SUM(case when TO_DATE(WO.W_MEASURE_CLAIMS_SAVING_DATE,'YYYY-MM-DD') between (sysdate -365) and sysdate then PM.M_GROSS_ANNUAL_KWH_SVG else 0 end) as CURRENT_KWH_12,
SUM(case when TO_DATE(WO.W_MEASURE_CLAIMS_SAVING_DATE,'YYYY-MM-DD') between sysdate -730 and (sysdate -365) then PM.M_GROSS_ANNUAL_KWH_SVG else 0 end) as PREVIOUS_LAST_KWH_12,
SUM(case when TO_DATE(WO.W_MEASURE_CLAIMS_SAVING_DATE,'YYYY-MM-DD') between (sysdate -365) and sysdate then PM.M_GROSS_ANNUAL_THERM_SVG else 0 end) as CURRENT_THERMS_12,
sum(case when TO_DATE(WO.W_MEASURE_CLAIMS_SAVING_DATE,'YYYY-MM-DD') between sysdate -730 and (sysdate -365) then PM.M_GROSS_ANNUAL_THERM_SVG else 0 end) as PREVIOUS_LAST_THERMS_12,
... i think the "current" data needs to be W_MEASURE_CLAIMS_SAVING_DATE >= 2022-01-01
and the [2:09 PM] Siegel, James R
and the "previous" data needs to be W_MEASURE_CLAIMS_SAVING_DATE between 2021-01-01 and today's date -365 days
but i just need help writing it
You appear to want to compare values between the start of this year until now to between the start of last year and the same date as now last year:
SUM(
CASE
WHEN WO.W_MEASURE_CLAIMS_SAVING_DATE BETWEEN TRUNC(SYSDATE, 'YY')
AND SYSDATE
THEN PM.M_GROSS_ANNUAL_KWH_SVG
END
) AS CURRENT_KWH,
SUM(
CASE
WHEN WO.W_MEASURE_CLAIMS_SAVING_DATE BETWEEN ADD_MONTHS(TRUNC(SYSDATE, 'YY'), -12)
AND ADD_MONTHS(SYSDATE, -12)
THEN PM.M_GROSS_ANNUAL_KWH_SVG
END
) as PREVIOUS_KWH
Related
The table I am working with is called 'transactions'. The columns are id (customer id), amount (amount spent by customer), timestamp (time of purchase).
I am trying to query:
yesterdays revenue: sum of amount.
percent difference from 8 day's ago revenue to yesterday's revenue.
MTD.
percent difference from last months MTD to this months MTD.
SAMPLE DATA
id
amount
timestamp
1
50
2021-12-01
2
60
2021-12-02
3
70
2021-11-05
4
80
2022-01-26
5
90
2022-01-25
6
20
2022-01-26
7
80
2022-01-19
EXPECTED OUTPUT
yesterday_revenue
pct_change_week_ago
mtd
pct_change_month_prior
100
0.25
270
0.50
This is my code. The percent change columns are both incorrect. Please help.
select
-- yesterday
sum(case when timestamp::date = current_date - 1 then amount else null end) yesterday_revenue,
-- yesterday v. last week
(sum(case when timestamp::date > current_date - 1 then amount else null end) - sum(case when timestamp::date = current_date - 8 then amount else null end))
/ sum(case when timestamp::date = current_date - 8 then amount else null end) pct_change_week_ago,
-- mtd
sum(case when date_trunc('month',timestamp) = date_trunc('month',CURRENT_DATE -1) then amount else null end) mtd,
-- mtd v. month prior
(sum(case when date_trunc('month',timestamp) = date_trunc('month',CURRENT_DATE -1) then amount else null end) - sum(case when date_trunc('month',timestamp) = date_trunc('month',CURRENT_DATE -1) - interval '1 month'
and date_part('day',timestamp ) <= date_part('day', CURRENT_DATE -1) then amount else null end))
/ sum(case when date_trunc('month',timestamp) = date_trunc('month',CURRENT_DATE -1) - interval '1 month'
and date_part('day',timestamp ) <= date_part('day', CURRENT_DATE -1) then amount else null end) pct_change_month_prior
from transactions
Some things to consider:
"yesterday vs last week" currently uses timestamp::date > current_date - 1 at the start. This will include transactions from today only, not yesterday (it says "greater than yesterday"). I think it should be timestamp::date = current_date - 1
I could be wrong here, but I think sum(case when date_trunc('month',timestamp) = date_trunc('month',CURRENT_DATE -1) will capture transactions on the current date as well if the current date is in the same month as yesterday. You may not want that.
