Oracle - Distinct with a Group by date - sql

I have a table like this in a Oracle 11g Database
TABLE REC
REC_ID NUMBER
CARD_ID NUMBER
REC_STATUS NUMBER
REC_DATE TIMESTAMP
I want to know how many cards have recharged in a given period, but I want this information grouped by date.
If a card_id has already been counted on one date, it should not be counted on another next (distinct).
Here some test data
with
REC ( REC_ID, CARD_ID, REC_STATUS, REC_DATE ) as (
select '1', '100', '1', SYSTIMESTAMP - 5 from dual union all
select '2', '100', '1', SYSTIMESTAMP - 5 from dual union all
select '3', '200', '1', SYSTIMESTAMP - 5 from dual union all
select '4', '100', '1', SYSTIMESTAMP - 4 from dual union all
select '5', '300', '1', SYSTIMESTAMP - 4 from dual union all
select '6', '200', '1', SYSTIMESTAMP - 4 from dual union all
select '7', '100', '1', SYSTIMESTAMP - 3 from dual union all
select '8', '400', '1', SYSTIMESTAMP - 3 from dual union all
select '9', '400', '1', SYSTIMESTAMP - 3 from dual union all
select '10', '400', '1', SYSTIMESTAMP - 2 from dual union all
select '11', '300', '1', SYSTIMESTAMP - 2 from dual union all
select '12', '100', '1', SYSTIMESTAMP - 2 from dual union all
select '13', '400', '1', SYSTIMESTAMP - 2 from dual
)
-- end of test data
When I execute the query like this, i have the total count of 4, which is correct.
SELECT
COUNT(DISTINCT CARD_ID) COUNT
FROM REC
WHERE REC_STATUS = 1
Result
|COUNT|
| 4 |
But, when I try this way, i have the total count of 10.
This is because when I use a "group by" on a date and use the "distinct" in the ID, the distinction will only work for the grouped date, not for the total period.
SELECT
TRUNC(REC_DATE) DAT,
COUNT(DISTINCT CARD_ID) COUNT
FROM REC
WHERE REC_STATUS = 1
GROUP BY TRUNC(REC_DATE)
Result
DAT | COUNT
14/06/19 | 2
13/06/19 | 3
15/06/19 | 3
12/06/19 | 2
What can I do to apply the distinct to the period total and still keep the grouping by date?


Perhaps you just want the earliest date for each card:
SELECT TRUNC(MIN_REC_DATE) as DAT,
COUNT(*) as COUNT
FROM (SELECT CARD_ID, MIN(REC_DATE) as MIN_REC_DATE
FROM REC
WHERE REC_STATUS = 1
GROUP BY CARD_ID
) R
GROUP BY TRUNC(MIN_REC_DATE);

Related

Which statement to use based on its row and transaction in stay that way

I am getting stuck on this, hard to explain to write down here as well the subject heading hopefully by the data example and output result below that enough to give you an idea.
I am run out which Oracle SQL statement best to use. The over (partition) seem didn't work out for the below scenario.
Before & After:
DATA
customer_id
row_id
date
type
LB01
22
14/03/2022
CAR 1
LB01
21
11/03/2022
CAR 1
LB01
20
9/11/2001
CAR 1
LB01
19
16/10/2001
CAR 1
LB01
18
10/08/2001
CAR 2
LB01
17
29/05/2001
CAR 2
LB01
16
24/04/2001
CAR 2
LB01
15
13/03/2001
CAR 3
LB01
14
21/12/2000
CAR 3
LB01
13
13/11/2000
CAR 3
LB01
12
20/10/2000
CAR 3
LB01
11
14/03/2000
CAR 1
LB01
10
18/01/2000
CAR 1
LB01
9
24/12/1999
CAR 2
LB01
8
14/09/1999
CAR 2
LB01
7
30/03/1999
CAR 2
LB01
6
24/02/1999
CAR 2
LB01
5
19/02/1999
CAR 4
LB01
4
15/12/1998
CAR 4
LB01
3
15/12/1998
CAR 4
LB01
2
24/09/1998
CAR 4
LB01
1
06/08/1998
CAR 4
The output that I want result like this:
customer_id
type
min_date
max_date
LB01
Car 1
16/10/2001
14/03/2002
LB01
Car 2
24/04/2001
10/08/2001
LB01
Car 3
20/10/2000
13/03/2001
LB01
Car 1
18/01/2000
14/03/2000
LB01
Car 2
24/02/1999
24/12/1999
LB01
Car 4
6/08/1998
19/02/1999
I hope those makes sense for you and hopefully you can assist me on this.

