I have table with the following columns (product ID, product group code, product category)
I only want to pull the data if there there are two or more unique product category data within each product group. for example I have the following data.
Product id | product group code | product category
1 | a | Apple
2 | a | Orange
3 | a | Apple
4 | b | Toys
5 | b | Toys
I only want to see all the unique product category for each product code. The output i want to see is:
Product id product group code product category
1 | a | Apple
2 | a | Orange
3 | a | Apple
Thanks
I only want to pull the data if there there are two or more unique product category data within each product group. for example I have the following data.
This answer is based on the results you show which is consistent. The paragraph before the results is unclear.
One method is exists:
select t.*
from t
where exists (select 1
from t t2
where t2.product_group = t.product_group and
t2.product_category <> t.product_category
);
How about two nested selects? one grouping and selecting the group that has more than one in COUNT DISTINCT product_group_id, then join the "good group" back to the original input?
WITH
-- your input as an in-line table
input(Product_id,product_group_code,product_category) AS (
SELECT 1,'a','Apple'
UNION ALL SELECT 2,'a','Orange'
UNION ALL SELECT 3,'a','Apple'
UNION ALL SELECT 4,'b','Toys'
UNION ALL SELECT 5,'b','Toys'
)
,
good_grp AS (
SELECT
product_group_code
FROM input
GROUP BY product_group_code
HAVING COUNT(DISTINCT product_category) >1
)
SELECT
i.*
FROM input i
JOIN good_grp USING(product_group_code)
ORDER BY 1
-- returning ...
Product_id | product_group_code | product_category
-----------+--------------------+------------------
1 | a | Apple
2 | a | Orange
3 | a | Apple
I tried to search posts, but I only found solutions for SQL Server/Access. I need a solution in MySQL (5.X).
I have a table (called history) with 3 columns: hostid, itemname, itemvalue.
If I do a select (select * from history), it will return
+--------+----------+-----------+
| hostid | itemname | itemvalue |
+--------+----------+-----------+
| 1 | A | 10 |
+--------+----------+-----------+
| 1 | B | 3 |
+--------+----------+-----------+
| 2 | A | 9 |
+--------+----------+-----------+
| 2 | C | 40 |
+--------+----------+-----------+
How do I query the database to return something like
+--------+------+-----+-----+
| hostid | A | B | C |
+--------+------+-----+-----+
| 1 | 10 | 3 | 0 |
+--------+------+-----+-----+
| 2 | 9 | 0 | 40 |
+--------+------+-----+-----+
I'm going to add a somewhat longer and more detailed explanation of the steps to take to solve this problem. I apologize if it's too long.
I'll start out with the base you've given and use it to define a couple of terms that I'll use for the rest of this post. This will be the base table:
select * from history;
+--------+----------+-----------+
| hostid | itemname | itemvalue |
+--------+----------+-----------+
| 1 | A | 10 |
| 1 | B | 3 |
| 2 | A | 9 |
| 2 | C | 40 |
+--------+----------+-----------+
This will be our goal, the pretty pivot table:
select * from history_itemvalue_pivot;
+--------+------+------+------+
| hostid | A | B | C |
+--------+------+------+------+
| 1 | 10 | 3 | 0 |
| 2 | 9 | 0 | 40 |
+--------+------+------+------+
Values in the history.hostid column will become y-values in the pivot table. Values in the history.itemname column will become x-values (for obvious reasons).
When I have to solve the problem of creating a pivot table, I tackle it using a three-step process (with an optional fourth step):
select the columns of interest, i.e. y-values and x-values
extend the base table with extra columns -- one for each x-value
group and aggregate the extended table -- one group for each y-value
(optional) prettify the aggregated table
Let's apply these steps to your problem and see what we get:
Step 1: select columns of interest. In the desired result, hostid provides the y-values and itemname provides the x-values.
