I have an employee table with the following fields
employee(id, name, joiningDate, salary, dept)
I would like to retrieve count of all the employees who joined the company in past 1day, 2days, 3days and 4days in each department. Please see the result I need in the below link.
Sample result:
If you want it in the past 24 hours, between 24 and 48 hours, etc...
SELECT dept,
COUNT( CASE WHEN joiningDate BETWEEN SYSDATE - 1 AND SYSDATE THEN 1 ELSE NULL END ) AS day1,
COUNT( CASE WHEN joiningDate BETWEEN SYSDATE - 2 AND SYSDATE - 1 THEN 1 ELSE NULL END ) AS day2,
COUNT( CASE WHEN joiningDate BETWEEN SYSDATE - 3 AND SYSDATE - 2 THEN 1 ELSE NULL END ) AS day3,
COUNT( CASE WHEN joiningDate BETWEEN SYSDATE - 4 AND SYSDATE - 3 THEN 1 ELSE NULL END ) AS day4,
COUNT( CASE WHEN joiningDate BETWEEN SYSDATE - 5 AND SYSDATE - 4 THEN 1 ELSE NULL END ) AS day5
FROM Employee
GROUP BY dept;
If you want it yesterday, 2 days ago, 3 days ago, etc then wrap TRUNC() around each instance of SYSDATE.
If we have pivot tag then why not use pivot?
select * from (
select dept, trunc(sysdate)-trunc(joiningDate) dt
from employee where joiningDate >= trunc(sysdate)-5)
pivot (count(1) for dt in (1 day1, 2 day2, 3 day3, 4 day4, 5 day5))
order by dept
SQLFiddle demo
The following should get you what you're looking for:
SELECT DEPT,
SUM(CASE WHEN TRUNC(SYSDATE) - TRUNC(JOININGDATE) = 1 THEN 1 ELSE 0 END) AS day1,
SUM(CASE WHEN TRUNC(SYSDATE) - TRUNC(JOININGDATE) = 2 THEN 1 ELSE 0 END) AS day2,
SUM(CASE WHEN TRUNC(SYSDATE) - TRUNC(JOININGDATE) = 3 THEN 1 ELSE 0 END) AS day3,
SUM(CASE WHEN TRUNC(SYSDATE) - TRUNC(JOININGDATE) = 4 THEN 1 ELSE 0 END) AS day4,
SUM(CASE WHEN TRUNC(SYSDATE) - TRUNC(JOININGDATE) = 5 THEN 1 ELSE 0 END) AS day5
FROM EMPLOYEE
GROUP BY DEPT
ORDER BY DEPT;
SQLFiddle here
Related
certainly something very simple, but for an application I would like to know how, if I know the calendar week, I can display the first to the last day of the week per row.
Currently, I am only shown the day in which content is present.
I would like to have 7 days displayed (as date, not necessarily with name) whether they are empty or not.
SELECT
MIN( TO_CHAR(LP_BELEGUNG.GEN_DATUM,'DD.MM.YYYY')) AS GRD_ROW_ID
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 1 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_1
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 2 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_2
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 3 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_3
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 99 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_4
FROM
LP_BELEGUNG
WHERE
TO_CHAR(LP_BELEGUNG.GEN_DATUM, 'WW') = 37 --the calendar week
If you want one row per day, for a week number in a given year, then you can generate all the dates in that week and use an outer join to look for matching rows in your table, if there are any.
Unfortunately Oracle doesn't supply a simple way to get a date from a week number, but based on how the WW element is defined you can start from the first day of the year and add the appropriate number of days to get the start of the week:
select trunc(sysdate, 'YYYY') + (7 * 37) - 7 from dual;
TRUNC(SYSDATE,'YYYY')+(7*37)-7
10-SEP-22
... where 37 is the week number, and I've assumed you're looking at the current year (if not, use a fixed date like date '2022-01-01' instead of trunc(sysdate)).