You have to apply Tabibitosan algorithm first:
select customer_id, type, rn, min(dat) as min_date, max(dat) as max_dat
from (
select d.*, row_id+1-row_number() over(partition by customer_id, type order by row_id) as rn
from data d
)
group by customer_id, type, rn
order by customer_id, type
;
CUST TYPE RN MIN_DATE MAX_DAT
---- ----- ---------- -------- --------
LB01 CAR 1 10 18/01/00 14/03/00
LB01 CAR 1 17 16/10/01 14/03/22
LB01 CAR 2 6 24/02/99 24/12/99
LB01 CAR 2 12 24/04/01 10/08/01
LB01 CAR 3 12 20/10/00 13/03/01
LB01 CAR 4 1 06/08/98 19/02/99

Just create your own grouping calculation out of already existing ROW_ID and use MIN_DATE for ordering:
SELECT CUST_ID, A_TYPE, Min(A_DATE) "MIN_DATE", Max(A_DATE) "MAX_DATE"
FROM (SELECT t.*,
Max(ROW_ID) OVER(Partition By CUST_ID || A_TYPE ORDER BY ROW_ID DESC Rows Between Unbounded Preceding And Current Row) -
(ROW_ID + Sum(1) OVER(PARTITION BY CUST_ID || A_TYPE ORDER BY ROW_ID DESC) - 1) "GRP"
FROM tbl t
ORDER BY ROW_ID DESC )
GROUP BY CUST_ID, A_TYPE, GRP
ORDER BY CUST_ID, MIN(A_DATE) DESC
With your sample data:
WITH
tbl (CUST_ID, ROW_ID, A_DATE, A_TYPE) AS
( Select 'LB01', 22, To_Date('14/03/2022', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
Select 'LB01', 21, To_Date('11/03/2022', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
Select 'LB01', 20, To_Date('09/11/2001', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
Select 'LB01', 19, To_Date('16/10/2001', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
--
Select 'LB01', 18, To_Date('10/08/2001', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
Select 'LB01', 17, To_Date('29/05/2001', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
Select 'LB01', 16, To_Date('24/04/2001', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
--
Select 'LB01', 15, To_Date('13/03/2001', 'dd/mm/yyyy'), 'CAR 3' From Dual Union All
Select 'LB01', 14, To_Date('21/12/2000', 'dd/mm/yyyy'), 'CAR 3' From Dual Union All
Select 'LB01', 13, To_Date('13/11/2000', 'dd/mm/yyyy'), 'CAR 3' From Dual Union All
Select 'LB01', 12, To_Date('20/10/2000', 'dd/mm/yyyy'), 'CAR 3' From Dual Union All
--
Select 'LB01', 11, To_Date('14/03/2000', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
Select 'LB01', 10, To_Date('18/01/2000', 'dd/mm/yyyy'), 'CAR 1' From Dual Union All
--
Select 'LB01', 9, To_Date('24/12/1999', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
Select 'LB01', 8, To_Date('14/09/1999', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
Select 'LB01', 7, To_Date('30/03/1999', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
Select 'LB01', 6, To_Date('24/02/1999', 'dd/mm/yyyy'), 'CAR 2' From Dual Union All
--
Select 'LB01', 5, To_Date('19/02/1999', 'dd/mm/yyyy'), 'CAR 4' From Dual Union All
Select 'LB01', 4, To_Date('15/12/1998', 'dd/mm/yyyy'), 'CAR 4' From Dual Union All
Select 'LB01', 3, To_Date('15/12/1998', 'dd/mm/yyyy'), 'CAR 4' From Dual Union All
Select 'LB01', 2, To_Date('24/09/1998', 'dd/mm/yyyy'), 'CAR 4' From Dual Union All
Select 'LB01', 1, To_Date('06/08/1998', 'dd/mm/yyyy'), 'CAR 4' From Dual
)
R e s u l t :
CUST_ID
A_TYPE
MIN_DATE
MAX_DATE
LB01
CAR 1
16-OCT-01
14-MAR-22
LB01
CAR 2
24-APR-01
10-AUG-01
LB01
CAR 3
20-OCT-00
13-MAR-01
LB01
CAR 1
18-JAN-00
14-MAR-00
LB01
CAR 2
24-FEB-99
24-DEC-99
LB01
CAR 4
06-AUG-98
19-FEB-99