Step 2: extend the base table with extra columns. We typically need one column per x-value. Recall that our x-value column is itemname:
create view history_extended as (
select
history.*,
case when itemname = "A" then itemvalue end as A,
case when itemname = "B" then itemvalue end as B,
case when itemname = "C" then itemvalue end as C
from history
);
select * from history_extended;
+--------+----------+-----------+------+------+------+
| hostid | itemname | itemvalue | A | B | C |
+--------+----------+-----------+------+------+------+
| 1 | A | 10 | 10 | NULL | NULL |
| 1 | B | 3 | NULL | 3 | NULL |
| 2 | A | 9 | 9 | NULL | NULL |
| 2 | C | 40 | NULL | NULL | 40 |
+--------+----------+-----------+------+------+------+
Note that we didn't change the number of rows -- we just added extra columns. Also note the pattern of NULLs -- a row with itemname = "A" has a non-null value for new column A, and null values for the other new columns.
Step 3: group and aggregate the extended table. We need to group by hostid, since it provides the y-values:
create view history_itemvalue_pivot as (
select
hostid,
sum(A) as A,
sum(B) as B,
sum(C) as C
from history_extended
group by hostid
);
select * from history_itemvalue_pivot;
+--------+------+------+------+
| hostid | A | B | C |
+--------+------+------+------+
| 1 | 10 | 3 | NULL |
| 2 | 9 | NULL | 40 |
+--------+------+------+------+
(Note that we now have one row per y-value.) Okay, we're almost there! We just need to get rid of those ugly NULLs.
Step 4: prettify. We're just going to replace any null values with zeroes so the result set is nicer to look at:
create view history_itemvalue_pivot_pretty as (
select
hostid,
coalesce(A, 0) as A,
coalesce(B, 0) as B,
coalesce(C, 0) as C
from history_itemvalue_pivot
);
select * from history_itemvalue_pivot_pretty;
+--------+------+------+------+
| hostid | A | B | C |
+--------+------+------+------+
| 1 | 10 | 3 | 0 |
| 2 | 9 | 0 | 40 |
+--------+------+------+------+
And we're done -- we've built a nice, pretty pivot table using MySQL.
Considerations when applying this procedure:
what value to use in the extra columns. I used itemvalue in this example
what "neutral" value to use in the extra columns. I used NULL, but it could also be 0 or "", depending on your exact situation
what aggregate function to use when grouping. I used sum, but count and max are also often used (max is often used when building one-row "objects" that had been spread across many rows)
using multiple columns for y-values. This solution isn't limited to using a single column for the y-values -- just plug the extra columns into the group by clause (and don't forget to select them)
Known limitations:
this solution doesn't allow n columns in the pivot table -- each pivot column needs to be manually added when extending the base table. So for 5 or 10 x-values, this solution is nice. For 100, not so nice. There are some solutions with stored procedures generating a query, but they're ugly and difficult to get right. I currently don't know of a good way to solve this problem when the pivot table needs to have lots of columns.
SELECT
hostid,
sum( if( itemname = 'A', itemvalue, 0 ) ) AS A,
sum( if( itemname = 'B', itemvalue, 0 ) ) AS B,
sum( if( itemname = 'C', itemvalue, 0 ) ) AS C
FROM
bob
GROUP BY
hostid;
Another option,especially useful if you have many items you need to pivot is to let mysql build the query for you:
SELECT
GROUP_CONCAT(DISTINCT
CONCAT(
'ifnull(SUM(case when itemname = ''',
itemname,
''' then itemvalue end),0) AS `',
itemname, '`'
)
) INTO #sql
FROM
history;
SET #sql = CONCAT('SELECT hostid, ', #sql, '
FROM history
GROUP BY hostid');
PREPARE stmt FROM #sql;
EXECUTE stmt;
DEALLOCATE PREPARE stmt;
FIDDLE
Added some extra values to see it working
GROUP_CONCAT has a default value of 1000 so if you have a really big query change this parameter before running it
SET SESSION group_concat_max_len = 1000000;
Test:
DROP TABLE IF EXISTS history;
CREATE TABLE history
(hostid INT,
itemname VARCHAR(5),
itemvalue INT);
INSERT INTO history VALUES(1,'A',10),(1,'B',3),(2,'A',9),
(2,'C',40),(2,'D',5),
(3,'A',14),(3,'B',67),(3,'D',8);
hostid A B C D
1 10 3 0 0
2 9 0 40 5
3 14 67 0 8
Taking advantage of Matt Fenwick's idea that helped me to solve the problem (a lot of thanks), let's reduce it to only one query:
select
history.*,
coalesce(sum(case when itemname = "A" then itemvalue end), 0) as A,
coalesce(sum(case when itemname = "B" then itemvalue end), 0) as B,
coalesce(sum(case when itemname = "C" then itemvalue end), 0) as C
from history
group by hostid
I edit Agung Sagita's answer from subquery to join.