As far as I can tell, 'pct_change_month_prior' should be 1.45, not 0.5. You have 110 in December and 270 in January. 270 - 110 = 160 and 160 / 110 = 1.45. Your existing query already returns that result. FWIW, you can also use new/old-1 to get the same result in a slightly simpler way.
OK, so really, it's about your maths in the SELECT part of your statement.
Amount changed is: new - old
As a multiplicative amount, it is (new - old) / old or new / old - 1
As a percentage, you need to multiply by 100... 100 * (new / old - 1) but I understand you aren't worried about this.
Further to this, let's make sure your new and old are correct.
Yesterday's sum:
sum(case when timestamp::date = CURRENT_DATE - 1 then amount else null end)
8 days ago sum:
sum(case when timestamp::date = CURRENT_DATE - 8 then amount else null end)
1 month to yesterday sum:
sum(case when timestamp::date > CURRENT_DATE - 1 - INTERVAL '1 month' AND timestamp::date <= CURRENT_DATE - 1 then amount else null end)
1 month to 1 month and 1 day ago sum:
sum(case when timestamp::date > CURRENT_DATE - 1 - INTERVAL '2 month' AND timestamp::date <= CURRENT_DATE - 1 - INTERVAL '1 month' then amount else null end)
Start of month to yesterday sum:
sum(case when timestamp::date > DATE_TRUNC('month', CURRENT_DATE - 1) AND timestamp::date <= CURRENT_DATE - 1 then amount else null end)
Start of yesterday's last month to a month ago yesterday sum:
sum(case when timestamp::date > DATE_TRUNC('month', CURRENT_DATE - 1 - INTERVAL '1 month') AND timestamp::date <= CURRENT_DATE - 1 - INTERVAL '1 month' then amount else null end)
It's important you don't change = to > or cropping to just the date part else you will include more than you really want.
Effectively, by cropping to the month part, it would almost always sum all transactions for two months.
I was doing a MODE.com SQL practice question about date format.
The practice question is: Write a query that counts the number of companies acquired within 3 years, 5 years, and 10 years of being founded (in 3 separate columns). Include a column for total companies acquired as well. Group by category and limit to only rows with a founding date.
It uses two tables:
tutorial.crunchbase_companies_clean_date table, which includes information about all the companies, like company name, founded year, etc.
tutorial.crunchbase_acquisitions_clean_datetable, which includes the information about all the acquired companies, like acquired company name, acquired date, etc.
My code is:
SELECT companies.category_code,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= '3 years' THEN 1 ELSE NULL END) AS less_than_3_years,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= '5 years' THEN 1 ELSE NULL END) AS between_3_to_5_years,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= '10 years' THEN 1 ELSE NULL END) AS within_10_years,
COUNT(1) AS total
FROM tutorial.crunchbase_companies_clean_date companies
JOIN tutorial.crunchbase_acquisitions_clean_date acq
ON companies.permalink = acq.company_permalink
WHERE companies.founded_at_clean IS NOT NULL
GROUP BY 1
ORDER BY total DESC
The result is:
My result
The answer query is:
SELECT companies.category_code,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + INTERVAL '3 years'
THEN 1 ELSE NULL END) AS acquired_3_yrs,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + INTERVAL '5 years'
THEN 1 ELSE NULL END) AS acquired_5_yrs,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + INTERVAL '10 years'
THEN 1 ELSE NULL END) AS acquired_10_yrs,
COUNT(1) AS total
FROM tutorial.crunchbase_companies_clean_date companies
JOIN tutorial.crunchbase_acquisitions_clean_date acquisitions
ON acquisitions.company_permalink = companies.permalink
WHERE founded_at_clean IS NOT NULL
GROUP BY 1
ORDER BY 5 DESC
The result is:
The answer result
You can see in the screenshots that the results are very similar, but some numbers are different.
