I got a query from a question I asked earlier. It worked perfectly. I wanted to count the total number of entries for each student and display their total in a datagridview.
So Jason Smith attended 2 different days which are 2 different entries by date in my table and the datagridview displays 2 for Jason's total classes. David Harris attended 1 class and the datagridview displays 1 for David's total classes.
Here is the query that worked.
SELECT
FirstName AS [First Name],
LastName AS [Last Name],
TrainDate AS [Training Date], Count(*) AS TotalCount
FROM
ACJATTENDANCE
GROUP BY FirstName, LastName, TrainDate, TrainDate
In the query that didn't work it display all the dates attended for each person and a 1 for total class on each date in the datagridview.
SELECT
ID AS [STUDENT ID],
FirstName AS [First Name],
LastName AS [Last Name],
TrainDate AS [Training Date], Count(*) AS TotalCount
FROM
ACJATTENDANCE
GROUP BY ID, FirstName, LastName, TrainDate, TrainDate
Why didn't my modification work the same way?
Because you group by ID, which (if it's a proper ID) is unique, meaning that every group will have a size of 1
Let's look at an artificial example:
Animals
ID, Type
1, Cat
2, Cat
3, Cat
4, Cat
5, Dog
6, Dog
4 cats, 2 dogs.
SELECT Type, COUNT(*) FROM Animals GROUP BY Type
Cat, 4
Dog, 2
In your mind, imagine a bucket with "Cat" written on and another with "Dog" written on. Write the rows out on individual sheets of paper and put them into the buckets. That's what the grouping does; you'll end up with 4 sheets of paper in the cat bucket and 2 in the dog bucket. There is one bucket per unique value: cat is one value, dog is another = 2 buckets
Now if you group by ID, you need one bucket for every unique value. That's 6 buckets, numbered 1 to 6, with one piece of paper in each
If you have multiple clauses in a group by, you end up with as many buckets as there are combinations of unique values:
Animals
ID, Type, Neutered/Spayed
1, Cat, Yes
2, Cat, No
3, Cat, Yes
4, Cat, No
5, Dog, Yes
6, Dog, Yes
SELECT Type, Neutered, COUNT(*) GROUP BY Type, Neutered
Cat, Yes, 2
Cat, No, 2
Dog, Yes, 2
GROUP BY has generated 3 buckets this time with 2 papers in each, because some cats have been neutered and some have not, but all the dogs have been neutered. There is no "Dog/No" grouping because none of the rows have this combination.
Thus, the number of groups you get is the number of distinct combinations of the column data specified in the group by. When you specify an ID, which is unique for every row, it doesn't matter what other things you group by - you will always only ever get a group size of 1 if you group by a column that is unique
Related
Let's say if I have a table that contains Equipment IDs of equipments for each Equipment Type and Equipment Age, how can I do a Count Distinct of Equipment IDs that have at least that Equipment Age.
For example, let's say this is all the data we have:
equipment_type
equipment_id
equipment_age
Screwdriver
A123
1
Screwdriver
A234
2
Screwdriver
A345
2
Screwdriver
A456
2
Screwdriver
A567
3
I would like the output to be:
equipment_type
equipment_age
count_of_equipment_at_least_this_age
Screwdriver
1
5
Screwdriver
2
4
Screwdriver
3
1
Reason is there are 5 screwdrivers that are at least 1 day old, 4 screwdrivers at least 2 days old and only 1 screwdriver at least 3 days old.
So far I was only able to do count of equipments that falls within each equipment_age (like this query shown below), but not "at least that equipment_age".