I'm not sure about how much difference between this 2 way, but just for another reference.
SELECT hostid, T2.VALUE AS A, T3.VALUE AS B, T4.VALUE AS C
FROM TableTest AS T1
LEFT JOIN TableTest T2 ON T2.hostid=T1.hostid AND T2.ITEMNAME='A'
LEFT JOIN TableTest T3 ON T3.hostid=T1.hostid AND T3.ITEMNAME='B'
LEFT JOIN TableTest T4 ON T4.hostid=T1.hostid AND T4.ITEMNAME='C'
use subquery
SELECT hostid,
(SELECT VALUE FROM TableTest WHERE ITEMNAME='A' AND hostid = t1.hostid) AS A,
(SELECT VALUE FROM TableTest WHERE ITEMNAME='B' AND hostid = t1.hostid) AS B,
(SELECT VALUE FROM TableTest WHERE ITEMNAME='C' AND hostid = t1.hostid) AS C
FROM TableTest AS T1
GROUP BY hostid
but it will be a problem if sub query resulting more than a row, use further aggregate function in the subquery
If you could use MariaDB there is a very very easy solution.
Since MariaDB-10.02 there has been added a new storage engine called CONNECT that can help us to convert the results of another query or table into a pivot table, just like what you want:
You can have a look at the docs.
First of all install the connect storage engine.
Now the pivot column of our table is itemname and the data for each item is located in itemvalue column, so we can have the result pivot table using this query:
create table pivot_table
engine=connect table_type=pivot tabname=history
option_list='PivotCol=itemname,FncCol=itemvalue';
Now we can select what we want from the pivot_table:
select * from pivot_table
More details here
My solution :
select h.hostid, sum(ifnull(h.A,0)) as A, sum(ifnull(h.B,0)) as B, sum(ifnull(h.C,0)) as C from (
select
hostid,
case when itemName = 'A' then itemvalue end as A,
case when itemName = 'B' then itemvalue end as B,
case when itemName = 'C' then itemvalue end as C
from history
) h group by hostid
It produces the expected results in the submitted case.
I make that into Group By hostId then it will show only first row with values,
like:
A B C
1 10
2 3
I figure out one way to make my reports converting rows to columns almost dynamic using simple querys. You can see and test it online here.