PLEASE NOTE: For some reason this website can't tick both answers that the solution provided by #p3consulting and #d r are working on my data by creating a new column for a new row id in that way row numbers are in orderly
subquery before that;
row_number() over(partition by cust_id order by seq_id ) row_id
depend on how your data has numbers are not in orderly number

refer to the above post made by #p3consulting regarding the Tabibitosan algorithm
here is the below script that you can copy and paste into your Oracle SQL to learn
for my question here still does not work for my data and still searching the right script
with
sample_data (customer_id, row_id, mock_date, product_type) as (
select 'LB01', '22', to_date ('03/14/22', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '21', to_date ('03/11/22', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '20', to_date ('11/09/01', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '19', to_date ('10/16/01', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '18', to_date ('08/10/01', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '17', to_date ('05/29/01', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '16', to_date ('04/24/01', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '15', to_date ('03/13/01', 'mm/dd/rr'), 'CAR 3' from dual union all
select 'LB01', '14', to_date ('12/21/00', 'mm/dd/rr'), 'CAR 3' from dual union all
select 'LB01', '13', to_date ('11/13/00', 'mm/dd/rr'), 'CAR 3' from dual union all
select 'LB01', '12', to_date ('10/20/00', 'mm/dd/rr'), 'CAR 3' from dual union all
select 'LB01', '11', to_date ('03/14/00', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '10', to_date ('01/18/00', 'mm/dd/rr'), 'CAR 1' from dual union all
select 'LB01', '09', to_date ('12/24/99', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '08', to_date ('09/14/99', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '07', to_date ('03/30/99', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '06', to_date ('02/24/99', 'mm/dd/rr'), 'CAR 2' from dual union all
select 'LB01', '05', to_date ('02/19/99', 'mm/dd/rr'), 'CAR 4' from dual union all
select 'LB01', '04', to_date ('12/15/98', 'mm/dd/rr'), 'CAR 4' from dual union all
select 'LB01', '03', to_date ('12/15/98', 'mm/dd/rr'), 'CAR 4' from dual union all
select 'LB01', '02', to_date ('09/24/98', 'mm/dd/rr'), 'CAR 4' from dual union all
select 'LB01', '01', to_date ('06/08/98', 'mm/dd/rr'), 'CAR 4' from dual
)
select
customer_id ,
product_type ,
grp ,
min(mock_date) as min_date ,
max(mock_date) as max_date
from (
select d.* ,
row_id + 1 - row_number () over (partition by customer_id, product_type order by row_id) as grp
from sample_data d )
group by
customer_id ,
product_type ,
grp
order by
grp desc

how to use windows function during merge in sql

I am working in oracle sql. I have two table which is linked to each other by one column - company_id (see on the picture); I want to merge table 1 to table 2 and calculate 6 month average (6 month before period from table 2) of income for each company_id and each date of table2. I appreciate any code/idea how to solve this task.

