I am trying to create a script in SQL Server that will count values under a column but I want it to still report missing values not counted.
Currently, I have the following setup with a group by, but it cuts the results in half:
select count(ID) as Count, Building, ID
from table
group by Building, ID
I want my output to show the count per ID as well as null values if there was nothing to count per ID.
Building ID
1234 1
1234 2
4567 3
4567 4
8910 5
0 6
Want the Output To Be:
Building ID Count
1234 1 2
1234 2 2
4567 3 2
4567 4 2
8910 5 1
0 6 0
The total population is 200,000. I want to see 200,000 records with the total counts per name or null values. When I run the above script, I obtain 1's per record.
Example: If ID 1 has a count of 2 and ID 2 has a count of 2, I want both IDs to show up as separate counts per ID.
You need to get the count from a sub-query and then join that sub-query
SELECT
CASE WHEN t1.building is null THEN 0
ELSE t1.building END AS Building,
t1.id,
CASE WHEN t1.building is null THEN 0
ELSE t2.count END AS Count
FROM table t1
JOIN (SELECT building, COUNT(*) as count
FROM table
GROUP BY building) AS t2 ON t2.building = t1.building OR (t2.building is null AND t1.building is null)
try
select count(name) as Count, ID, Building
from table
group by ID, Building
Related
This is my parent table acc_detial -
ACC_DETIAL example -
acc_id
1
2
3
Now i have 3 tables:
ORDER
EMAIL
REPORT
Each table contains 100 rows and acc_id are ForeignKey from ACC_DETIAL.
In ORDER table I have a columns ACC_ID and QUANTITY. I want the count of ACC_ID and sum of QUANTITY.
ORDER table example:
acc_id
quantity
date
1
2
2022/01/22
2
5
2022/01/23
1
10
2022/01/25
3
1
2022/01/25
In EMAIL table I have a column name ACC_ID and I want count of ACC_ID.
EMAIL table example:
acc_id
mail
date
1
5
2022/01/22
2
10
2022/01/22
1
7
2022/01/23
1
7
2022/01/24
2
10
2022/01/25
In REPORT table I have a columns ACC_ID and TYPE and I want the count of ACC_ID and TYPE. Note that TYPE column has only two, possible values:
postive
negative
I want count of each, i.e. count of postive and count of negative in TYPE column.
REPORT table example:
acc_id
type
date
1
positive
2022/01/22
2
negative
2022/01/22
1
negative
2022/01/23
2
postitive
2022/01/26
2
postitive
2022/01/27
I need to take this in a single i need answer as raw query or sqlalchemy. Is it possible or not? Do I need to write separate query to get each table result ?
Result -
result based on above examplec -
acc_id
total_Order_acc_id
total_Order_quantity
total_Email_acc_id
total_Report_acc_id
total_postitive_report
total_negative_report
1
2
12
3
2
1
1
2
1
5
2
3
2
1
3
1
1
Null
Null
Null
Null
You need to aggregate then join as the following:
SELECT ADL.acc_id,
ORD.ord_cnt AS total_Order_acc_id,
ORD.tot_quantity AS total_Order_quantity,
EML.eml_cnt AS total_Email_acc_id,
RPT.rpt_cnt AS total_Report_acc_id,
RPT.pcnt AS total_postitive_report,
RPT.ncnt AS total_negative_report
FROM ACC_DETIAL ADL LEFT JOIN
(
SELECT acc_id,
SUM(quantity) AS tot_quantity,
COUNT(*) AS ord_cnt
FROM ORDERS
GROUP BY acc_id
) ORD
ON ADL.acc_id = ORD.acc_id
LEFT JOIN
(
SELECT acc_id, COUNT(*) AS eml_cnt
FROM EMAIL
GROUP BY acc_id
) EML
ON ADL.acc_id = EML.acc_id
LEFT JOIN
(
SELECT acc_id,
COUNT(*) AS rpt_cnt,
COUNT(*) FILTER (WHERE type='positive') AS pcnt,
COUNT(*) FILTER (WHERE type='negative') AS ncnt
FROM REPORT
GROUP BY acc_id
) RPT
ON ADL.acc_id = RPT.acc_id
See demo
Sample :
Select
`order`.`acc_id`,
report_email_select.`type`,
report_email_select.report_count,
report_email_select.email_count,
SUM(`quantity`) as quantity_sum
FROM
`order`
Left JOIN(
Select
report_select.`acc_id`,
report_select.`type`,
report_select.report_count,
COUNT(*) as email_count
from
(
SELECT
report.`acc_id`,
report.`type`,
COUNT(*) as report_count
FROM
`report`
WHERE
1
GROUP BY
report.`acc_id`,
report.`type`
) AS report_select
INNER JOIN email ON email.acc_id = report_select.acc_id
GROUP BY
report_select.`acc_id`,
report_select.`type`
) AS report_email_select ON `order`.acc_id = report_email_select.acc_id
GROUP BY
`order`.`acc_id`,
report_email_select.`type`;
My table
ID catone cattwo
100 2 1
100 3 1
200 1 2
expect result (count not sum)
ID totalcat1 totalcat2
100 2 2
200 1 1
My query
select COUNT(*) as totalcat1, catone
from Table1
group by cat1
left join
select COUNT(*) as totalcat2, cattwo
from Table1
group by cattwo
Try to have both count columns catone and cattwo
Not sure how to correct it. Thank you
A simple group-by should do it
select ID, COUNT(catone) as totalcat1, COUNT(cattwo) as totalcat2
from Table1
group by ID;
Note that this simply counts the number of values that are not NULL. If your original data was this...
