☑ This topic is solved.
Need further help from the community? Please
sign in and ask a new question.
1 ACCEPTED SOLUTION
Accepted Solutions
Hi,
Thanks for this code. There was no way I was coming up with something like this by myself.
I am running into some issues:
1. The code has run for 5 hours or so, and only 18% of the dates are complete. Is it normal to expect it to take that long?
2. Data lines are repeating themselves several times. For example, as you can see in the screenshot - every odd row up until row 29 is identical; as is every even row up until row 30. The number of repeats vary, from twice to 8 times (that I can see). (Note that I changed two of the variable names).
3. The _FREQ_ for before_after=1 is sometimes 31, but each FREQ should be 30 (or less if there is missing data). This results in incorrect values for hours_asleep or start_clocktime. This is not always the case, though - sometimes the _FREQ_ is correctly 30.
The log is way too long for me to include the entire thing, but I have a sample below:
108318 + data new; set SLEEP(where=(id= 376));
survey_date= 22713; if wake_date >= 22683 and wake_date <=
22713 then before_after=1; else if wake_date >= 22714
108319 + and wake_date <= 22743 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.09 seconds
cpu time 0.09 seconds
108319 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108320 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108320 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56934 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108321 + data new; set SLEEP(where=(id= 376));
survey_date= 22713; if wake_date >= 22683 and wake_date <=
22713 then before_after=1; else if wake_date >= 22714
108322 + and wake_date <= 22743 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.10 seconds
cpu time 0.11 seconds
108322 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108323 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108323 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56934 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108324 + data new; set SLEEP(where=(id= 376));
survey_date= 22713; if wake_date >= 22683 and wake_date <=
22713 then before_after=1; else if wake_date >= 22714
108325 + and wake_date <= 22743 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.10 seconds
cpu time 0.09 seconds
108325 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108326 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108326 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56934 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108327 + data new; set SLEEP(where=(id= 376));
survey_date= 22713; if wake_date >= 22683 and wake_date <=
22713 then before_after=1; else if wake_date >= 22714
108328 + and wake_date <= 22743 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.11 seconds
cpu time 0.11 seconds
108328 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108329 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108329 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56934 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108330 + data new; set SLEEP(where=(id= 376));
survey_date= 22701; if wake_date >= 22671 and wake_date <=
22701 then before_after=1; else if wake_date >= 22702
108331 + and wake_date <= 22731 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.10 seconds
cpu time 0.09 seconds
108331 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108332 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 1 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108332 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 1 observations read from the data set WORK._STATS_.
NOTE: 1 observations added.
NOTE: The data set WORK.ALL_STATS has 56935 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108333 + data new; set SLEEP(where=(id= 376));
survey_date= 22701; if wake_date >= 22671 and wake_date <=
22701 then before_after=1; else if wake_date >= 22702
108334 + and wake_date <= 22731 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.11 seconds
cpu time 0.10 seconds
108334 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108335 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 1 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108335 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 1 observations read from the data set WORK._STATS_.
NOTE: 1 observations added.
NOTE: The data set WORK.ALL_STATS has 56936 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108336 + data new; set SLEEP(where=(id= 376));
survey_date= 22701; if wake_date >= 22671 and wake_date <=
22701 then before_after=1; else if wake_date >= 22702
108337 + and wake_date <= 22731 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.08 seconds
cpu time 0.09 seconds
108337 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108338 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 1 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds
108338 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 1 observations read from the data set WORK._STATS_.
NOTE: 1 observations added.
NOTE: The data set WORK.ALL_STATS has 56937 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108339 + data new; set SLEEP(where=(id= 376));
survey_date= 22710; if wake_date >= 22680 and wake_date <=
22710 then before_after=1; else if wake_date >= 22711
108340 + and wake_date <= 22740 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.08 seconds
cpu time 0.07 seconds
108340 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108341 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108341 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56937 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108342 + data new; set SLEEP(where=(id= 376));
survey_date= 22710; if wake_date >= 22680 and wake_date <=
22710 then before_after=1; else if wake_date >= 22711
108343 + and wake_date <= 22740 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.10 seconds
cpu time 0.10 seconds
108343 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108344 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108344 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56937 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
108345 + data new; set SLEEP(where=(id= 376));
survey_date= 22710; if wake_date >= 22680 and wake_date <=
22710 then before_after=1; else if wake_date >= 22711
108346 + and wake_date <= 22740 then before_after=2; format survey_date
date9.; run;
NOTE: There were 80 observations read from the data set SLEEP.
WHERE id=376;
NOTE: The data set WORK.NEW has 80 observations and 241 variables.
NOTE: DATA statement used (Total process time):
real time 0.11 seconds
cpu time 0.10 seconds
108346 +
proc summary nway data=new; class before_after; id id survey_date;
var hours_asleep_w
108347 + start_clocktime_midcent_mean_w; output out=work._stats_ mean=
std=/autoname; run;
WARNING: A class or frequency variable is missing on every observation.
NOTE: There were 80 observations read from the data set WORK.NEW.
NOTE: The data set WORK._STATS_ has 0 observations and 9 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
108347 +
proc append base=all_stats new=work._stats_; run;
NOTE: Appending WORK._STATS_ to WORK.ALL_STATS.
NOTE: There were 0 observations read from the data set WORK._STATS_.
NOTE: 0 observations added.
NOTE: The data set WORK.ALL_STATS has 56937 observations and 9 variables.
NOTE: PROCEDURE APPEND used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
I'd really appreciate any ideas on how to fix these errors. Thank you.
How to Concatenate Values
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.
Click image to register for webinar
Classroom Training Available!
Select SAS Training centers are offering in-person courses. View upcoming courses for:
-
1317 views
-
0 likes
-
-