The number of columns of query is fixed but the values are dynamic and based on values of rows. You can build it So, I use one query to build the table header and another one to see the values:
SELECT distinct concat('<th>',itemname,'</th>') as column_name_table_header FROM history order by 1;
SELECT
hostid
,(case when itemname = (select distinct itemname from history a order by 1 limit 0,1) then itemvalue else '' end) as col1
,(case when itemname = (select distinct itemname from history a order by 1 limit 1,1) then itemvalue else '' end) as col2
,(case when itemname = (select distinct itemname from history a order by 1 limit 2,1) then itemvalue else '' end) as col3
,(case when itemname = (select distinct itemname from history a order by 1 limit 3,1) then itemvalue else '' end) as col4
FROM history order by 1;
You can summarize it, too:
SELECT
hostid
,sum(case when itemname = (select distinct itemname from history a order by 1 limit 0,1) then itemvalue end) as A
,sum(case when itemname = (select distinct itemname from history a order by 1 limit 1,1) then itemvalue end) as B
,sum(case when itemname = (select distinct itemname from history a order by 1 limit 2,1) then itemvalue end) as C
FROM history group by hostid order by 1;
+--------+------+------+------+
| hostid | A | B | C |
+--------+------+------+------+
| 1 | 10 | 3 | NULL |
| 2 | 9 | NULL | 40 |
+--------+------+------+------+
Results of RexTester:
http://rextester.com/ZSWKS28923
For one real example of use, this report bellow show in columns the hours of departures arrivals of boat/bus with a visual schedule. You will see one additional column not used at the last col without confuse the visualization:
** ticketing system to of sell ticket online and presential
This isn't the exact answer you are looking for but it was a solution that i needed on my project and hope this helps someone. This will list 1 to n row items separated by commas. Group_Concat makes this possible in MySQL.
select
cemetery.cemetery_id as "Cemetery_ID",
GROUP_CONCAT(distinct(names.name)) as "Cemetery_Name",
cemetery.latitude as Latitude,
cemetery.longitude as Longitude,
c.Contact_Info,
d.Direction_Type,
d.Directions
from cemetery
left join cemetery_names on cemetery.cemetery_id = cemetery_names.cemetery_id
left join names on cemetery_names.name_id = names.name_id
left join cemetery_contact on cemetery.cemetery_id = cemetery_contact.cemetery_id
left join
(
select
cemetery_contact.cemetery_id as cID,
group_concat(contacts.name, char(32), phone.number) as Contact_Info
from cemetery_contact
left join contacts on cemetery_contact.contact_id = contacts.contact_id
left join phone on cemetery_contact.contact_id = phone.contact_id
group by cID
)
as c on c.cID = cemetery.cemetery_id
left join
(
select
cemetery_id as dID,
group_concat(direction_type.direction_type) as Direction_Type,
group_concat(directions.value , char(13), char(9)) as Directions
from directions
left join direction_type on directions.type = direction_type.direction_type_id
group by dID
)
as d on d.dID = cemetery.cemetery_id
group by Cemetery_ID
This cemetery has two common names so the names are listed in different rows connected by a single id but two name ids and the query produces something like this
CemeteryID Cemetery_Name Latitude
1 Appleton,Sulpher Springs 35.4276242832293
You can use a couple of LEFT JOINs. Kindly use this code
SELECT t.hostid,
COALESCE(t1.itemvalue, 0) A,
COALESCE(t2.itemvalue, 0) B,
COALESCE(t3.itemvalue, 0) C
FROM history t
LEFT JOIN history t1
ON t1.hostid = t.hostid
AND t1.itemname = 'A'
LEFT JOIN history t2
ON t2.hostid = t.hostid
AND t2.itemname = 'B'
LEFT JOIN history t3
ON t3.hostid = t.hostid
AND t3.itemname = 'C'
GROUP BY t.hostid
I'm sorry to say this and maybe I'm not solving your problem exactly but PostgreSQL is 10 years older than MySQL and is extremely advanced compared to MySQL and there's many ways to achieve this easily. Install PostgreSQL and execute this query
CREATE EXTENSION tablefunc;
then voila! And here's extensive documentation: PostgreSQL: Documentation: 9.1: tablefunc or this query
CREATE EXTENSION hstore;
then again voila! PostgreSQL: Documentation: 9.0: hstore
I solemnly swear I did my best to find an existing question, may I'm not sure how to phrase it correctly.
I would like to return records for users that have quota for only one product type.
| user_id | product |
| 1 | A |
| 1 | B |
| 1 | C |
| 2 | B |
| 3 | B |
| 3 | C |
| 3 | D |
In the example above I'd like a query that only returns users who carry quota for only one product type - doesn't really matter which product at this point.