You can use an analytic range window to calculate the averages for table1 and then JOIN the result to table2:
SELECT t2.*,
t1.avg_income_6,
t1.avg_income_12
FROM table2 t2
LEFT OUTER JOIN (
SELECT company_id,
dt,
ROUND(AVG(income) OVER (
PARTITION BY company_id
ORDER BY dt
RANGE BETWEEN INTERVAL '5' MONTH PRECEDING
AND INTERVAL '0' MONTH FOLLOWING
), 2) AS avg_income_6,
ROUND(AVG(income) OVER (
PARTITION BY company_id
ORDER BY dt
RANGE BETWEEN INTERVAL '11' MONTH PRECEDING
AND INTERVAL '0' MONTH FOLLOWING
), 2) AS avg_income_12
FROM table1
) t1
ON (t2.company_id = t1.company_id AND t2.dt = t1.dt);
Which, for the sample data:
CREATE TABLE table1 (company_id, dt, income) AS
SELECT 1, date '2019-01-01', 65 FROM DUAL UNION ALL
SELECT 1, date '2019-02-01', 58 FROM DUAL UNION ALL
SELECT 1, date '2019-03-01', 12 FROM DUAL UNION ALL
SELECT 1, date '2019-04-01', 81 FROM DUAL UNION ALL
SELECT 1, date '2019-05-01', 38 FROM DUAL UNION ALL
SELECT 1, date '2019-06-01', 81 FROM DUAL UNION ALL
SELECT 1, date '2019-07-01', 38 FROM DUAL UNION ALL
SELECT 1, date '2019-08-01', 69 FROM DUAL UNION ALL
SELECT 1, date '2019-09-01', 54 FROM DUAL UNION ALL
SELECT 1, date '2019-10-01', 90 FROM DUAL UNION ALL
SELECT 1, date '2019-11-01', 10 FROM DUAL UNION ALL
SELECT 1, date '2019-12-01', 12 FROM DUAL UNION ALL
SELECT 1, date '2020-01-01', 11 FROM DUAL UNION ALL
SELECT 1, date '2020-02-01', 83 FROM DUAL UNION ALL
SELECT 1, date '2020-03-01', 18 FROM DUAL UNION ALL
SELECT 1, date '2020-04-01', 28 FROM DUAL UNION ALL
SELECT 1, date '2020-05-01', 52 FROM DUAL UNION ALL
SELECT 1, date '2020-06-01', 21 FROM DUAL UNION ALL
SELECT 1, date '2020-07-01', 54 FROM DUAL UNION ALL
SELECT 1, date '2020-08-01', 30 FROM DUAL UNION ALL
SELECT 1, date '2020-09-01', 12 FROM DUAL UNION ALL
SELECT 1, date '2020-10-01', 25 FROM DUAL UNION ALL
SELECT 1, date '2020-11-01', 86 FROM DUAL UNION ALL
SELECT 1, date '2020-12-01', 4 FROM DUAL UNION ALL
SELECT 1, date '2021-01-01', 10 FROM DUAL UNION ALL
SELECT 1, date '2021-02-01', 72 FROM DUAL UNION ALL
SELECT 1, date '2021-03-01', 65 FROM DUAL UNION ALL
SELECT 1, date '2021-04-01', 25 FROM DUAL;
CREATE TABLE table2 (company_id, dt) AS
SELECT 1, date '2019-06-01' FROM DUAL UNION ALL
SELECT 1, date '2019-09-01' FROM DUAL UNION ALL
SELECT 1, date '2019-12-01' FROM DUAL UNION ALL
SELECT 1, date '2020-01-01' FROM DUAL UNION ALL
SELECT 1, date '2020-07-01' FROM DUAL UNION ALL
SELECT 1, date '2020-08-01' FROM DUAL UNION ALL
SELECT 1, date '2021-03-01' FROM DUAL UNION ALL
SELECT 1, date '2021-04-01' FROM DUAL;
Outputs:
COMPANY_ID
DT
AVG_INCOME_6
AVG_INCOME_12
1
2019-06-01 00:00:00
55.83
55.83
1
2019-09-01 00:00:00
60.17
55.11
1
2019-12-01 00:00:00
45.5
50.67
1
2020-01-01 00:00:00
41
46.17
1
2020-07-01 00:00:00
42.67
41.83
1
2020-08-01 00:00:00
33.83
38.58
1
2021-03-01 00:00:00
43.67
38.25
1
2021-04-01 00:00:00
43.67
38
db<>fiddle here

I don't think you need any window function here (if you were thinking of analytic functions); ordinary avg with appropriate join conditions should do the job.
Sample data:
SQL> with
2 table1 (company_id, datum, income) as
3 (select 1, date '2019-01-01', 65 from dual union all
4 select 1, date '2019-02-01', 58 from dual union all
5 select 1, date '2019-03-01', 12 from dual union all
6 select 1, date '2019-04-01', 81 from dual union all
7 select 1, date '2019-05-01', 38 from dual union all
8 select 1, date '2019-06-01', 81 from dual union all
9 select 1, date '2019-07-01', 38 from dual union all
10 select 1, date '2019-08-01', 69 from dual union all
11 select 1, date '2019-09-01', 54 from dual union all
12 select 1, date '2019-10-01', 90 from dual union all
13 select 1, date '2019-11-01', 10 from dual union all
14 select 1, date '2019-12-01', 12 from dual
15 ),
16 table2 (company_id, datum) as
17 (select 1, date '2019-06-01' from dual union all
18 select 1, date '2019-09-01' from dual union all
19 select 1, date '2019-12-01' from dual union all
20 select 1, date '2020-01-01' from dual union all
21 select 1, date '2020-07-01' from dual
22 )
Query begins here:
23 select b.company_id,
24 b.datum ,
25 round(avg(a.income), 2) result
26 from table1 a join table2 b on a.company_id = b.company_id
27 and a.datum > add_months(b.datum, -6)
28 and a.datum <= b.datum
29 group by b.company_id, b.datum;
COMPANY_ID DATUM RESULT
---------- -------- ----------
1 01.06.19 55,83
1 01.09.19 60,17
1 01.12.19 45,5
1 01.01.20 47
SQL>