The only difference I can see between my query and the answer is in the COUNT statements, but I don't really see the difference, for example, between: acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= '3 years' and acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + INTERVAL '3 years'
I tried adding INTERVAL in my SELECT statement:
SELECT companies.category_code,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= INTERVAL '3 years' THEN 1 ELSE NULL END) AS less_than_3_years,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= INTERVAL '5 years' THEN 1 ELSE NULL END) AS between_3_to_5_years,
COUNT(CASE WHEN acq.acquired_at_cleaned - companies.founded_at_clean:: timestamp <= INTERVAL '10 years' THEN 1 ELSE NULL END) AS within_10_years,
COUNT(1) AS total
and remove the INTERVAL from the answer query:
SELECT companies.category_code,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + '3 years'
THEN 1 ELSE NULL END) AS acquired_3_yrs,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + '5 years'
THEN 1 ELSE NULL END) AS acquired_5_yrs,
COUNT(CASE WHEN acquisitions.acquired_at_cleaned <= companies.founded_at_clean::timestamp + '10 years'
THEN 1 ELSE NULL END) AS acquired_10_yrs,
COUNT(1) AS total
But the results are the same.
I tried to know the result of just the difference between the acquired_date and founded_date, to see if the value can be compared with INTERVAL. The result is in days, which looks promising to me.
The result
I try to give all the information for your consideration. Hope somebody could help. Thank you in advance!
My suggestion is to add/subtract the INTERVAL to/from one date/time and then compare with the other date/time. Don't subtract the date/times and then compare to a string literal. Your database seems to understand '3 YEARS' as 3 * 365 days, regardless of the actual number of days between someDateTime and someDateTime +/- '3 YEARS'. The actual number of days from year to year could be 365 or 366, depending on whether a leap year is crossed.
Here's a simple example of comparing with a specific interval, which also requires we know whether and how many leap years were crossed.
Fiddle
The test case:
WITH dates AS (
SELECT '2021-01-01'::date AS xdate
)
SELECT xdate - (xdate - INTERVAL '1' YEAR) AS diff
, xdate - (xdate - INTERVAL '1' YEAR) = '1 YEAR' AS b1
, xdate - (xdate - INTERVAL '1' YEAR) = '365 DAYS' AS b2
, xdate - (xdate - INTERVAL '1' YEAR) = '366 DAYS' AS b3
FROM dates
;
-- AND --
WITH dates AS (
SELECT '2021-01-01'::date AS xdate
)
SELECT xdate - (xdate - INTERVAL '1' YEAR) AS diff
, xdate - (xdate - INTERVAL '1' YEAR) = INTERVAL '1' YEAR AS b1
, xdate - (xdate - INTERVAL '1' YEAR) = INTERVAL '365 DAYS' AS b2
, xdate - (xdate - INTERVAL '1' YEAR) = INTERVAL '366 DAYS' AS b3
FROM dates
;
Result:
diff
b1
b2
b3
366 days
f
f
t
Fiddle
WITH dates AS (
SELECT '2021-01-01'::date AS xdate
)
, diff AS (
SELECT xdate - (xdate - INTERVAL '1' YEAR) AS diff
FROM dates
)
SELECT diff
, CASE WHEN diff = (366*24*60*60 * INTERVAL '1' SECOND)
THEN 1
END AS compare1
, 366*24*60*60 AS seconds
, CASE WHEN diff = (366*24*60*60 * INTERVAL '1' SECOND)
THEN 1
END AS compare2
, CASE WHEN diff = '31622400 SECONDS'
THEN 1
END AS compare3
FROM diff
;
The result:
diff
compare1
seconds
compare2
compare3
366 days
1
31622400
1
1
Original response:
The fiddle for PostgreSQL
The behavior shown here (below) is similar to the posted behavior.
The problem is the value generated isn't necessarily what you think.
Here's a test case in postgresql which might be representative of your issue.
Maybe this is related to leap year, where the number of days in a year isn't constant.
So it's probably safer to compare the dates rather than assume some number of days, which is probably the assumption <= '3 years' makes.