I tried using select user_id, product from table group by 1,2 having count(user) < 2 but this does not work, nor does select user_id, product from table group by 1,2 having count(*) < 2
Any help is appreciated.
Your having clause is good; the issue's with your group by. Try this:
select user_id
, count(distinct product) NumberOfProducts
from table
group by user_id
having count(distinct product) = 1
Or you could do this; which is closer to your original:
select user_id
from table
group by user_id
having count(*) < 2
The group by clause can't take ordinal arguments (like, e.g., the order by clause can). When grouping by a value like 1, you're in fact grouping by the literal value 1, which would just be the same for any row in the table, and thus will group all the rows in the table to one group. Since there are more than one product in the entire table, no rows will be returned.
Instead, you should group by the user_id:
SELECT user_id
FROM mytable
GROUP BY user_id
HAVING COUNT(*) = 1
If you want the product, then do:
select user_id, max(product) as product
from table
group by user_id
having min(product) = max(product);
The having clause could also be:
having count(distinct product) = 1
Closed. This question needs debugging details. It is not currently accepting answers.
Edit the question to include desired behavior, a specific problem or error, and the shortest code necessary to reproduce the problem. This will help others answer the question.
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Suppose I have a Table such that:
|ID | product |orderid | brand |number of product cust ord|
|----|---------|--------|-------|--------------------------|
| 1 | 123 | 111 | br | 1 |
|----|---------|--------|-------|--------------------------|
| 1 | 234 | 111 | br | 1 |
|----|---------|--------|-------|--------------------------|
| 1 | 345 | 333 | br | 1 |
|----|---------|--------|-------|--------------------------|
| 2 | 123 | 211 | br | 1 |
|----|---------|--------|-------|--------------------------|
| 2 | 456 | 212 | br | 2 |
|----|---------|--------|-------|--------------------------|
| 3 | 567 | 213 | br | 1 |
|----|---------|--------|-------|--------------------------|
What I'd like to do is group them as:
|ID | brand |number of product cust ord|
|----|---------|--------------------------|
| 1 | br | 3 |
|----|---------|--------------------------|
| 2 | br | 4 |
|----|---------|--------------------------|
further to that i'd like to classify them and tried a case...when but can't seem to get it right.
if ID purchases more than 3 unique products and orders more than twice- i'd like to call them a frequent buyer (in the above example, ID '1' would be a 'frequent buyer'), if the average number of products they purchase is higher than the average number of that product sold - i'd like to call them a 'merchant', else just a purchaser.
I've renamed the last field to qty for brevity and called the table test1.
To get frequent flyers use below query. Note that I used >= instead of >. I changed this based on your example where ID 1 is a "frequent flyer" even though he only bought 3 products, not more than 3.
SELECT ID, count(distinct product) as DistinctProducts, count(distinct orderid) DistinctOrders
FROM test1
GROUP BY ID
HAVING count(distinct product) >= 3 and count(distinct orderid) >= 2
Not sure if I understood the merchant logic correctly. Below is the query which will give you customers that on average purchased more than overall average of product for any given product. There are none in the data.
SELECT DISTINCT c.ID
FROM
(select ID, product, avg(qty) as AvgQty
FROM test1
GROUP BY ID, product) as c
FULL OUTER JOIN
(select product, avg(qty) as AvgQty
FROM test1
GROUP BY product) p ON p.product = c.product
WHERE c.AvgQty > p.AvgQty;
To get "purchasers" do EXCEPT between all customer and the UNION of merchants and frequent buyers:
select distinct ID from test1
EXCEPT
(SELECT ID FROM (
select ID, count(distinct product) as DistinctProducts, count(distinct orderid) DistinctOrders
FROM test1
GROUP BY ID
HAVING count(distinct product) >= 3 and count(distinct orderid) >= 2) t
UNION
SELECT DISTINCT c.ID
FROM
(select ID, product, avg(qty) as AvgQty
FROM test1
GROUP BY ID, product) as c
FULL OUTER JOIN
(select product, avg(qty) as AvgQty
FROM test1
GROUP BY product) p ON p.product = c.product
WHERE c.AvgQty > p.AvgQty
);
This is one way that you could do it. Note that according to the description you gave, buyers could be constantly being reclassified between 'Merchant' and 'Purchaser' as the average goes up and down. That might not be what you want.
