I have a table that contains Following entries:
completed_time|| BOOK_CNT
*********************************************
2013-07-23 | 2
2013-07-22 | 1
2013-07-19 | 3
2013-07 16 |5
2013-07-12 |4
2013-07-11 |2
2013-07-02 |9
2013-06-30 |5
Now, I want to use above entries for data analysis.
Lets say DAYS_FROM, DAYS_TO and PERIOD are three variables.
I need to fire following sort of queries:
"Total book from DAYS_FROM to DAYS_TO in interval of PERIOD."
DAYS_FROM is a date in format YYYY-MM-DD
,DAYS_TO is a date in format YYYY-MM-DD
PERIOD is {1W,2W,1M,2M,1Y}
where W,M,Y represents WEEK,MONTH and YEAR.
Example: The queries DAYS_FROM=2013-07-23 , DAYS_TO=2013-07-03 and PERIOD=1W should return:
ith week - total
1 - 3
2- 8
3- 6
4- 14
Explanation:
1-3 means (The total book from 2013-07-21(sun) to 2013-07-23(tue) is 3 )
2-8 means (The total book from 2013-07-14(sun) to 2013-07-21(sun) is 8 )
3-16 means (The total book from 2013-07-07(sun) to 2013-07-14(sun) is 6 )
4-14 means (The total book from 2013-07-03(wed) to 2013-07-07(sun) is 14 )
Please refer the calendar image for better understanding.
How to fire such query?
What I tried?
SELECT DAY(completed_time), COUNT(total) AS Total
FROM my_tab
WHERE completed_time BETWEEN '2013-07-23' - INTERVAL 1 WEEK AND '2013-07-03'
GROUP BY DAY(completed_time);
The above queries subtracted 7 days from 2013-07-23 and thus considered 2013-07-16 to 2013-07-23 as first week, 2013-07-09 to 2013-07-16 as second week and so on.
A simple starting point would be something like below, of course you may want to adjust the ith value to suit your needs;
SET #period='1M';
SELECT CASE WHEN #period='1Y' THEN YEAR(completed_time)
WHEN #period='1M' THEN YEAR(completed_time)*100+MONTH(completed_time)
WHEN #period='2M' THEN FLOOR((YEAR(completed_time)*100+MONTH(completed_time))/2)*2
WHEN #period='1W' THEN YEARWEEK(completed_time)
WHEN #period='2W' THEN FLOOR(YEARWEEK(completed_time)/2)*2
END ith,
SUM(BOOK_CNT) Total
FROM my_tab
GROUP BY ith
ORDER BY ith DESC;
An SQLfiddle to test with.
Related
My requirement is to compute the total months and then broken months separately between 2 dates (ie first date from table and second date is current date). If broken months total count is > 15 then account it as one month experience and if its les than 15 don't account that as 1 month experience.
Assume I have a date on table as 25/11/2018 and current date is 06/01/2019;
the full month in between is December, so 1 month experience; and broken months are November and January, so now I have to count the dates which is 6 days in Nov and 6 days in Jan, so 12 days and is <= (lte) 15 so total experience will be rounded to 1 month experience
I referred multiple questions related to calculating date difference in MYSQL from stackoverflow, but couldn't find any possible options. The inbuilt functions in MYSQL TIMESTAMPDIFF, TIMEDIFF, PERIOD_DIFF, DATE_DIFF are not giving my required result as their alogrithms are different from my calculation requirement.
Any clue on how to perform this calculation in MYSQL and arrive its result as part of the SQL statement will be helpful to me. Once this value is arrived, in the same SQL, that value will be validated to be within a given value range.
Including sample table structure & value:
table_name = "user"
id | name | join_date
---------------------
1| Sam | 25-11-2017
2| Moe | 03-04-2017
3| Tim | 04-07-2018
4| Sal | 30-01-2017
5| Joe | 13-08-2018
I wanted to find out the users from above table whose experience is calculated in months based on the aforementioned logic. If those months are between either of following ranges, then those users are fetched for further processing.
table_name: "allowed_exp_range"
starting_exp_months | end_exp_months
-------------------------------------
0 | 6
9 | 24
For ex: Sam's experience till date (10-12-2018) based on my calculation is 12+1 month = 13 months. Since 13 is between 9 & 24, Sam's record is one of the expected output.
I think this query will do what you want. It uses
(YEAR(CURDATE())*12+MONTH(CURDATE()))
- (YEAR(STR_TO_DATE(join_date, '%d-%m-%Y'))*12+MONTH(STR_TO_DATE(join_date, '%d-%m-%Y'))) -
- 1
to get the number of whole months of experience for the user,
DAY(LAST_DAY(STR_TO_DATE(join_date, '%d-%m-%Y')))
- DAY(STR_TO_DATE(join_date, '%d-%m-%Y'))
+ 1
to get the number of days in the first month, and
DAY(CURDATE())
to get the number of days in the current month. The two day counts are summed and if the total is > 15, 1 is added to the number of whole months e.g.
