I want to select the total number of appearance of a single player in two other tables.
Here is my database structure (postgres):
Table: Player
id integer
Table: World Champions
id integer
year date
player_id integer
Table: European Champions
id integer
year date
player_id integer
The id on table player is also available in table "World Champions" and "European Champions" (player_id).
I want to select the data as following:
player.id worldChampionTitles europeanChampionTitles
1 3 4
2 1 0
3 0 0
4 1 1
But I have no Idea how to write my select query for that.
Easy with subqueries:
SELECT p.id
, (SELECT count(*) FROM "World Champions" AS c WHERE c.player_id = p.id)
+ (SELECT count(*) FROM "European Champions" AS c WHERE c.player_id = p.id)
FROM Player AS p
Related
I have the following schema:
expenses
id
name, varchar
cost, double
date, DATE
category_id, int f_key
user_id, int f_key
1
Pizza
22.9
22/08/2022
1
1
2
Pool
34.9
23/08/2022
2
1
categories
id
name, varchar
1
Food
2
Leisure
3
Medicine
4
Fancy food
users_categories(user_id int foreign key, category_id foreign key)
user_id int f_key
category_id int f_key
1
1
1
2
1
3
2
4
And two users with id 1 and 2.
Relation between user and category is many to many.
Problem:
I want to get statistics (total cost amount and count) for all categories. For categories where there are no expenses I want to return 0. Here is my query:
SELECT categories.name as name, count(expenses.name) as count, round(SUM(price)::numeric,2) as sum
FROM expenses
Right JOIN categories ON expenses.category_id = categories.id
and expenses.category_id in (
select users_categories.category_id from users_categories where users_categories.user_id = 1
)
and expenses.id in(
Select expenses.id from expenses
join users_categories on expenses.category_id = users_categories.category_id
and expenses.user_id = 1
AND (extract(year from date) = 2022 OR CAST(2022 AS int) is null)
AND (extract(month from date) = 8 OR CAST(8 AS int) is null)
)
GROUP BY categories.id ORDER BY categories.id
The response is:
name
count
sum
Food
1
22.9
Leisure
1
33.9
Medicine
0
null
Fancy food
0
null
How I should edit my query to eliminate the last row, because this category doesn't belong to the user 1.
In your query you used user_categories as subquery so it will not filter category ids,
Try this Query
SELECT categories.name as name,count(expenses.name) as count, coalesce(round(SUM(price)::numeric,2),0) as sum from
categories
left join users_categories on users_categories.category_id= categories.id
left join expenses ON expenses.category_id = categories.id
AND (extract(year from date) = 2022 OR CAST(2022 AS int) is null)
AND (extract(month from date) = 8 OR CAST(8 AS int) is null)
where users_categories.user_id='1'
GROUP BY categories.name,categories.id ORDER BY categories.id
OUTPUT :
name count sum
Food 1 22.90
Leisure 1 34.90
Medicine 0 0
You want to move expenses.category_id in ... out of the ON condition and into a WHERE clause.
When it is in the ON clause, that means rows which were removed by the in-test just get NULL-fabricated anyway. You want to remove those rows after the NULL-fabrication is done, so that they remain removed. But why do you use that in-test anyway? Seems like it would be much simpler written as another join.
What I understand is that you are trying to get the count and sum of expenses for all the categories related to the user_id 1 within the month of august 2022.
Please try out the following query.
WITH statistics
AS (SELECT e.category_id,
Count(e.*) AS count,
Round(Sum(e.cost), 2) AS sum
FROM expenses e
WHERE e.user_id = 1
AND ( e.date BETWEEN '01/08/2022' AND '31/08/2022' )
GROUP BY e.category_id),
user_category
AS (SELECT uc.category_id,
COALESCE(s.count, 0) AS count,
COALESCE(s.sum, 0) AS sum
FROM users_categories uc
LEFT JOIN statistics s
ON uc.category_id = s.id
WHERE uc.user_id = 1)
SELECT c.NAME,
u.count,
u.sum
FROM categories c
INNER JOIN user_category u
ON u.category_id = c.id;
I use PostgreSQL 13.3
I'm trying to think how I can make include/exclude in query at the same time
I have include_system_ids [1,5] and exclude_system_ids [3]
There's one big table - records
system_records table
record
system_id
1
1
1
5
1
3
2
1
2
5
If a record contains an exclusive identifier, then it should not be included in the final selection. I had some several tries, but I didn't get a necessary result
Awaiting result: record with id 2
Fact result: 1, 2
My variants
select r.id from records r
left join (select record_id from system_records
where system_id in (1,5)
) include_ids on r.id = include_ids
left join (select record_id from system_records
where system_id not in (3)
) exclude_ids on r.id = exclude_ids.id
Honestly, I don't understand how I can do it((
Is there anyone who can help me
Maybe this query could be a solution (result here)
with x as (select record,string_agg(system_id::varchar,',') as sys_id from records group by record)
select records.*
from records,x
where records.record = x.record
and x.sys_id = '1,5'
Data
So my data looks like:
product user_id value id
pizza 1 50 1
burger 1 30 2
pizza 2 50 3
fries 1 10 4
pizza 3 50 5
burger 1 30 6
burger 2 30 7
Problem Statement
And I wanted to compute Lifetime values of customers of each product as a metric to know which product is doing great in terms of user retention.
