I'm trying to calculate the frequency of fractions in my data set (excluding whole numbers).
For example, my variable P takes values 24+1/2, 97+3/8, 12+1/4, 57+1/2, etc. and I'm looking to find the frequency of 1/2, 3/8, and so on. Can anyone help?!
Thanks in advance!
Clyde013
Clyde013, here is one way, assuming that p is of character type. hth. cheers, chang
> Pulled from SAS-L
/* test data -- if p is a character var */
data one;
input p $ ##;
cards;
24+1/2
97+3/8
12+1/4
57+1/2
36 3/8 ;
run;
/* frequencies of frations? */
data two;
set one;
whole = scan(p, 1, "+");
frac = scan(p, 2, "+");
run;
proc freq data=two;
tables frac;
run;
/* on lst
Cumulative Cumulative
frac Frequency Percent Frequency Percent
---------------------------------------------------------
1/2 2 50.00 2 50.00
1/4 1 25.00 3 75.00
3/8 1 25.00 4 100.00
Frequency Missing = 2 */
Related
I want to check p-value in chi-Square test, and this is my code in SAS.
data dataA;
input Ball $ observed;
datalines;
A 1
B 0
C 0
D 0
E 9
;
run;
proc freq data=dataA;
tables Ball / chisq;
weight observed;
run;
Here is a problem. This Chi-square test did not include when value is 0. Actually, DF is 4, but now it's 1.
The below calculation is what I want (Chi-square should be 31), including 0 values.
How can I include the category with 0 value so that DF becomes 4, not 1? and Chi-squared becomes 31, not 6.4?
Thanks!!
You need to use ZEROS option on the WEIGHT statement.
proc freq data=dataA;
tables Ball / chisq;
weight observed / zeros;
run;
I need to create a variable that takes the product of the values of all prior values and including the one in the current obs.
data temp;
input time cond_prob;
datalines;
1 1
2 0.2
3 0.3
4 0.4
5 0.6
;
run;
Final data should be:
1 1
2 0.2 (1*0.2)
3 0.06 (0.2* 0.3)
4 0.024 (0.06 * 0.4
5 0.0144 (0.024 *0.6)
This seems like a simple code but I can't get it to work. I can do cumulative sums but cumulative product is not working when using the same logic.
Use the RETAIN functionality.
For the first record I set it to a value of 1 because anything multiplied by 1 will stay the same.
data want;
set temp;
retain cum_product 1;
cum_product = cond_prob * cum_product;
run;
I have 70 databases of different sizes (same number of columns, different numbers of lines).
I need to get the 25% higher values and the 25% lower values considering a given column VAR1.
I have:
id VAR1
1 10
2 -5
3 -12
4 7
5 12
6 7
7 -9
8 -24
9 0
10 6
11 -18
12 22
Sorting by VAR1, I need to select the rows (all columns) containing the 3 smallest and the 3 largest (25% from each extreme), i.e.,
id VAR1
8 -24
11 -18
3 -12
7 -9
2 -5
9 0
10 6
4 7
6 7
1 10
5 12
12 22
I need to keep in the database the rows (all columns) that contain the VAR1 equal to -24, -18, -12, 10, 12 and 22.
id VAR1
8 -24
11 -18
3 -12
1 10
5 12
12 22
What I’ve been thinking:
Order column VAR1 in ascending order;
Create a numbered column from 1 to N (n=_N_) - in this case, N=12;
I do a=N*0.25 (to have the value that represents 25%);
I do b=N-a (to have the value that represents the "last" 25%).
So, I can use keep:
if N<a.... I will have the first 25% (the smallest).
if N>b.... I will have the last 25% (the largest).
I can calculate a and b.
But I’m not getting the maximum value of N in this case 12.
I will repeat this for the 70 database, I would not like to have to enter this maximum value every time (it varies from one database to another).
I need help to "fix" the maximum value (N) without having to type it (even if it is repeated in all the lines of another "auxiliary column").
Or if there’s some better way to get those 25% from each end.
My code:
proc sort data=have; by VAR1; run;
data want; set have;
seq=_N_;
N=max(seq); *N=max. value of lines. (I stopped here and don’t know if below is right);
a=N*0.25;
b=N-b;
if N<a;
if N>b;
run;
Thank you very much!
Proc RANK computes percentiles that you can use to select the desired rows.
Example:
data have1 have2 have3 have4 have5;
do id = 1 to 100;
X = ceil(rand('normal', 0, 10));
if id < 60 then output have1;
if id < 70 then output have2;
if id < 80 then output have3;
if id < 90 then output have4;
if id < 100 then output have5;
end;
run;
proc rank data=have1 percent out=want1(where=(pct not between 25 and 75)) ;
var x;
ranks pct;
run;
proc rank data=have2 percent out=want2(where=(pct not between 25 and 75)) ;
var x;
ranks pct;
run;
proc rank data=have3 percent out=want3(where=(pct not between 25 and 75)) ;
var x;
ranks pct;
run;
Say that I have the following database:
Min Rank Qty
2 1 100
2 2 90
2 3 80
2 4 70
5 1 110
5 2 100
5 3 90
5 4 80
5 5 70
7 1 120
7 2 110
7 3 100
7 4 90
I need to have the database with the continuous values for minutes like this:
Min Rank Qty
2 1 100
2 2 90
2 3 80
2 4 70
3 1 100
3 2 90
3 3 80
3 4 70
4 1 100
4 2 90
4 3 80
4 4 70
5 1 110
5 2 100
5 3 90
5 4 80
5 5 70
6 1 110
6 2 100
6 3 90
6 4 80
6 5 70
7 1 120
7 2 110
7 3 100
7 4 90
How can I do this in SAS? I just need to replicate the previous minute. The number of observations per minute varies...it can be 4 or 5 or more.