Count daily fidelity

I have the below table and I would like to count, day by day, the number of distinct people who logged in everyday. For example, for day 1, everyone logged in, so it's 4. For day 4, there's just one person ID who logged in everyday since day 1, so the count would be 1.
DAY
PERSON_ID
1
01
1
02
1
03
1
04
2
01
2
02
2
03
3
01
4
02
4
01
Expected output.
DAY
PEOPLE_LOGGED_EVERYDAY
PEOPLE
1
4
01, 02, 03, 04
2
3
01, 02, 03
3
1
01
4
1
01
EDIT: the query should also work on the below data.
with t ( DAY, PERSON_ID ) AS(
SELECT 10, '01' FROM DUAL UNION ALL
SELECT 10, '02' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 12, '01' FROM DUAL UNION ALL
SELECT 12, '02' FROM DUAL UNION ALL
SELECT 12, '03' FROM DUAL UNION ALL
SELECT 13, '04' FROM DUAL UNION ALL
SELECT 13, '01' FROM DUAL UNION ALL
SELECT 14, '02' FROM DUAL UNION ALL
SELECT 14, '01' FROM DUAL)
Expected output:
DAY
PEOPLE_LOGGED_EVERYDAY
PEOPLE
EXPLANATION
10
3
01, 02, 04
Three unique people in day 10
12
2
01, 02
Day 11 does not have values, so it's not included. From those in day 10, only 2 appear in day 12
13
1
01
From those in day 10 and 12, only 01 appears in day 13
14
1
01
From those in day 10, 12 and 13, only 01 appears in day 14

