SAS:how to count average interval time - sas

Question

how to count average interval time
+-------------+----------+----------+--------+------------------+
| customer_id | date | time | answer | missed_call_type |
+-------------+----------+----------+--------+------------------+
| 101 | 2018/8/3 | 12:13:00 | no | employee |
| 102 | 2018/8/3 | 12:15:00 | no | customer |
| 103 | 2018/8/3 | 12:20:00 | no | employee |
| 102 | 2018/8/3 | 15:15:00 | no | customer |
| 101 | 2018/8/3 | 18:15:00 | no | employee |
| 105 | 2018/8/3 | 18:18:00 | no | customer |
| 102 | 2018/8/3 | 19:18:00 | no | employee |
+-------------+----------+----------+--------+------------------+
I got a table which looks like this and wanted to calculate average interval time for those who did not answer the phone. For this example,the average interval time is:
[(18:15:00-12:13:00)+(19:18:00-15:15:00)+(15:15:00-12:15:00)]/3
it could work in mssql, and could create a colum interval_time for each customer then sum up. How to achive it in sas？data step or proc sql
CREATE TABLE customer_data (
customer_id BIGINT,
date DATE,
time time,
answer VARCHAR(100),
missed_call_type VARCHAR(100)
);
INSERT INTO customer_data
VALUES
(101, '2018/8/3', '12:13:00', 'no', 'employee'),
(102, '2018/8/3', '12:15:00', 'no', 'customer'),
(103, '2018/8/3', '12:20:00', 'no', 'employee'),
(102, '2018/8/3', '15:15:00', 'no', 'customer'),
(101, '2018/8/3', '18:15:00', 'no', 'employee'),
(105, '2018/8/3', '18:18:00', 'no', 'customer'),
(102, '2018/8/3', '19:18:00', 'no', 'employee')
select cd.customer_id, answer, missed_call_type,
CAST(CAST(cd.date as VARCHAR(10))+' ' +CAST(cd.time as VARCHAR(10)) as datetime) as date,
ROW_NUMBER() OVER(PARTITION BY cd.customer_id ORDER BY date desc, time desc) as ranks
INTO #temP
from customer_data cd
order by cd.customer_Id, ranks;
select AVG(DATEDIFF(MINUTE, x1.date, x2.date)) as avg_mins
from #temP x1
INNER JOIN #temP x2 ON x1.customer_id = x2.customer_id
WHERE x2.ranks = (x1.ranks-1)

Answer 1

A nested query can be used to prepare the data for the selection and computation you want. An important feature is to recognize that the datetime range (max-min) of a customer_id group is the same as adding up the sequential intervals of all the nos.
data have;
input customer_id date & yymmdd8. time & time8. answer $ missed_call_type $;
format date yymmdd10. time time8.;
datetime = dhms(date,hour(time), minute(time), second(time));
format datetime datetime20.;
datalines;
101 2018/8/3 12:13:00 no employee
102 2018/8/3 12:15:00 no customer
103 2018/8/3 12:20:00 no employee
102 2018/8/3 15:15:00 no customer
101 2018/8/3 18:15:00 no employee
105 2018/8/3 18:18:00 no customer
102 2018/8/3 19:18:00 no employee
run;
proc sql;
create table want as
select
sum(range) / sum (interval_count) as mean_interval_time format=time8.
, sum(range) as sum_range format=time8.
, sum(interval_count) as sum_interval_count
, count(range) as group_count
from
( select
max(datetime) - min(datetime) as range
, count(*) - 1 as interval_count
from have
group by customer_id
having count(*) > 1
);
You do not explain what should happen if the answer=yes, so the actual query may be more complicated than shown here.