ID catone cattwo
100 2 1
100 3 1
100 4 NULL
... then the result would be
ID totalcat1 totalcat2
100 3 2
If you want to count the distinct values - so totalcat2 would be 1 (as only 1 value exists in that column, although it's there twice) you could use
select ID, COUNT(DISTINCT catone) as totalcat1, COUNT(DISTINCT cattwo) as totalcat2
from Table1
group by ID;
which would return totalcat1 = 3 and totalcat2 = 1.
Here's a db<>fiddle with the two options.
Here's a second db<>fiddle on request of OP with ID 200.
I have a table called "Scan" customer transactions where an individual_id appears once for every different transaction and contains column like scan_id.
I have another table called ids which contains random individual_ids sampled from Scan Table
I would like to join ids with scan and get a single record of ids and scan_id if it matches certain values.
Suppose data is like below
Scan table
Ids scan_id
---- ------
1 100
1 111
1 1000
2 100
2 111
3 124
4 1000
4 111
Ids table
id
1
2
3
4
5
I want below output i.e if scan_id matches either 100 or 1000
Id MT
------ ------
1 1
2 1
3 0
4 1
I executed below query and got error
select MT, d.individual_id
from
(
select
CASE
when scan_id in (90069421,53971306,90068594,136739913,195308160) then 1
ELSE 0
END as MT
from scan cs join ids r
on cs.individual_id = r.individual_id
where
base_div_nbr =1
and
country_code ='US'
and
retail_channel_code=1
and visit_date between '2019-01-01' and '2019-12-31'
) as d
group by individual_id;
I would appreciate any suggestions or help with regard to this Hive query. If there is an efficient way of getting this job done. Let me know.
Use a group by:
select s.individual_id,
max(case when s.scan_id in (100, 1000) then 1 else 0 end) as mt
from scan s
group by s.individual_id;
The ids table doesn't seem to be needed for this query.
I have Table like Below:
Sr_No C_A C_B
-------------------
1 100 A
2 100 A
3 100 B
4 101 A
5 102 A
6 102 B
7 103 A
8 103 A
9 103 B
And I want select query to get below
C_A
----
100
103
I want to know how many records are in C_A column having duplicate values in C_B column.
The query below checks, for each C_A group, that the number of distinct C_B values is less than the total number of values. This condition implies that all C_B values are not unique for a given C_A group, and that there are duplicates.
SELECT C_A
FROM yourTable
GROUP BY C_A
HAVING COUNT(DISTINCT C_B) < COUNT(*)
If I understand well, you may need:
select distinct C_A
from
(select C_A, C_B, count(1) over ( partition by C_A, C_B) as cnt
from test
)
where cnt > 1
The nested query counts the number of duplicates for each couple of values in C_A, C_B, while the external one simply filters this result to only get couples with duplicates
I am trying to do a count from multiple tables but there could be multiple entries in each table. Here is simple sample data simplified. There are actually more then 3 tables but just so I get an understanding of how to do it
table2 table2 table3
person_ID person_id person_id
1 1 2
2 1 2
3 2 1
4 2 4
5 4 5
I'm trying to get a count of each person ID in each table so the output would be the following. Note that personID is a key I don't need the addition of the number of the ID not 2+2+2+2. But the count of the number of appearances it makes in the all tables then the count in each table added together for total number of appearances it makes. Basically I'm trying to find a total number of items attached to each personID
person_id total
1 4
2 4
3 1
4 3
5 2
Select the ids from all the tables together withunion. That result can be grouped by the id and counted for each
select person_id, count(*) as count
from
(
select person_id from table1
union all
select person_id from table2
union all
select person_id from table3
) tmp
group by person_id