You can then get all the days in that week with a hierarchical query:
select trunc(sysdate, 'YYYY') + (7 * 37) + level - 8
from dual
connect by level <= 7;
TRUNC(SYSDATE,'YYYY')+(7*37)+LEVEL-8
10-SEP-22
11-SEP-22
12-SEP-22
13-SEP-22
14-SEP-22
15-SEP-22
16-SEP-22
Then use those values in an inline view or CTE, and left-join to your table using a date range (to allow for non-midnight times but still allowing an index on that column to be used), grouping by the date:
with cte (dt) as (
select trunc(sysdate, 'YYYY') + (7 * 37) + level - 8
from dual
connect by level <= 7
)
SELECT
TO_CHAR(cte.dt, 'DD.MM.YYYY') AS GRD_ROW_ID
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 1 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_1
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 2 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_2
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 3 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_3
, COUNT( DISTINCT
CASE
WHEN LP_BELEGUNG.ART = 99 THEN LP_BELEGUNG.LP_BELEGUNG_ID
ELSE NULL
END ) AS ANZAHL_ART_4
FROM
cte
LEFT JOIN
LP_BELEGUNG
ON
LP_BELEGUNG.GEN_DATUM >= cte.dt AND LP_BELEGUNG.GEN_DATUM < cte.dt + 1
GROUP BY
cte.dt
ORDER BY
cte.dt
With some sample data to mimic your original result, that gives:
GRD_ROW_ID
ANZAHL_ART_1
ANZAHL_ART_2
ANZAHL_ART_3
ANZAHL_ART_4
10.09.2022
0
0
0
0
11.09.2022
0
0
0
0
12.09.2022
0
0
0
0
13.09.2022
0
0
0
0
14.09.2022
0
0
0
0
15.09.2022
0
0
0
0
16.09.2022
1
0
0
7
fiddle
Here is a set of dates counted and divided to days of the week using to_char and pivot.
select *
from
(
select dt
,to_char(dt, 'D') as dow
from t
) t
pivot (count(dt) for dow in('1', '2', '3', '4', '5', '6', '7')) p
'1'
'2'
'3'
'4'
'5'
'6'
'7'
1
1
0
0
1
3
1
Fiddle
Use conditional aggregation:
SELECT TO_CHAR(MIN(GEN_DATUM),'DD.MM.YYYY') AS GRD_ROW_ID,
COUNT( DISTINCT
CASE
WHEN ART = 1
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 0
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_1_DAY1,
COUNT( DISTINCT
CASE
WHEN ART = 1
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 1
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_1_DAY2,
-- ...
COUNT( DISTINCT
CASE
WHEN ART = 1
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 6
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_1_DAY7,
COUNT( DISTINCT
CASE
WHEN ART = 2
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 0
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_2_DAY1,
COUNT( DISTINCT
CASE
WHEN ART = 2
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 1
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_2_DAY2,
-- ...
COUNT( DISTINCT
CASE
WHEN ART = 2
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 6
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_2_DAY7,
COUNT( DISTINCT
CASE
WHEN ART = 3
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 0
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_3_DAY1,
COUNT( DISTINCT
CASE
WHEN ART = 3
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 1
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_3_DAY2,
-- ...
COUNT( DISTINCT
CASE
WHEN ART = 3
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 6
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_3_DAY7,
COUNT( DISTINCT
CASE
WHEN ART = 99
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 0
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_4_DAY1,
COUNT( DISTINCT
CASE
WHEN ART = 99
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 1
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_4_DAY2,
-- ...
COUNT( DISTINCT
CASE
WHEN ART = 99
AND TRUNC(gen_datum) - TRUNC(gen_datum, 'WW') = 6
THEN LP_BELEGUNG_ID
END
) AS ANZAHL_ART_4_DAY7
FROM LP_BELEGUNG
WHERE TO_CHAR(GEN_DATUM, 'WW') = 37
I'm trying to create a cohort query using SQL.
Usually with cohort analysis we look at users and check if a user who performed a specific action at a specific time and count if that user performs the same action over time.
WITH by_week
AS (SELECT
user_id,
TD_DATE_TRUNC('week', login_time) AS login_week
FROM logins
GROUP BY 1, 2),
with_first_week
AS (SELECT
user_id,
login_week,
FIRST_VALUE(login_week) OVER (PARTITION BY user_id ORDER BY login_week) AS first_week
FROM by_week),
with_week_number
AS (SELECT
user_id,
login_week,
first_week,
(login_week - first_week) / (24 * 60 * 60 * 7) AS week_number
FROM with_first_week)
SELECT
TD_TIME_FORMAT(first_week, 'yyyy-MM-dd') AS first_week,
SUM(CASE WHEN week_number = 1 THEN 1 ELSE 0 END) AS week_1,
SUM(CASE WHEN week_number = 2 THEN 1 ELSE 0 END) AS week_2,
SUM(CASE WHEN week_number = 3 THEN 1 ELSE 0 END) AS week_3,
SUM(CASE WHEN week_number = 4 THEN 1 ELSE 0 END) AS week_4,
SUM(CASE WHEN week_number = 5 THEN 1 ELSE 0 END) AS week_5,
SUM(CASE WHEN week_number = 6 THEN 1 ELSE 0 END) AS week_6,
SUM(CASE WHEN week_number = 7 THEN 1 ELSE 0 END) AS week_7,
SUM(CASE WHEN week_number = 8 THEN 1 ELSE 0 END) AS week_8,
SUM(CASE WHEN week_number = 9 THEN 1 ELSE 0 END) AS week_9
FROM with_week_number
GROUP BY 1
ORDER BY 1
But let say now I don't care that much about first time/user-level analysis and I only want to see if my login action increases over time (i.e I want to add up logins of the first cohort during week 2 with logins of the second cohort in week 1). Is there a simple/elegant way to do this?