Desired Output
My desired output is:
product
value_by_customers_of_these_products
total_customers
ltv
pizza
250
3
250/3 = 83.33
burger
200
2
200/2 = 100
fries
120
1
120/1 = 120
Columns Description:
value_by_customers_of_these_products : Total value generated by
customers of each product including orders which do not contain the
product
total_customers : Simple COUNT(DISTINCT user_id) GROUP BY product
Current Workaround
Currently I am doing this:
SELECT "pizza" AS product, SUM(value) value_by_customers_of_these_products, COUNT(DISTINCT user_id) users FROM orders WHERE user_id in (SELECT user_id FROM orders WHERE product = "pizza")
UNION ALL
SELECT "burger" AS product, SUM(value) value_by_customers_of_these_products, COUNT(DISTINCT user_id) users FROM orders WHERE user_id in (SELECT user_id FROM orders WHERE product = "burger")
UNION ALL
SELECT "fries" AS product, SUM(value) value_by_customers_of_these_products, COUNT(DISTINCT user_id) users FROM orders WHERE user_id in (SELECT user_id FROM orders WHERE product = "fries")
I have a python script obtaining DISTINCT product names from my table and then repeating the query string for each product and updating query from time to time. This is really a pain as I have to do every time a new product is launched and sky-rocketing length of query is another issue. How can I achieve this via built-in BigQuery functions or minimal headache?
Code to generate Sample Data
WITH orders as (SELECT "pizza" AS product,
1 AS user_id,
50 AS value, 1 AS id,
UNION ALL SELECT "burger", 1, 30,2
UNION ALL SELECT "pizza", 2, 50,3
UNION ALL SELECT "fries", 1, 10,4
UNION ALL SELECT "pizza", 3, 50,5
UNION ALL SELECT "burger", 1, 30, 6
UNION ALL SELECT "burger", 3, 30, 7)
Use below
with user_value as (
select user_id, sum(value) values
from `project.dataset.table`
group by user_id
), product_user as (
select distinct product, user_id
from `project.dataset.table`
)
select product,
sum(values) as value_by_customers_of_these_products,
count(user_id) as total_customers,
round(sum(values) / count(user_id), 2) as ltv
from product_user
join user_value
using(user_id)
group by product
if applied to sample data in your question - output is
I have this datatables:
table1
id category
-------------
1 a
2 b
3 c
table2
id heading category_id
----------------------
1 name 1
2 adddress 2
3 phone 3
4 email 1
I want to group this table and display the latest data for that the following query was I used:
SELECT news.id,news.image,news.heading,news.description,
news.date,news.category_id,categories.category
FROM `news`
INNER JOIN categories On news.category_id=categories.id
group by category_id
But I didnt get the latest data that I entered.
Try the query below:
SELECT *
FROM table2 AS tb2 LEFT JOIN table1 AS tb1 ON tb2.category_id = tb1.id
ORDER BY tb1.id
GROUP BY tb2.category_id
How can the results of a "group by" count be normalized by the count's sum?
For example, given:
User Rating (1-5)
----------------------
1 3
1 4
1 2
3 5
4 3
3 2
2 3
The result will be:
User Count Percentage
---------------------------
1 3 .42 (=3/7)
2 1 .14 (=1/7)
3 2 .28 (...)
4 1 .14
So for each user the number of ratings they provided is given as the percentage of the total ratings provided by everyone.
SELECT DISTINCT ON (user) user, count(*) OVER (PARTITION BY user) AS cnt,
count(*) OVER (PARTITION BY user) / count(*) OVER () AS percentage;
The count(*) OVER (PARTITION BY user) is a so-called window function. Window functions let you perform some operation over a "window" created by some "partition" which is here made over the user id. In plain and simple English: the partitioned count(*) is calculated for each distinct user value, so in effect it counts the number of rows for each user value.
Without using a windowing function or variables, you will need to cross join a grouped subquery on a second "maxed" subquery then select again to return a subset you can work with.
SELECT
B.UserID,
B.UserCount,
A.CountAll
FROM
(
SELECT
CountAll=SUM(UserCount)
FROM
(
SELECT
UserCount=COUNT(*)
FROM
MyTable
GROUP BY
UserID
) AS A
)AS C
CROSS JOIN(
SELECT
UserID,
UserCount=COUNT(*)
FROM
MyTable
GROUP BY
UserID
)AS B