With cte As (
Select ID,
Brand,
DistinctOrders = Count(Distinct OrderID), -- How many separate orders by this customer for the brand?
DistinctProducts = Count(Distinct Product), -- How many different products by this customer for the brand?
[number of product cust ord] = Sum(CountOfProduct), -- Total number of items by this customer for the brand.
AverageCountOfProductPerBuyer =
Sum(Sum(CountOfProduct)) Over () * 1.0 / (Select Count(*) From (Select Distinct ID, Brand From #table) As tbl)
-- Average number of items per customer (for all customers) for this brand
From #table
Group By ID, Brand)
Select ID, Brand, DistinctOrders, DistinctProducts, [number of product cust ord],
IsFrequentBuyer = iif(DistinctOrders > 1 And DistinctProducts > 2, 'Frequent Buyer', NULL),
IsMerchant = iif(AverageCountOfProductPerBuyer < [number of product cust ord], 'Merchant', 'Purchaser')
From cte;
This query could be written without the common-table expression, but was written this way to avoid defining expressions multiple times.
Note that I have the first ID as a 'Frequent Buyer' based on your description, so I'm assuming that when you say 'more than 3 unique products' you mean 3 or more. Likewise with two or more distinct orders.
Each row in my table belongs to some category, has some value and other data.
I would like to select each category with the most common value for it (doesn't matter which one if there are multiple), ordered by category.
some_table: expected result:
+--------+-----+--- +--------+-----+
|category|value|... |category|value|
+--------+-----+--- +--------+-----+
| 1 | a | | 1 | a |
| 1 | a | | 2 | b |
| 1 | b | | 3 | a # or b
| 2 | a | +--------+-----+
| 2 | b |
| 2 | c |
| 2 | b |
| 3 | a |
| 3 | a |
| 3 | b |
| 3 | b |
+--------+-----+---
I have a solution (posting it as an answer) but it seems suboptimal to me. So I'm looking for better solutions.
My table will have up to 10000 rows (possibly, but not likely, beyond that).
I'm planning to use SQLite but I'm not tied to it, so I may reconsider if SQLite can't do this with reasonable performance.
I would be inclined to do this using a correlated subquery:
select distinct category,
(select value
from some_table t2
where t2.category = t.category
group by value
order by count(*) desc
limit 1
) as mode_value
from some_table t;
The name for the most common value is "mode" in statistics.
And, if you had a categories table, this would be written as:
select category,
(select value
from some_table t2
where t2.category = c.category
group by value
order by count(*) desc
limit 1
) as mode_value
from categories c;
Here is one option, but I think it's slow...
SELECT DISTINCT `category` AS `the_category`, `value`
FROM `some_table`
WHERE `value`=(
SELECT `value`
FROM `some_table`
WHERE `category`=`the_category`
GROUP BY `value`
ORDER BY COUNT(`value`) DESC LIMIT 1)
ORDER BY `category`;
You can replace a part of this with WHERE `id`=( SELECT `id` if the table has a unique/primary key column, then the LIMIT 1 is not needed.
select category, value, count(*) value_count
from some_table t
group by category, value
order by category, value_count DESC;
returns us amout of each value in each category
select category, value
from (
select category, value, count(*) value_count
from some_table t
group by category, value) sub
group by category
actually we need the first value because it's sorted.
I am not sure sqlite leaves the first one and can't test but IMHO it should work