recode_c = 1; else if c <= 1.58 then recode_c = 2; else if c <= 2.34 then recode_c = 3;
else if c <= 3.15 then recode_c = 4; else if c <= 3.85 then recode_c = 5; else if c <= 4.615 then recode_c = 6;
else if c <= 5.315 then recode_c = 7; else if c <= 5.96 then recode_c = 8; else if c <= 6.75 then recode_c = 9;
else if c <= 7.5 then recode_c = 10;
run;
proc print data=test (obs=5);
run;
sample of desired output
以下内容无需硬编码即可动态地为您工作——我进行了编辑以将其压缩为单个宏。本质上，它将您想要的变量放入一个列表中，使用您的输出创建一个数据集，然后使用变量内容将您的数据步骤放入长字符串中。然后将这些字符串放入一个宏变量中，您可以在最后的数据步骤中调用它。同样，不涉及硬编码。
%MACRO stratify(library=,input=,output=);
%local varlist varlist_space data_step_list;
** get vars into comma-separated list and space-separated list **;
proc sql noprint;
select NAME
into: varlist separated by ","
from dictionary.columns
where libname=upcase("&library.") and memname=upcase("&input.");
select NAME
into: varlist_space separated by " "
from dictionary.columns
where libname=upcase("&library.") and memname=upcase("&input.");
quit;
%percentiles(%bquote(&varlist.));
** put data into long format **;
proc transpose data = pcts out=pcts_long;
by recode percentile;
var &varlist_space.;
run;
** sort to get if-else order **;
proc sort data = pcts_long;
by _NAME_ percentile;
run;
** create your if-then strings using data itself **;
data str;
length STR 0;
set pcts_long;
bin = percentile/10;
by _NAME_;
if first._NAME_ then do;
STR = "if "||strip(_NAME_)||" <= "||strip(put(COL1,best.))||" then "||catx("_","recode",_NAME_)||" = "||strip(put(bin,best.))||";";
end;
else do;
STR = "else if "||strip(_NAME_)||" <= "||strip(put(COL1,best.))||" then "||catx("_","recode",_NAME_)||" = "||strip(put(bin,best.))||";";
end;
run;
** put strings into a list **;
proc sql noprint;
select STR
into: data_step_list separated by " "
from STR;
quit;
** call data step list in final data **;
data &output.; set &input.;
&data_step_list.;
run;
proc print data = &output.(obs=5);
run;
%MEND;
%stratify(library=work,input=test,output=final);
不需要所有的代码生成。只需使用一个数组。基本上将 PROC UNIVARIATE 生成的数据集中的百分位数加载到二维数组中，然后找到实际值的十分位数。
%macro stratify(varlist,in=,out=,pcts=pcts);
%local nvars pctls droplist recodes ;
%let varlist=%sysfunc(compbl(&varlist));
%let nvars=%sysfunc(countw(&varlist));
%let pctls=pctl_%sysfunc(tranwrd(&varlist,%str( ),%str( pctl_)));
%let droplist=pctl_%sysfunc(tranwrd(&varlist,%str( ),%str(: pctl_))):;
%let recodes=recode_%sysfunc(tranwrd(&varlist,%str( ),%str( recode_)));
proc univariate data=&in noprint ;
var &varlist;
output out=&pcts pctlpre=&pctls
pctlpts = 10 20 30 40 50 60 70 80 90 100
;
run;
data want ;
if _n_=1 then set &pcts ;
array _pcts (10,&nvars) _numeric_;
set test;
array _in &varlist ;
array out &recodes ;
do i=1 to dim(_in);
do j=1 to 10 while(_in(i) > _pcts(j,i));
end;
out(i)=j;
end;
drop i j &droplist;
run;
%mend stratify;
因此，如果我使用您生成的样本，这里是打开 MPRINT 选项后日志的样子。
1093 %stratify(a b c,in=test,out=want);
MPRINT(STRATIFY): proc univariate data=test noprint ;
MPRINT(STRATIFY): var a b c;
MPRINT(STRATIFY): output out=pcts pctlpre=pctl_a pctl_b pctl_c pctlpts = 10 20 30 40 50
60 70 80 90 100 ;
MPRINT(STRATIFY): run;
NOTE: The data set WORK.PCTS has 1 observations and 30 variables.
NOTE: PROCEDURE UNIVARIATE used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
MPRINT(STRATIFY): data want ;
MPRINT(STRATIFY): if _n_=1 then set pcts ;
MPRINT(STRATIFY): array _pcts (10,3) _numeric_;
MPRINT(STRATIFY): set test;
MPRINT(STRATIFY): array _in a b c ;
MPRINT(STRATIFY): array out recode_a recode_b recode_c ;
MPRINT(STRATIFY): do i=1 to dim(_in);
MPRINT(STRATIFY): do j=1 to 10 while(_in(i) > _pcts(j,i));
MPRINT(STRATIFY): end;
MPRINT(STRATIFY): out(i)=j;
MPRINT(STRATIFY): end;
MPRINT(STRATIFY): drop i j pctl_a: pctl_b: pctl_c:;
MPRINT(STRATIFY): run;
NOTE: There were 1 observations read from the data set WORK.PCTS.
NOTE: There were 1000 observations read from the data set WORK.TEST.
NOTE: The data set WORK.WANT has 1000 observations and 6 variables
前五个观察结果是：
另一个选项 - PROC RANK。您可以将它做得更多 'automated'，但它非常简单。使用 PROC RANK，您还可以指定处理平局的不同方式。请注意，它会从 0 到 9 而不是 1 到 10，但这很容易改变。
data test (drop=i);
do i=1 to 1000;
a=round(uniform(1)*4,.01);
b=round(uniform(1)*10,.01);
c=round(uniform(1)*7.5,.01);
output;
end;
stop;
run;
proc rank data=test out=want groups=10;
var a b c;
ranks rankA rankB rankC;
run;