You can use listagg() with group by clause. If day is always start from the 1 and increases by 1 then you can use below query. He with the help of exits I have selected only those person_id which are available in all the previous days.
create table yourtable(DAY int, PERSON_ID varchar(10));
insert into yourtable values(1, '01');
insert into yourtable values(1, '02');
insert into yourtable values(1, '03');
insert into yourtable values(1, '04');
insert into yourtable values(2, '01');
insert into yourtable values(2, '02');
insert into yourtable values(2, '03');
insert into yourtable values(3, '01');
insert into yourtable values(4, '02');
insert into yourtable values(4, '01');
Query:
select day, count(person_id) as PEOPLE_LOGGED_EVERYDAY, LISTAGG(person_id,',') WITHIN GROUP(ORDER BY person_id) AS PEOPLE
from yourtable a
where exists (select 1 from yourtable b where b.day<=a.day and a.person_id=b.person_id
group by person_id having count(day)=a.day)
group by day;
Output:
DAY
PEOPLE_LOGGED_EVERYDAY
PEOPLE
1
4
01,02,03,04
2
3
01,02,03
3
1
01
4
1
01
db<fiddle here
Instead of day sequence if you had increasing dates in day column:
create table yourtable(DAY date, PERSON_ID varchar(10));
insert into yourtable values(date '2021-01-01', '01');
insert into yourtable values(date '2021-01-01', '02');
insert into yourtable values(date '2021-01-01', '03');
insert into yourtable values(date '2021-01-01', '04');
insert into yourtable values(date '2021-01-02', '01');
insert into yourtable values(date '2021-01-02', '02');
insert into yourtable values(date '2021-01-02', '03');
insert into yourtable values(date '2021-01-03', '01');
insert into yourtable values(date '2021-01-04', '02');
insert into yourtable values(date '2021-01-04', '01');
Query:
select day, count(person_id) as PEOPLE_LOGGED_EVERYDAY, LISTAGG(person_id,',') WITHIN GROUP(ORDER BY person_id) AS PEOPLE
from yourtable a
where exists (select 1 from yourtable b where b.day<=a.day and a.person_id=b.person_id
group by person_id having count(day)=( max(day)- min(day))+1)
group by day;
Output:
DAY
PEOPLE_LOGGED_EVERYDAY
PEOPLE
01-JAN-21
4
01,02,03,04
02-JAN-21
3
01,02,03
03-JAN-21
1
01
04-JAN-21
1
01
db<fiddle here
Revised answer
create table yourtable(DAY int, PERSON_ID varchar(10));
insert into yourtable(day,person_id)
with cte ( DAY, PERSON_ID ) AS(
SELECT 10, '01' FROM DUAL UNION ALL
SELECT 10, '02' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 12, '01' FROM DUAL UNION ALL
SELECT 12, '02' FROM DUAL UNION ALL
SELECT 12, '03' FROM DUAL UNION ALL
SELECT 13, '04' FROM DUAL UNION ALL
SELECT 13, '01' FROM DUAL UNION ALL
SELECT 14, '02' FROM DUAL UNION ALL
SELECT 14, '01' FROM DUAL)
select * from cte ;
Query#1 (for Oracle 19c and later)
select day, count(person_id) as PEOPLE_LOGGED_EVERYDAY, LISTAGG(distinct person_id,',') WITHIN GROUP(ORDER BY person_id) AS PEOPLE
from yourtable a
where exists (select 1 from yourtable b where b.day<=a.day and a.person_id=b.person_id
group by person_id having count(DISTINCT day)=(select COUNT( distinct DAY) from yourtable where day<=a.day))
group by day;
Query#1 (for Oracle 18c and earlier)
select day, count(person_id) as PEOPLE_LOGGED_EVERYDAY, LISTAGG( person_id,',') WITHIN GROUP(ORDER BY person_id) AS PEOPLE
from
(
select distinct day, person_id
from yourtable a
where exists (select 1 from yourtable b where b.day<=a.day and a.person_id=b.person_id
group by person_id having count(DISTINCT day)=(select COUNT( distinct DAY) from yourtable where day<=a.day))
)t group by day
Output:
DAY
PEOPLE_LOGGED_EVERYDAY
PEOPLE
10
3
01,02,04
12
2
01,02
13
1
01
14
1
01
db<fiddle here

In Standard SQL, I would approach this by doing the following:
Enumerate the days for each person.
Determine the earliest day for each person.
Filter where the earliest day is "1" and the enumeration equals the days.
Then aggregate:
select day, count(*),
listagg(person_id, ',') within group (order by person_id)
from (select t.*,
row_number() over (partition by person_id order by day) as seqnum,
min(day) over (partition by person_id) as min_day
from t
) t
where seqnum = day and min_day = 1
group by day
order by day;
Note only is this simpler than using match recognize, but I would guess that the performance would be much better too.

You can use either:
SELECT DAY,
COUNT(DISTINCT person_id) AS num_people
FROM (
SELECT t.*,
DENSE_RANK() OVER (ORDER BY day)
- DENSE_RANK() OVER (PARTITION BY person_id ORDER BY day) AS day_grp
FROM table_name t
)
WHERE day_grp = 0
GROUP BY day
ORDER BY day
or MATCH_RECOGNIZE to find the successive days:
SELECT day,
COUNT(
DISTINCT
CASE cls WHEN 'CONSECUTIVE_DAYS' THEN person_id END
) AS num_people
FROM (
SELECT t.*,
DENSE_RANK() OVER (ORDER BY day) AS day_rank
FROM table_name t
)
MATCH_RECOGNIZE(
PARTITION BY person_id
ORDER BY day
MEASURES
classifier() AS cls
ALL ROWS PER MATCH
PATTERN ( ^ consecutive_days* )
DEFINE
consecutive_days AS COALESCE( PREV(day_rank) + 1, 1 ) = day_rank
)
GROUP BY day
ORDER BY day
Which, for the sample data:
CREATE TABLE table_name ( DAY, PERSON_ID ) AS
SELECT 1, '01' FROM DUAL UNION ALL
SELECT 1, '02' FROM DUAL UNION ALL
SELECT 1, '03' FROM DUAL UNION ALL
SELECT 1, '04' FROM DUAL UNION ALL
SELECT 2, '01' FROM DUAL UNION ALL
SELECT 2, '02' FROM DUAL UNION ALL
SELECT 2, '03' FROM DUAL UNION ALL
SELECT 3, '01' FROM DUAL UNION ALL
SELECT 3, '02' FROM DUAL UNION ALL
SELECT 4, '01' FROM DUAL;
Outputs:
DAY
NUM_PEOPLE
1
4
2
3
3
2
4
1
and for the sample data:
CREATE TABLE table_name ( DAY, PERSON_ID ) AS
SELECT 10, '01' FROM DUAL UNION ALL
SELECT 10, '02' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 10, '04' FROM DUAL UNION ALL
SELECT 12, '01' FROM DUAL UNION ALL
SELECT 12, '02' FROM DUAL UNION ALL
SELECT 12, '03' FROM DUAL UNION ALL
SELECT 13, '04' FROM DUAL UNION ALL
SELECT 13, '01' FROM DUAL UNION ALL
SELECT 14, '02' FROM DUAL UNION ALL
SELECT 14, '01' FROM DUAL
Outputs:
DAY
NUM_PEOPLE
10
3
12
2
13
1
14
1
db<>fiddle here