The test SQL:
WITH test (acquired_at_cleaned, founded_at_clean, n) AS (
SELECT current_date, current_date - INTERVAL '4' YEAR, 4 UNION
SELECT current_date, current_date - INTERVAL '3' YEAR, 3 UNION
SELECT current_date, current_date - INTERVAL '2' YEAR, 2 UNION
SELECT current_date, current_date - INTERVAL '1' YEAR, 1
)
, cases AS (
SELECT test.*
, CASE WHEN acquired_at_cleaned <= founded_at_clean::timestamp + INTERVAL '3' year
THEN 1 ELSE NULL
END AS acquired_3_yrs_case1
, CASE WHEN acquired_at_cleaned - founded_at_clean::timestamp <= '3 year'
THEN 1 ELSE NULL
END AS acquired_3_yrs_case2
, acquired_at_cleaned - founded_at_clean::timestamp AS x1
, acquired_at_cleaned - (n * INTERVAL '1' YEAR) AS x2
FROM test
)
SELECT acquired_at_cleaned AS acquired
, founded_at_clean AS founded
, n
, acquired_3_yrs_case1 AS case1
, acquired_3_yrs_case2 AS case2
, x1, x2
FROM cases
ORDER BY founded_at_clean
;
The result:
acquired
founded
n
case1
case2
x1
x2
2021-12-25
2017-12-25 00:00:00
4
null
null
1461 days
2017-12-26 00:00:00
2021-12-25
2018-12-25 00:00:00
3
1
null
1096 days
2018-12-26 00:00:00
2021-12-25
2019-12-25 00:00:00
2
1
1
731 days
2019-12-26 00:00:00
2021-12-25
2020-12-25 00:00:00
1
1
1
365 days
2020-12-26 00:00:00
Interesting result.
I have a table like:
ID TIMEVALUE
----- -------------
1 06.07.15 06:43:01,000000000
2 06.07.15 12:17:01,000000000
3 06.07.15 18:21:01,000000000
4 06.07.15 23:56:01,000000000
5 07.07.15 04:11:01,000000000
6 07.07.15 10:47:01,000000000
7 07.07.15 12:32:01,000000000
8 07.07.15 14:47:01,000000000
and I want to group this data by special times.
My current query looks like this:
SELECT TO_CHAR(TIMEVALUE, 'YYYY\MM\DD'), COUNT(ID),
SUM(CASE WHEN TO_CHAR(TIMEVALUE, 'HH24MI') <=700 THEN 1 ELSE 0 END) as morning,
SUM(CASE WHEN TO_CHAR(TIMEVALUE, 'HH24MI') >700 AND TO_CHAR(TIMEVALUE, 'HH24MI') <1400 THEN 1 ELSE 0 END) as daytime,
SUM(CASE WHEN TO_CHAR(TIMEVALUE, 'HH24MI') >=1400 THEN 1 ELSE 0 END) as evening FROM Table
WHERE TIMEVALUE >= to_timestamp('05.07.2015','DD.MM.YYYY')
GROUP BY TO_CHAR(TIMEVALUE, 'YYYY\MM\DD')
and I am getting this output
day overall morning daytime evening
----- ---------
2015\07\05 454 0 0 454
2015\07\06 599 113 250 236
2015\07\07 404 139 265 0
so that is fine grouping on the same day (0-7 o'clock, 7-14 o'clock and 14-24 o'clock)
But my question now is:
How can I group over midnight?
For example count from 6-14 , 14-23 and 23-6 o'clock on next day.
I hope you understand my question. You are welcome to even improve my upper query if there is a better solution.
EDIT: It is tested now: SQL Fiddle
The key is simply to adjust the group by so that anything before 6am gets grouped with the previous day. After that, the counts are pretty straight-forward.
SELECT TO_CHAR(CASE WHEN EXTRACT(HOUR FROM timevalue) < 6
THEN timevalue - 1
ELSE timevalue
END, 'YYYY\MM\DD') AS day,
COUNT(*) AS overall,
SUM(CASE WHEN EXTRACT(HOUR FROM timevalue) >= 6 AND EXTRACT(HOUR FROM timevalue) < 14
THEN 1 ELSE 0 END) AS morning,
SUM(CASE WHEN EXTRACT(HOUR FROM timevalue) >= 14 AND EXTRACT(HOUR FROM timevalue) < 23
THEN 1 ELSE 0 END) AS daytime,
SUM(CASE WHEN EXTRACT(HOUR FROM timevalue) < 6 OR EXTRACT(HOUR FROM timevalue) >= 23
THEN 1 ELSE 0 END) AS evening
FROM my_table
WHERE timevalue >= TO_TIMESTAMP('05.07.2015','DD.MM.YYYY')
GROUP BY TO_CHAR(CASE WHEN EXTRACT(HOUR FROM timevalue) < 6
THEN timevalue - 1
ELSE timevalue
END, 'YYYY\MM\DD');
Substract 1 day from timevalue for times lower than '06:00' at first and then:
SQLFiddle demo
select TO_CHAR(day, 'YYYY\MM\DD') day, COUNT(ID) cnt,
SUM(case when '23' < tvh or tvh <= '06' THEN 1 ELSE 0 END) as midnight,