It is not that hard to imagine code that would do this, the problem is that it quickly starts to look messy.
If your dataset is not too large, one approach you could consider the following approach:
/* We find all gaps. the output dataset is a mapping: the data of which minute (reference_minute) do we need to create each minute of data*/
data MINUTE_MAPPING (keep=current_minute reference_minute);
set YOUR_DATA;
by min;
retain last_minute 2; *set to the first minute you have;
if _N_ NE 1 and first.min then do;
/* Find gaps, map them to the last minute of data we have*/
if last_minute+1 < min then do;
do current_minute=last_minute+1 to min-1;
reference_minute=last_minute;
output;
end;
end;
/* For the available data, we map the minute to itself*/
reference_minute=min;
current_minute=min;
output;
*update;
last_minute=min;
end;
run;
/* Now we apply our mapping to the data */
*you must use proc sql because it is a many-to-many join, data step merge would give a different outcome;
proc sql;
create table RESULT as
select YD.current_minute as min, YD.rank, YD.qty
MINUTE_MAPPING as MM
join YOUR_DATA as YD
on (MM.reference_minute=YD.min)
;
quit;
The more performant approach would involve trickery with arrays.
But i find this approach a bit more appealing (disclaimer: at first thought), it is quicker to grasp (disclaimer again: imho) for someone else afterwards.
For good measure, the array approach:
data RESULT (keep=min rank qty);
set YOUR_DATA;
by min;
retain last_minute; *assume that first record really is first minute;
array last_data{5} _TEMPORARY_;
if _N_ NE 1 and first.min and last_minute+1 < min then do; *gap found;
do current_min=last_minute+1 to min-1;
*store data of current record;
curr_min=min;
curr_rank=rank;
curr_qty=qty;
*produce records from array with last available data;
do iter=1 to 5;
min = current_minute;
rank = iter;
qty = last_data{iter};
if qty NE . then output; *to prevent output of 5th element where there are only 4;
end;
*put back values of actual current record before proceeding;
min=curr_min;
rank=curr_rank;
qty=curr_qty;
end;
*update;
last_minute=min;
end;
*insert data for use on later missing minutes;
last_data{rank}=qty;
if last.min and rank<5 then last_data{5}=.;
output; *output actual current data point;
run;
Hope it helps.
Note, currently no access to a SAS client where i am. So untested code, might contain a couple of typo's.
Unless you have an absurd number of observations, I think transposing would make this easy.
I don't have access to sas at the moment so bear with me (I can test it out tomorrow if you can't get it working).
proc transpose data=data out=data_wide prefix=obs_;
by minute;
id rank;
var qty;
run;
*sort backwards so you can use lag() to fill in the next minute;
proc sort data=data_wide;
by descending minute;
run;
data data_wide; set data_wide;
nextminute = lag(minute);
run;
proc sort data=data_wide;
by minute;
run;
*output until you get to the next minute;
data data_wide; set data_wide;
*ensure that the last observation is output;
if nextminute = . then output;
do until (minute ge nextminute);
output;
minute+1;
end;
run;
*then you probably want to reverse the transpose;
proc transpose data=data_wide(drop=nextminute)
out=data_narrow(rename=(col1=qty));
by minute;
var _numeric_;
run;
*clean up the observation number;
data data_narrow(drop=_NAME_); set data_narrow;
rank = substr(_NAME_,5)*1;
run;
Again, I can't test this now, but it should work.
Someone else may have a clever solution that makes it so you don't have to reverse-sort/lag/forward-sort. I feel like I have dealt with this before but the obvious solution for me right now is to have it sorted backwards at whatever prior sort you do (you can do the transpose with a descending sort no problem) to save you an extra sort.
How can we do iteration in a sas dataset.
For example I have chosen the first. of a variable.
And want to find the occurence of a particular condition and set a value when it satisfy
SAS data step has a built-in loop over observations. You don't have to do any thing, unless you want to, for some reason. For instance, the following generates a random number for each observation:
data one;
set sashelp.class;
rannum = ranuni(0);
run;
If you want to loop over variables, then there are arrays. For example, the following initializes variables, var1 to var10, with random numbers:
data one;
array vars[1:10] var1-var10;
do i = 1 to 10;
vars[i] = ranuni(0);
end;
run;
The first. and last. flags are automatically generated when you set a (sorted) data with a by statement. An example:
proc sort data=sashelp.class out=class;
by age;
run;
data one;
set class;
by age;
first = first.age;
last = last.age;
run;
/* check */
proc print data=one;
run;
/* on lst
Obs Name Age first last
1 Joyce 11 1 0
2 Thomas 11 0 1
3 James 12 1 0
4 Jane 12 0 0
5 John 12 0 0
6 Louise 12 0 0
7 Robert 12 0 1
8 Alice 13 1 0
...
18 William 15 0 1
19 Philip 16 1 1
*/