Edit:
Giving an example below
WeekStart Week1 Week2 Week 3
2017/05/03 66 **53** **49**
2017/05/10 (**53**+74) (**49**+70) **65**
2017/05/17 (**49**+ 70 + 45) (**65** + 80) etc.
I think you need to group by login_week instead of first_week so you count all logins during the given week in every row, not by cohort, and then you have to use >= instead of = so it will sum up this week's cohort with all older cohorts in any given row.
WITH
by_week AS (
SELECT
user_id,
TD_DATE_TRUNC('week', login_time) AS login_week
FROM logins
GROUP BY 1, 2
)
,with_first_week AS (
SELECT
user_id,
login_week,
FIRST_VALUE(login_week) OVER (PARTITION BY user_id ORDER BY login_week) AS first_week
FROM by_week
)
,with_week_number AS (
SELECT
user_id,
login_week,
first_week,
(login_week - first_week) / (24 * 60 * 60 * 7) AS week_number
FROM with_first_week
)
SELECT
TD_TIME_FORMAT(login_week, 'yyyy-MM-dd') AS login_week,
SUM(CASE WHEN week_number>= 1 THEN 1 ELSE 0 END) AS week_1,
SUM(CASE WHEN week_number>= 2 THEN 1 ELSE 0 END) AS week_2,
SUM(CASE WHEN week_number>= 3 THEN 1 ELSE 0 END) AS week_3,
SUM(CASE WHEN week_number>= 4 THEN 1 ELSE 0 END) AS week_4,
SUM(CASE WHEN week_number>= 5 THEN 1 ELSE 0 END) AS week_5,
SUM(CASE WHEN week_number>= 6 THEN 1 ELSE 0 END) AS week_6,
SUM(CASE WHEN week_number>= 7 THEN 1 ELSE 0 END) AS week_7,
SUM(CASE WHEN week_number>= 8 THEN 1 ELSE 0 END) AS week_8,
SUM(CASE WHEN week_number>= 9 THEN 1 ELSE 0 END) AS week_9
FROM with_week_number
GROUP BY 1
ORDER BY 1;
I want to get statistics with sql query. My table is like this:
ID MATERIAL CREATEDATE DEPARTMENT
1 M1 10.10.1980 D1
2 M2 11.02.1970 D2
2 M3 18.04.1971 D3
.....................
.....................
.....................
How can I get a range of data count like this
DEPARTMENT AGE<10 10<AGE<20 20<AGE
D1 24 123 324
D2 24 123 324
Assuming that CREATEDATE is a date column, in PostgreSQL you can use the AGE function:
select DEPARTMENT, age(CREATEDATE) as AGE
from Materials
and with date_part you can get the age in years. To show the data in the format that you want, you could use this GROUP BY query:
select
DEPARTMENT,
sum(case when date_part('year', age(CREATEDATE))<10 then 1 end) as "age<10",
sum(case when date_part('year', age(CREATEDATE))>=10 and date_part('year', age(CREATEDATE))<20 then 1 end) as "10<age<20",
sum(case when date_part('year', age(CREATEDATE))>=20 then 1 end) as "20<age"
from
Materials
group by
DEPARTMENT
which can be simplified as:
with mat_age as (
select DEPARTMENT, date_part('year', age(CREATEDATE)) as mage
from Materials
)
select
DEPARTMENT,
sum(case when mage<10 then 1 end) as "age<10",
sum(case when mage>=10 and mage<20 then 1 end) as "10<age<20",
sum(case when mage>=20 then 1 end) as "20<age"
from
mat_age
group by
DEPARTMENT;
if you are using PostgreSQL 9.4 you can use FILTER:
with mat_age as (
select DEPARTMENT, date_part('year', age(CREATEDATE)) as mage
from Materials
)
select
DEPARTMENT,
count(*) filter (where mage<10) as "age<10",
count(*) filter (where mage>=10 and mage<20) as "10<age<20",
count(*) filter (where mage>=20) as "20<age"
from
mat_age
group by
DEPARTMENT;
The following solution assumes that your CREATEDATE column exists as some sort of valid Postgres date type. If this be not the case, and it is being stored as text, you will first have to convert it to date in order for the query to work.