How to convert column with Rank Value into rows in oracle

I've some query, that returns following data:
Month Year EMP_ID EMP_NAME RANK
Jan 2019 1 EmpName1 1
Jan 2019 2 EmpName2 2
Jan 2019 3 EmpName3 3
Jan 2019 4 EmpName4 4
Jan 2019 5 EmpName5 5
FEB 2019 1 EmpName1 1
FEB 2019 2 EmpName2 2
FEB 2019 3 EmpName3 3
FEB 2019 4 EmpName4 4
FEM 2019 5 EmpName5 5
I want to display this data in the following format:
Month Year Rank1 Rank2 Rank3 Rank4 Rank5
Jan 2019 EmpName1 EmpNAme2 EmpName3 EmpName4 EmpName5
Feb 2019 EmpName1 EmpNAme2 EmpName3 EmpName4 EmpName5

If version Oracle 11+ to use pivot
with tbl as
(SELECT 'JAN' mon, '2019' y, '1' rn, 'EmpName1' name from dual
UNION ALL
select 'JAN', '2019', '2', 'EmpName2' from dual
union all
select 'JAN', '2019', '3', 'EmpName3' from dual
union all
select 'JAN', '2019', '4', 'EmpName4' from dual
union all
select 'JAN', '2019', '5', 'EmpName5' from dual
union all
select 'FEB', '2019', '1', 'EmpName1' from dual
union all
select 'FEB', '2019', '2', 'EmpName2' from dual
union all
select 'FEB', '2019', '3', 'EmpName3' from dual
union all
select 'FEB', '2019', '4', 'EmpName4' from dual
union all
select 'FEB', '2019', '5', 'EmpName5' from dual)
select *
from (select mon, y, rn, name
from tbl)
pivot
(
MAX(name)
FOR rn
IN ('1', '2', '3', '4', '5')
)
ORDER BY 1
if 10g
with tbl as
(SELECT 'JAN' mon, '2019' y, '1' rn, 'EmpName1' name from dual
UNION ALL
select 'JAN', '2019', '2', 'EmpName2' from dual
union all
select 'JAN', '2019', '3', 'EmpName3' from dual
union all
select 'JAN', '2019', '4', 'EmpName4' from dual
union all
select 'JAN', '2019', '5', 'EmpName5' from dual
union all
select 'FEB', '2019', '1', 'EmpName1' from dual
union all
select 'FEB', '2019', '2', 'EmpName2' from dual
union all
select 'FEB', '2019', '3', 'EmpName3' from dual
union all
select 'FEB', '2019', '4', 'EmpName4' from dual
union all
select 'FEB', '2019', '5', 'EmpName5' from dual)
select
mon,
y,
min(decode(rn, 1, nm, NULL)) Rank1 ,
min(decode(rn, 2, nm, NULL)) Rank2 ,
min(decode(rn, 3, nm, NULL)) Rank3 ,
min(decode(rn, 4, nm, NULL)) Rank4 ,
min(decode(rn, 5, nm, NULL)) Rank5
from
(
select
tbl.mon,
tbl.y,
tbl.rn,
max(name) nm
from
tbl
group by tbl.mon, tbl.y, tbl.rn
)
group by mon, y