SELECT id
, name
, (YEAR(CURDATE())*12+MONTH(CURDATE())) - (YEAR(STR_TO_DATE(join_date, '%d-%m-%Y'))*12+MONTH(STR_TO_DATE(join_date, '%d-%m-%Y'))) - 1 -- whole months
+ CASE WHEN DAY(LAST_DAY(STR_TO_DATE(join_date, '%d-%m-%Y'))) - DAY(STR_TO_DATE(join_date, '%d-%m-%Y')) + 1 + DAY(CURDATE()) > 15 THEN 1 ELSE 0 END -- broken month
AS months
FROM user
We can use this expression as a JOIN condition between user and allowed_exp_range to find all users who have experience within a given range:
SELECT u.id
, u.name
, a.starting_exp_months
, a.end_exp_months
FROM user u
JOIN allowed_exp_range a
ON (YEAR(CURDATE())*12+MONTH(CURDATE())) - (YEAR(STR_TO_DATE(u.join_date, '%d-%m-%Y'))*12+MONTH(STR_TO_DATE(u.join_date, '%d-%m-%Y'))) - 1
+ CASE WHEN DAY(LAST_DAY(STR_TO_DATE(u.join_date, '%d-%m-%Y'))) - DAY(STR_TO_DATE(u.join_date, '%d-%m-%Y')) + 1 + DAY(CURDATE()) > 15 THEN 1 ELSE 0 END
BETWEEN a.starting_exp_months AND a.end_exp_months
Output (for your sample data, includes all users as they all fit into one of the experience ranges):
id name starting_exp_months end_exp_months
1 Sam 9 24
2 Moe 9 24
3 Tim 0 6
4 Sal 9 24
5 Joe 0 6
I've created a small demo on dbfiddle which demonstrates the steps in arriving at the result.
We have a database for patients that shows the details of their various visits to our office, such as their weight during that visit. I want to generate a report that returns the visit (a row from the table) based on the difference between the date of that visit and the patient's first visit being the largest value possible but not exceeding X number of days.
That's confusing, so let me try an example. Let's say I have the following table called patient_visits:
visit_id | created | patient_id | weight
---------+---------------------+------------+-------
1 | 2006-08-08 09:00:05 | 10 | 180
2 | 2006-08-15 09:01:03 | 10 | 178
3 | 2006-08-22 09:05:43 | 10 | 177
4 | 2006-08-29 08:54:38 | 10 | 176
5 | 2006-09-05 08:57:41 | 10 | 174
6 | 2006-09-12 09:02:15 | 10 | 173
In my query, if I were wanting to run this report for "30 days", I would want to return the row where visit_id = 5, because it's 28 days into the future, and the next row is 35 days into the future, which is too much.
I've tried a variety of things, such as joining the table to itself, or creating a subquery in the WHERE clause to try to return the max value of created WHERE it is equal to or less than created + 30 days, but I seem to be at a loss at this point. As a last resort, I can just pull all of the data into a PHP array and build some logic there, but I'd really rather not.
The bigger picture is this: The database has about 5,000 patients, each with any number of office visits. I want to build the report to tell me what the average wait loss has been for all patients combined when going from their first visit to X days out (that is, X days from each individual patient's first visit, not an arbitrary X-day period). I'm hoping that if I can get the above resolved, I'll be able to work the rest out.
You can get the date of the first and next visit using query like this (Note that this doesn't has correct syntax for date comparing and it is just an schema of the query):
select
first_visits.patient_id,
first_visits.date first_date,
max(next_visit.created) next_date
from (
select patient_id, min(created) as "date"
from patient_visits
group by patient_id
) as first_visits
inner join patient_visits next_visit
on (next_visit.patient_id = first_visits.patient_id
and next_visit.created between first_visits.created and first_visits.created + 30 days)
group by first_visits.patient_id, first_visits.date
So basically you need to find start date using grouping by patient_id and then join patient_visits and find max date that is within the 30 days window.
Then you can join the result to patient_visits to get start and end weights and calculate the loss.
I have a table like this
id plan_id cancel_date paid_date
9 2 2015-08-05 2014-09-13
10 2 2015-09-08 2015-09-03
10 3 NULL 2015-09-10
11 3 NULL 2015-09-13
14 3 2015-09-28 2015-09-14
And I would like to select ids where there is a less than 30 days difference between cancel_date and paid_date (for a given plan), and they didn't acquired a new plan in less than 30 days.
In this case, this would mean returning id 14 only.
Update:
Whenever a user buy a new plan, we insert it to the table, with a different paid_date (paid_date is the date that the plan was acquired the first time).