SELECT DEPARTMENT,
SUM(CASE WHEN DATEDIFF(year, CREATEDATE, now()::date) < 10 THEN 1 ELSE 0 END) AS "AGE<10",
SUM(CASE WHEN DATEDIFF(year, CREATEDATE, now()::date) >= 10 AND
DATEDIFF(year, CREATEDATE, now()::date) < 20 THEN 1 ELSE 0 END) AS "10<AGE<20",
SUM(CASE WHEN DATEDIFF(year, CREATEDATE, now()::date) >= 20 THEN 1 ELSE 0 END) AS "20<AGE"
FROM Materials
GROUP BY DEPARTMENT
You can use extract(year FROM age(createdate)) to get the exact age
i.e
select extract(year FROM age(timestamp '01-01-1989')) age
will give you
Result:
age
---
27
so you can use following select statement to get your desired output:
SELECT dept
,sum(CASE WHEN age < 10THEN 1 END) "age<10"
,sum(CASE WHEN age >= 10 AND age < 20 THEN 1 END) "10<age<20"
,sum(CASE WHEN age >= 20 THEN 1 END) "20<age"
FROM (
SELECT dept,extract(year FROM age(crdate)) age
FROM dt
) t
GROUP BY dept
If you don't want to use a sub select use this.
SELECT dept
,sum(CASE WHEN extract(year FROM age(crdate)) < 10THEN 1 END) "age<10"
,sum(CASE WHEN extract(year FROM age(crdate)) >= 10 AND extract(year FROM age(crdate)) < 20 THEN 1 END) "10<age<20"
,sum(CASE WHEN extract(year FROM age(crdate)) >= 20 THEN 1 END) "20<age"
FROM dt
GROUP BY dept
i have the following situation. every row has a timestamp when it was written on table. now i want to evaluate per day how many rows have been inserted before 5 am and how many after. how can that be done??
You can use the HH24 format to get the hour in 24-hour time:
select trunc(created_Date) as the_day
,sum(case when to_number(to_char(created_Date,'HH24')) < 5 then 1 else 0 end) as before_five
,sum(case when to_number(to_char(created_Date,'HH24')) >= 5 then 1 else 0 end) as after_five
from yourtable
group by trunc(created_Date)
Per USER's comment on 5:10, to show timestamps just before and after 5:
select trunc(created_Date) as the_day
,sum(case when to_number(to_char(created_Date,'HH24')) < 5 then 1 else 0 end) as before_five
,sum(case when to_number(to_char(created_Date,'HH24')) >= 5 then 1 else 0 end) as after_five
from (
-- one row januar 1 just after 5:00 a.m.
select to_Date('01/01/2015 05:10:12','dd/mm/yyyy hh24:mi:ss') as created_date from dual
union all
-- one row Januar 2 just before 5:00 a.m.
select to_Date('02/01/2015 04:59:12','dd/mm/yyyy hh24:mi:ss') as created_date from dual
)
group by trunc(created_Date);
THE_DAY, BEFORE_FIVE, AFTER_FIVE
02/01/2015, 1, 0
01/01/2015, 0, 1
Assuming your timestamp is a DATE column:
select trunc(date_written) as day
, count (case when (date_written-trunc(date_written))*24 < 5 then 1 end) before_5_count
, count (case when (date_written-trunc(date_written))*24 >= 5 then 1 end) after_5_count
from mytable
group by trunc(date_written)
select to_char(time_column, 'dd/mm/yyyy'),
sum( decode ( greatest(extract(hour from time_column), 5), extract(hour from time_column), 1, 0)) post_5,
sum( decode ( greatest(extract(hour from time_column), 5), extract(hour from time_column), 0, 1)) pre_5
from test_time
group by to_char(time_column, 'dd/mm/yyyy')
I'm trying write a query to retrieve the following data :
TYPE | TOTAL | 0_10 DAYS | 10_20 DAYS | .......
X 300 100 200 .......
Y 0 0 0 .......
Z 600 50 120 .......
I have to group all my entries by type and count the number of entries of each type for each date range and add them up as a total.