SUM(case when '06' < tvh and tvh <= '14' THEN 1 ELSE 0 END) as daytime,
SUM(case when '14' < tvh and tvh <= '23' THEN 1 ELSE 0 END) as evening
FROM (
select id, to_char(TIMEVALUE, 'HH24') tvh,
trunc(case when (to_char(timevalue, 'hh24') <= '06')
then timevalue - interval '1' day
else timevalue end) day
from t1
)
GROUP BY day
Maybe you can do it like this (with some reformatting or PIVOT):
WITH spans AS
(SELECT TIMESTAMP '2015-01-01 00:00:00' + LEVEL * INTERVAL '1' HOUR AS start_time
FROM dual
CONNECT BY TIMESTAMP '2015-01-01 00:00:00' + LEVEL * INTERVAL '1' HOUR < LOCALTIMESTAMP),
t AS
(SELECT start_time, lead(start_time, 1) OVER (ORDER BY start_time) AS end_time, ROWNUM AS N
FROM spans
WHERE EXTRACT(HOUR FROM start_time) IN (6,14,23))
SELECT N, start_time, end_time, COUNT(*) AS ID_COUNT,
DECODE(EXTRACT(HOUR FROM start_time), 6,'morning', 14,'daytime', 23,'evening') AS daytime
FROM t
JOIN YOUR_TABLE WHERE TIMEVALUE BETWEEN start_time AND end_time
GROUP BY N;
Of course, the initial time value ('2015-01-01 00:00:00' in my example) has to be lower than the least date in your table.
I am looking to see the number of firstexam patients seen per month for a given date range this year vs last year, and compare that to the total number of patients seen per month for the same date range.
I am able to set up the firstexam patients as follows:
select case EXTRACT(month FROM patient_info.firstexam)
when 1 then '01 - January'
when 2 then '02 - February'
when 3 then '03 - March'
when 4 then '04 - April'
when 5 then '05 - May'
when 6 then '06 - June'
when 7 then '07 - July'
when 8 then '08 - August'
when 9 then '09 - September'
when 10 then '10 - October'
when 11 then '11 - November'
when 12 then '12 - December'
end as month,
sum(case when patient_info.firstexam >= '2013-01-01' AND patient_info.firstexam <= '2013-12-31' then 1 else 0 end) thisyear,
sum(case when patient_info.firstexam >= '2012-01-01' AND patient_info.firstexam <= '2012-12-31' then 1 else 0 end) lastyear
from patient_info WHERE (patient_info.firstexam >= '2013-01-01' AND patient_info.firstexam <= '2013-12-31' OR patient_info.firstexam >= '2012-01-01' AND patient_info.firstexam <= '2012-12-31')
GROUP BY month
ORDER BY month
This gives me three columns: month, thisyear, lastyear.
Please note: I entered numerical month before month name because I could not get the months to appear in chronological order otherwise. Any hints to not show the number before the month would be appreciated.
I would like to add two more columns for total patients - something like:
select case EXTRACT(month FROM patient_info.lastexam)
when 1 then '01 - January'
when 2 then '02 - February'
when 3 then '03 - March'
when 4 then '04 - April'
when 5 then '05 - May'
when 6 then '06 - June'
when 7 then '07 - July'
when 8 then '08 - August'
when 9 then '09 - September'
when 10 then '10 - October'
when 11 then '11 - November'
when 12 then '12 - December'
end as month,
sum(case when patient_info.lastexam >= '2013-01-01' AND patient_info.lastexam <= '2013-12-31' then 1 else 0 end) totalthisyear,
sum(case when patient_info.lastexam >= '2012-01-01' AND patient_info.lastexam <= '2012-12-31' then 1 else 0 end) totallastyear
from patient_info WHERE (patient_info.lastexam >= '2013-01-01' AND patient_info.lastexam <= '2013-12-31' OR patient_info.lastexam >= '2012-01-01' AND patient_info.lastexam <= '2012-12-31')
GROUP BY month
ORDER BY month
with the results in 5 columns: month, thisyear, totalthisyear, lastyear, totallastyear
but can't seem to figure out exactly how this could be done. The order of the columns is not important.