The final result of this will be used for a graphing application where sometimes we would not want the detailed granularity of data at the level it is stored in the table. This may be hard to phrase in a single question so I will give an example:
Example table:
DateTime AddressID Amount
1/1/2015 10:00:00 1 10
1/1/2015 10:00:00 2 8
1/1/2015 10:01:00 1 7
1/1/2015 10:01:00 2 12
1/1/2015 10:02:00 1 21
1/1/2015 10:02:00 2 15
etc...
Note: The times will always have 00 for the seconds - if that helps.
Note: The entries may NOT always have an entry for every minute, but they generally should. So it is possible some might times might be skipped. But there will always be an entry for both addressIDs (1 & 2) every time without fail.
I need to return the above 3 fields, in a period of time requested (for example past 24 hours), but only for certain increments of time FOR EACH OF THE ADDRESS ID's. For example, records for every 5 minutes, or every 10 minutes.
so in the case of 5 minutes it would return:
DateTime AddressID Amount
1/1/2015 10:**00**:00 1 10
1/1/2015 10:**00**:00 2 8
1/1/2015 10:**05**:00 1 11
1/1/2015 10:**05**:00 2 17
1/1/2015 10:**10**:00 1 28
1/1/2015 10:**10**:00 2 5
etc...
Performance is very important. I hope I explained that well enough for someone to get the idea of what I need and I thank you in advance for your suggestions.
EDIT: For clarification, the 5 minutes in the above example should be the minimum time BETWEEN each row. So, if in the above example, on the rare chance that there was a missing time entry for 10:05:00 it should not simply select the 10:10:00 row, it should select the 10:06:00 record and then the next row selected would be 10:11:00, etc.
EDIT: The original post follows, but its a bit long and wordy. This edit presents a simplified question.
I'm trying to SUM 1 column multiple times; from what I've found, my options are either CASE or (SELECT). I am trying to SUM based on a date range and I can't figure out if CASE allows that.
table.number | table.date
2 2014/12/18
2 2014/12/19
3 2015/01/11
3 2015/01/12
7 2015/02/04
7 2015/02/05
As separate queries, it would look like this:
SELECT SUM(number) as alpha FROM table WHERE date >= 2014/12/01 AND date<= DATE_ADD (2014/12/01, INTERVAL 4 WEEKS)
SELECT SUM(number) as beta FROM table WHERE date >= 2014/12/29 AND date<= DATE_ADD (2014/12/01, INTERVAL 4 WEEKS)
SELECT SUM(number) as gamma FROM table WHERE date >= 2014/01/19 AND date<= DATE_ADD (2014/12/01, INTERVAL 4 WEEKS)
Looking for result set
alpha | beta | gamma
2 6 14
ORIGINAL:
I'm trying to return SUM of payments that will be due within my budgeting time frame (4 weeks) for the current budgeting period and 2 future periods. Some students pay every 4 weeks, others every 12. Here are the relevant fields in my tables:
client.name | client.ppid | client.last_payment
john | 1 | 12/01/14
jack | 2 | 11/26/14
jane | 3 | 10/27/14
pay_profile.id | pay_profile.price | pay_profile.interval (in weeks)
1 140 4
2 399 4
3 1 12
pay_history.name | pay_history.date | pay_history.amount
john | 12/02/14 | 140
jerry | more historical | data
budget.period_start |
12/01/14
I think the most efficient way of doing this is:
1.)SUM all students who pay every 4 weeks as base_pay
2.)SUM all students who pay every 12 weeks and whose DATEADD(client.last_payment, INTERVAL pay_profile.interval WEEKS) is >= budget.period_start and <= DATEADD(budget.period_start, INTERVAL 28 DAYS) as accounts_receivable
3.) As the above step will miss people who've already paid in this budgeting period (as this updates their last_payment dating, putting them out of the range specified in #2), I'll also need to SUM pay_history.date for the range above as well. paid_in_full
4.) repeat step 2 above, adjusting the range and column name for future periods (i.e. accounts_receivable_2
5.) use php to SUM base_pay, accounts_receivable, and pay_history, repeating the process for future periods.
I'm guessing the easiest way would be to use CASE, which I've not done before. Here was my best guess, which fails due to a sytax error. I assuming I can use DATE_ADD in the WHEN statement.
SELECT
CASE
DATE_ADD(client.last_payment, INTERVAL pay_profile.interval WEEK) >= budget.period_start
AND
DATE_ADD(client.last_payment, INTERVAL pay_profile.interval WEEK) <=
DATE_ADD(budget.period_start,INTERVAL 28 DAY) THEN SUM(pay_profile.price) as base_pay
FROM client
LEFT OUTER JOIN pay_profile ON client.ppid = pay_profile.ppid
LEFT OUTER JOIN budget ON client.active = 1
WHERE
client.active = 1
Thanks.