SELECT
equipment_type,
equipment_age,
COUNT(DISTINCT equipment_id) as count_of_equipments
FROM equipment_table
GROUP BY 1, 2
Consider below join-less solution
select distinct
equipment_type,
equipment_age,
count(*) over equipment_at_least_this_age as count_of_equipment_at_least_this_age
from equipment_table
window equipment_at_least_this_age as (
partition by equipment_type
order by equipment_age
range between current row and unbounded following
)
if applied to sample data in your question - output is
Use a self join approach:
SELECT
e1.equipment_type,
e1.equipment_age,
COUNT(*) AS count_of_equipments
FROM equipment_table e1
INNER JOIN equipment_table e2
ON e2.equipment_type = e1.equipment_type AND
e2.equipment_age >= e1.equipment_age
GROUP BY 1, 2
ORDER BY 1, 2;
GROUP BY restricts the scope of COUNT to the rows in the group, i.e. it will not let you reach other rows (rows with equipment_age greater than that of the current group). So you need a subquery or windowing functions to get those. One way:
SELECT
equipment_type,
equipment_age,
(Select COUNT(*)
from equipment_table cnt
where cnt.equipment_type = a.equipment_type
AND cnt.equipment_age >= a.equipment_age
) as count_of_equipments
FROM equipment_table a
GROUP BY 1, 2, 3
I am not sure if your environment supports this syntax, though. If not, let us know we will find another way.
This question already has answers here:
What's the SQL query to list all rows that have 2 column sub-rows as duplicates?
(10 answers)
Closed last year.
Suppose I have the following schema:
student(name, siblings)
The related table has names and siblings. Note the number of rows of the same name will appear the same number of times as the number of siblings an individual has. For instance, a table could be as follows:
Jack, Lucy
Jack, Tim
Meaning that Jack has Lucy and Tim as his siblings.
I want to identify an SQL query that reports the names of all students who have 2 or more siblings. My attempt is the following:
select name
from student
where count(name) >= 1;
I'm not sure I'm using count correctly in this SQL query. Can someone please help with identifying the correct SQL query for this?
You're almost there:
select name
from student
group by name
having count(*) > 1;
HAVING is a where clause that runs after grouping is done. In it you can use things that a grouping would make available (like counts and aggregations). By grouping on the name and counting (filtering for >1, if you want two or more, not >=1 because that would include 1) you get the names you want..
This will just deliver "Jack" as a single result (in the example data from the question). If you then want all the detail, like who Jack's siblings are, you can join your grouped, filtered list of names back to the table:
select *
from
student
INNER JOIN
(
select name
from student
group by name
having count(*) > 1
) morethanone ON morethanone.name = student.name
You can't avoid doing this "joining back" because the grouping has thrown the detail away in order to create the group. The only way to get the detail back is to take the name list the group gave you and use it to filter the original detail data again
Full disclosure; it's a bit of a lie to say "can't avoid doing this": SQL Server supports something called a window function, which will effectively perform a grouping in the background and join it back to the detail. Such a query would look like:
select student.*, count(*) over(partition by name) n
from student
And for a table like this:
jack, lucy
jack, tim
jane, bill
jane, fred
jane, tom
john, dave
It would produce:
jack, lucy, 2
jack, tim, 2
jane, bill, 3
jane, fred, 3
jane, tom, 3
john, dave, 1
The rows with jack would have 2 on because there are two jack rows. There are 3 janes, there is 1 john. You could then wrap all that in a subquery and filter for n > 1 which would remove john
select *
from
(
select student.*, count(*) over(partition by name) n
from student
) x
where x.n > 1
If SQL Server didn't have window functions, it would look more like:
select *
from
student
INNER JOIN
(
select name, count(*) as n
from student
group by name
) x ON x.name = student.name
The COUNT(*) OVER(PARTITION BY name) is like a mini "group by name and return the count, then auto join back to the main detail using the name as key" i.e. a short form of the latter query
You can do:
select name
from student as s1
where exists (
select s2
from student as s2
where s1.name = s2.name and s1.siblings != s2.siblings
)
I think the best approach is what 'Caius Jard' mentioned. However, additional way if you want to get how many siblings each name has .
SELECT name, COUNT(*) AS Occurrences
FROM student
GROUP BY name
HAVING (COUNT(*) > 1)
I wanted to share another solution I came up with:
select s1.name
from student s1, student s2
where s1.name = s2.name and s1.sibling != s2.sibling;
I am confused how to count items that are the same but have different formatting. E.g we want to know how many different fruits people have and have the following data:
Mary|Apple|
Mary|apple|
Mary|Apple |
Mary|Orange|
Liu|Grape|
Liu|Apple|
I expect the output
Mary|2
Liu|2
But if I do count(distinct fruits) then I get
Mary|4
Liu|2
If there any way to deal with formatting in this case?