It could be: month, thisyear, lastyear, totalthisyear, totallastyear
SQL Fiddle
select
to_char(('2012-' || m || '-01')::date, 'Month'),
thisyear, lastyear, totalthisyear, totallastyear
from (
select
extract(month from m) as m,
sum(case
when firstexam between '2013-01-01' and '2013-12-31' then firstexam_count
else 0 end
) as thisyear,
sum(case
when firstexam between '2012-01-01' and '2012-12-31' then firstexam_count
else 0 end
) as lastyear,
sum(case
when lastexam between '2013-01-01' and '2013-12-31' then lastexam_count
else 0 end
) as totalthisyear,
sum(case
when lastexam between '2012-01-01' and '2012-12-31' then lastexam_count
else 0 end
) as totallastyear
from
generate_series (
'2012-01-01'::date, '2013-12-31', '1 month'
) g(m)
left join (
select count(*) as firstexam_count, date_trunc('month', firstexam) as firstexam
from patient_info
where firstexam between '2012-01-01' and '2013-12-31'
group by 2
) pif on firstexam = m
left join (
select count(*) as lastexam_count, date_trunc('month', lastexam) as lastexam
from patient_info
where lastexam between '2012-01-01' and '2013-12-31'
group by 2
) pil on lastexam = m
group by 1
) s
order by m
I'm trying to return some results spread over a rolling 12 month period eg:
MONTH IN OUT
January 210 191
February 200 111
March 132 141
April 112 141
May 191 188
etc...
How do I spread the results over a date range, populating the first column with the month name?
IN MSSQL it would be something like:
SELECT COUNT(problem.problem_type = 'IN') AS IN,
COUNT(problem.problem_type = 'OUT') AS OUT,
DATEPART(year, DateTime) as Year,
DATEPART(month, DateTime) as Month
FROM problem
WHERE (DateTime >= dbo.FormatDateTime('2010-01-01'))
AND
(DateTime < dbo.FormatDateTime('2010-01-31'))
GROUP BY DATEPART(year, DateTime),
DATEPART(month, DateTime);
But this is against an Oracle database so DATEPART and DateTime are not available.
My Problem table is roughly:
problem_ID Problem_type IN_Date OUT_Date
1 IN 2010-01-23 16:34:29.0 2010-02-29 13:06:28.0
2 IN 2010-01-27 12:34:29.0 2010-01-29 12:01:28.0
3 OUT 2010-02-13 13:24:29.0 2010-09-29 15:04:28.0
4 OUT 2010-02-15 16:31:29.0 2010-07-29 11:03:28.0
Use:
SELECT SUM(CASE WHEN p.problem_type = 'IN' THEN 1 ELSE 0 END) AS IN,
SUM(CASE WHEN p.problem_type = 'OUT' THEN 1 ELSE 0 END) AS OUT,
TO_CHAR(datetime, 'YYYY') AS year,
TO_CHAR(datetime, 'MM') AS month
FROM PROBLEM p
WHERE p.DateTime >= TO_DATE('2010-01-01', 'YYYY-MM-DD')
AND p.DateTime < TO_DATE('2010-01-31', 'YYYY-MM-DD')
GROUP BY TO_CHAR(datetime, 'YYYY'), TO_CHAR(datetime, 'MM')
You could also use:
SELECT SUM(CASE WHEN p.problem_type = 'IN' THEN 1 ELSE 0 END) AS IN,
SUM(CASE WHEN p.problem_type = 'OUT' THEN 1 ELSE 0 END) AS OUT,
TO_CHAR(datetime, 'MM-YYYY') AS mon_year
FROM PROBLEM p
WHERE p.DateTime >= TO_DATE('2010-01-01', 'YYYY-MM-DD')
AND p.DateTime < TO_DATE('2010-01-31', 'YYYY-MM-DD')
GROUP BY TO_CHAR(datetime, 'MM-YYYY')
Reference:
TO_CHAR
TO_DATE
You probably want something like
SELECT SUM( (CASE WHEN problem_type = 'IN' THEN 1 ELSE 0 END) ) in,
SUM( (CASE WHEN problem_type = 'OUT' THEN 1 ELSE 0 END) ) out,
EXTRACT( year FROM DateTime ) year,
EXTRACT( month FROM DateTime ) month
FROM problem
WHERE DateTime >= date '2010-01-01'
AND DateTime < date '2010-01-31'
GROUP BY EXTRACT( year FROM DateTime ),
EXTRACT( month FROM DateTime )