Just use Conditional Aggregation with case..when expressions :
select Month, Year,
max( case when emp_id = 1 then Emp_Name end ) as EmpName1,
max( case when emp_id = 2 then Emp_Name end ) as EmpName2,
max( case when emp_id = 3 then Emp_Name end ) as EmpName3,
max( case when emp_id = 4 then Emp_Name end ) as EmpName4,
max( case when emp_id = 5 then Emp_Name end ) as EmpName5
from tab
group by Month, Year

Select Query Oracle

My Table Structure is like below:
Carrier Terminal timestamp1
1 1 21-Mar-17
2 101 21-Mar-17
3 2 21-Mar-17
4 202 21-Mar-17
5 3 21-Mar-17
6 303 21-Mar-17
where carrier
flight 1,2 = Delta
flight 3,4 = Air France
flight 5,6 = Lufthanse
and
Terminal 1,101 = T1
terminal 2,202 = T2
terminal 3,303 = T3
I am trying output like below:
count(Delta), count(Air France), count(Lufthansa), terminal as column output
2, 0, 0, T1
0, 2, 0, T2
0, 0, 2, T3
I have started like this
select count(Delta), count(Air France), count(Lufthansa), terminal
from table_name
where timestamp between '01-Mar-18 07.00.00.000000 AM' and '30-Mar-18 07.59.59.999999 AM'
I am trying to write a query to have a count of different carriers flown through a particular day for each terminal
Any Advise will be highly appreciated

I'm making a whole lot of assumptions for this to work... I've extracted all the rules you've mentioned in your text and I've assumed that those structures are are already in place. Otherwise, let us know :)
with flights(carrier, terminal, departure) as(
select 1, 1, timestamp '2017-03-01 01:00:00' from dual union all
select 2, 101, timestamp '2017-03-01 02:00:00' from dual union all
select 3, 2, timestamp '2017-03-01 03:00:00' from dual union all
select 4, 202, timestamp '2017-03-01 04:00:00' from dual union all
select 5, 3, timestamp '2017-03-01 05:00:00' from dual union all
select 6, 303, timestamp '2017-03-01 06:00:00' from dual
)
,carriers(carrier, carrier_name) as(
select 1, 'Delta' from dual union all
select 2, 'Delta' from dual union all
select 3, 'Air France' from dual union all
select 4, 'Air France' from dual union all
select 5, 'Lufthanse' from dual union all
select 6, 'Lufthanse' from dual
)
,terminals(terminal, terminal_name) as(
select 1, 'T1' from dual union all
select 101, 'T1' from dual union all
select 2, 'T2' from dual union all
select 202, 'T2' from dual union all
select 3, 'T3' from dual union all
select 303, 'T3' from dual
)
select terminal_name
,count(case when carrier_name = 'Delta' then 1 end) as "Delta"
,count(case when carrier_name = 'Air France' then 1 end) as "Air France"
,count(case when carrier_name = 'Lufthanse' then 1 end) as "Lufthanse"
from flights f
join carriers c using(carrier)
join terminals t using(terminal)
where departure >= timestamp '2017-03-01 00:00:00'
and departure < timestamp '2017-04-01 00:00:00'
group by terminal_name
order by terminal_name;

with
t ( flight, gate, ts ) as (
select 1, 1, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual union all
select 2, 101, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual union all
select 3, 2, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual union all
select 4, 202, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual union all
select 5, 3, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual union all
select 6, 303, to_timestamp('21-Mar-17', 'dd-Mon-rr') from dual
)
-- End of simulated inputs (for testing only, not part of the solution).
-- SQL query begins below this line. Use your actual table and column names.
select count (case when flight in (1, 2) then 1 end) as delta
, count (case when flight in (3, 4) then 1 end) as air_france
, count (case when flight in (5, 6) then 1 end) as lufthansa
, case when gate in (1, 101) then 'T1'
when gate in (2, 202) then 'T2'
when gate in (3, 303) then 'T3' end as terminal
from t
where ts between '21-Mar-17 02.00.00.000000 AM' and '21-Mar-17 10.00.00.000000 AM'
group by case when gate in (1, 101) then 'T1'
when gate in (2, 202) then 'T2'
when gate in (3, 303) then 'T3' end
order by terminal
;
DELTA AIR_FRANCE LUFTHANSA TERMINAL
---------- ---------- ---------- --------
2 0 0 T1
0 2 0 T2
0 0 2 T3