You could count them:
Removing initial and trailing spaces - use TRIM().
Removing the letter case - use LOWER().
As in:
select
name,
count(distinct lower(trim(fruits)))
from my_table
group by name
You could use the same strategy with the name column if it happens to have similar irregularities.
Take the distinct count of the lowercase version of the fruit names:
SELECT
name,
COUNT(DISTINCT LOWER(TRIM(fruit))) AS cnt
FROM yourTable
GROUP BY
name;
Demo
The demo is in MySQL, but the same logic should work in SQLite.
DISTINCT is not the only tool here. You can use GROUP BY with a normalized version of the column text to combine all the different casings and trailing spaces into one. For example:
SELECT name, fruit, count(fruit) AS cnt
FROM test
GROUP BY name, trim(upper(fruit));
gives me
name fruit cnt
---------- ---------- ----------
Liu Apple 1
Liu Grape 1
Mary Apple 3
Mary Orange 1
However, it looks like you want the total number of different types of fruit per person. So...
WITH totals(name, fruit) AS
(SELECT name, fruit
FROM test
GROUP BY name, trim(upper(fruit)))
SELECT name, count(fruit) AS fruits
FROM totals
GROUP BY name;
gives me
name fruits
---------- ----------
Liu 2
Mary 2
I would like to ignore some of the results of my query as for all intents and purposes, some of the results are a duplicate, but based on the way the request was made, we need to use this hierarchy and although we are seeing different 'Company_Name' 's, we need to ignore one of the results.
Query:
SELECT
COUNT(DISTINCT A12.Company_name) AS Customer_Name_Count,
Company_Name,
SUM(Total_Sales) AS Total_Sales
FROM
some_table AS A12
GROUP BY
2
ORDER BY
3 ASC, 2 ASC
This code omits half a doze joins and where statements that are not germane to this question.
Results:
Customer_Name_Count Company_Name Total_Sales
-------------------------------------------------------------
1 3 Blockbuster 1,000
2 6 Jimmy's Bar 1,500
3 6 Jimmy's Restaurant 1,500
4 9 Impala Hotel 2,000
5 12 Sports Drink 2,500
In the above set, we can see that numbers 2 & 3 have the same count and the same total_sales number and similar company names. Is there a way to create a case statement that takes these 3 factors into consideration and then drops one or the other for Jimmy's enterprises? The other issue is that this has to be variable as there are other instances where this happens. And I would only want this to happen if the count and sales number match each other with a similar name in the company name.
Desired result:
Customer_Name_Count Company_Name Total_Sales
--------------------------------------------------------------
1 3 Blockbuster 1,000
2 6 Jimmy's Bar 1,500
3 9 Impala Hotel 2,000
4 12 Sports Drink 2,500
Looks like other answers are accurate based on assumption that Company_IDs are the same for both.
If Company_IDs are different for both Jimmy's Bar and Jimmy's Restaurant then you can use something like this. I suggest you get functional users involved and do some data clean-up else you'll be maintaining this every time this issue arise:
SELECT
COUNT(DISTINCT CASE
WHEN A12.Company_Name = 'Name2' THEN 'Name1'
ELSE A12.Company_Name
END) AS Customer_Name_Count
,CASE
WHEN A12.Company_Name = 'Name2' THEN 'Name1'
ELSE A12.Company_Name
END AS Company_Name
,SUM(A12.Total_Sales) AS Total_Sales
FROM some_table er
GROUP BY CASE
WHEN A12.Company_Name = 'Name2' THEN 'Name1'
ELSE A12.Company_Name
END
Your problem is that the joins you are using are multiplying the number of rows. Somewhere along the way, multiple names are associated with exactly the same entity (which is why the numbers are the same). You can fix this by aggregating by the right id:
SELECT COUNT(DISTINCT A12.Company_name) AS Customer_Name_Count,
MAX(Company_Name) as Company_Name,
SUM(Total_Sales) AS Total_Sales
FROM some_table AS A12
GROUP BY Company_id -- I'm guessing the column is something like this
ORDER BY 3 ASC, 2 ASC;
This might actually overstate the sales (I don't know). Better would be fixing the join so it only returned one name. One possibility is that it is a type-2 dimension, meaning that there is a time component for values that change over time. You may need to restrict the join to a single time period.