My problem is the need to display rows of zeros for the types for which I don't retrieve any data. Basically the type column always displays a fixed amount of types. So far I have tried using 'UNION ALL' but then the rows of zeros will always show. Here is my query :
SELECT TYPE AS "ORDERS",
Count(*) AS "TOTAL",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 10 AND SYSDATE ) THEN 1
ELSE 0
END), 0) AS "0_10_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 20 AND SYSDATE - 11 ) THEN
1
ELSE 0
END), 0) AS "10_20_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 30 AND SYSDATE - 21 ) THEN
1
ELSE 0
END), 0) AS "20_30_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER <= To_date(SYSDATE - 30) ) THEN 1
ELSE 0
END), 0) AS "PLUS_30_DAYS"
FROM T_ORDERS
WHERE TYPE = 'X'
OR TYPE = 'Y'
OR TYPE = 'Z'
GROUP BY TYPE
UNION ALL
SELECT TYPE AS "ORDERS",
0 AS "TOTAL",
0 AS "0_10_DAYS",
0 AS "10_20_DAYS",
0 AS "20_30_DAYS",
0 AS "PLUS_30_DAYS"
FROM T_ORDERS
WHERE TYPE IS NOT NULL
GROUP BY TYPE;
I'm new to SQL so bear with me if any of the answers to questions on this topic solves mine but I can't seem to work it out. If something is unclear please write it in comment box.
Try:
SELECT TYPE AS "ORDERS",
Count(DATE_ORDER) AS "TOTAL",
Nvl(Sum(CASE
WHEN (DATE_ORDER BETWEEN SYSDATE - 10 AND SYSDATE) THEN 1
ELSE 0
END), 0) AS "0_10_DAYS",
Nvl(Sum(CASE
WHEN (DATE_ORDER BETWEEN SYSDATE - 20 AND SYSDATE - 11) THEN 1
ELSE 0
END), 0) AS "10_20_DAYS",
Nvl(Sum(CASE
WHEN (DATE_ORDER BETWEEN SYSDATE - 30 AND SYSDATE - 21) THEN 1
ELSE 0
END), 0) AS "20_30_DAYS",
Nvl(Sum(CASE
WHEN (DATE_ORDER <= To_date(SYSDATE - 30)) THEN 1
ELSE 0
END), 0) AS "PLUS_30_DAYS"
FROM (SELECT TYPE, DATE_ORDER
FROM T_ORDERS
WHERE TYPE IN ('X', 'Y', 'Z')
UNION ALL
SELECT DECODE(LEVEL, 1,'X', 2,'Y', 3,'Z') TYPE, NULL DATE_ORDER
FROM DUAL
CONNECT BY LEVEL <= 3
) SQ
GROUP BY TYPE
you can use an OUTER JOIN to achive the desired result
with types
AS
(
SELECT 'X' as t_name FROM dual
UNION ALL
SELECT 'Y' as t_name FROM dual
UNION ALL
SELECT 'Z' as t_name FROM dual
)
SELECT
types.t_name AS "ORDERS",
SUM(CASE WHEN T_ORDERS.TYPE IS NULL THEN 0 ELSE 1 END ) AS "TOTAL",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 10 AND SYSDATE ) THEN 1
ELSE 0
END), 0) AS "0_10_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 20 AND SYSDATE - 11 ) THEN
1
ELSE 0
END), 0) AS "10_20_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 30 AND SYSDATE - 21 ) THEN
1
ELSE 0
END), 0) AS "20_30_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER <= To_date(SYSDATE - 30) ) THEN 1
ELSE 0
END), 0) AS "PLUS_30_DAYS"
FROM
types
LEFT OUTER JOIN T_ORDERS ON (types.t_name = T_ORDERS.TYPE )
GROUP BY types.t_name
or if you already have all types in a TYPES table you can use this table instead of WITH
SELECT
types.t_name AS "ORDERS",
SUM(CASE WHEN T_ORDERS.TYPE IS NULL THEN 0 ELSE 1 END ) AS "TOTAL",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 10 AND SYSDATE ) THEN 1
ELSE 0
END), 0) AS "0_10_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 20 AND SYSDATE - 11 ) THEN
1
ELSE 0
END), 0) AS "10_20_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER BETWEEN SYSDATE - 30 AND SYSDATE - 21 ) THEN
1
ELSE 0
END), 0) AS "20_30_DAYS",
Nvl(Sum(CASE
WHEN ( DATE_ORDER <= To_date(SYSDATE - 30) ) THEN 1
ELSE 0
END), 0) AS "PLUS_30_DAYS"
FROM
types
LEFT OUTER JOIN T_ORDERS ON (types.t_name = T_ORDERS.TYPE )
WHERE
types.t_name IN ( 'X', 'Y','Z')
GROUP BY types.t_name