You need to have function to return a common name for the companies and then use DISTINCT:
SELECT DISTINCT
Customer_Name_Count,
dbo.GetCommonName(Company_Name) as Company_Name,
Total_Sales
FROM dbo.theTable
You can try to use ROW_NUMBER with window function to make row number by Customer_Name_Count and Total_Sales then get rn = 1
SELECT * FROM (
SELECT *,ROW_NUMBER() OVER(PARTITION BY Customer_Name_Count,Total_Sales ORDER BY Company_Name) rn
FROM (
SELECT
COUNT(DISTINCT A12.Company_name) AS Customer_Name_Count,
Company_Name,
SUM(Total_Sales) AS Total_Sales
FROM
some_table AS A12
GROUP BY
Company_Name
)t1
)t1
WHERE rn = 1
What is the difference between the two SQL queries below other than Query2 returning an additional field? Are there any possible scenarios where the output of the two queries would be different (other than the additional field in Query2)
Query1:
SELECT Field1, COUNT(*)
FROM Table1
GROUP BY Field1
HAVING COUNT(*) > 1
Query2:
SELECT Field1, Field2, COUNT(*)
FROM Table1
GROUP BY Field1, Field2
HAVING COUNT(*) > 1
Absolutely, these are different. Query2's Group By clause specifies an extra field. That means when the results are aggregated, they will be aggregated for the combined unique values of Field1 AND Field2. That is, two records are aggregated if and only if both Field1 and Field2 are equal.
For example:
SELECT Profession, Count(*)
FROM People
GROUP BY Profession
HAVING Count(*) > 1
will return a list of professions with associated counts like:
Software Developer, 10
PM, 5
Tester, 2
whereas:
SELECT Profession, Gender, Count(*)
FROM People
GROUP BY Profession, Gender
HAVING Count(*) > 1
will return a list of professions broken out by gender like:
Software Developer, Male, 5
Sofware Developer, Female, 5
PM, Male, 3
PM, Female, 2
Tester, Male, 2
Edit with additional requested information:
You can retrieve counts of professions with rows for both genders via:
SELECT Profession, Count(*)
FROM People
GROUP BY Profession
HAVING SUM(case Gender when 'Female' then 1 else 0 end) > 0 AND SUM(case Gender when 'Male' then 1 else 0 end) > 0
It gets a bit hairy (need subqueries) if you also need associated gender counts
Extra group by clause in query 2 filters records.To know more look at below example.
test data:
id name
1 a
2 b
3 a
4 a
So when I say group by name,sql first filters out distinct records for name which goes like below for the below query
select name,sum(id)
from test
group by name
--first filter out distinct values for group by column (here name)
a
b
--next for each distinct record ,how many values fall into that category..
a 1 a
4 a
3 a
b 2 b
So from the above groups ,now you can calculate any aggregations on the group in our case,it is sum,so next output will go some thing like this
a 8
b 2
As you can see from above output,you also can calculate,any aggregation on group (here a and b values) ,like give me count(id),len(name) on group like below
select name,len(name),sum(id)
from test
group by name
The same thing happens when you group by another field,lets say like below
select id,name
from
test
group by id,name
so in above case,sql first filters alldistinct records for id,name
1 a
2 b
3 a
4 a
next step is to get records which fall for each group
groupby columns --columns which fall into this
1 a 1 a
2 b 2 b
3 a 3 a
4 a 4 a
Now you can calculate aggergations on above groups.hope this helps in visualizing your group by.further having will eliminate groups after group by phase,where will eliminate record before group by phase