I have a Users table (id, name, created_at) and a Transaction table(id, user_id, created_at, amount).
For each month, I would like to know the number of users who did not have any transaction in the 3 months interval before that month.
For example, for April 2022, the query would return number of users who did not have a transaction in January 2022, February 2022 and March 2022. And so on for every month.
Can I do this with a single MySQL query, and without PHP loop?
If I wanted it for April 2022 only, then I guess this would do the trick:
SELECT count(distinct(users.id)) FROM users
INNER JOIN transactions
on users.id = transactions.user_id
WHERE transactions.user_id NOT IN
(SELECT user_id FROM transactions WHERE created_at > "2022-01-01" AND created_at < "2022-04-01" );
How to get it for all months?
In a normal situation, you would have a calendar table that, for examples, stores all starts of months over a wide period of time, like calendar(start_of_month).
From there on, you can cross join the calendar with the users table to generate all possible combinations of months and customers (with respect to the user's creation time). The last step is to check each user/month tuple for transations in the last 3 months.
select c.start_of_month, count(*) as cnt_inactive_users
from calendar c
cross join users u
where not exists (
select 1
from transactions t
where t.user_id = u.id
and t.created_at >= c.start_of_month - interval 3 month
and t.created_at < c.start_of_month
)
where c.start_of_month >= '2021-01-01' and c.start_of_month < '2022-01-01'
group by c.start_of_month
order by c.start_of_month
This gives you one row per month that has at least one "inactive" customers,with the corresponding count.
You control the range of months over which the query applies with the where clause to the query (as an example, the above gives you all year 2021).
SELECT count(*)
FROM users
WHERE NOT EXISTS (
SELECT NULL
FROM transactions
WHERE users.id = transactions.user_id
AND created_at > '2022-01-01' AND created_at < '2022-04-01'
);
Related
So we log when we send our clients promotional emails and sometimes clients are in our database for a while before they receive their first email so we want to know how many clients received their first ever email by month for the past 12 months.
So far I can only think to get the information month by month but there has to be a way to query all 12 months in a single query.
SELECT DISTINCT
`id`
FROM
`table1`
WHERE
`sendtime` BETWEEN '2019-08-01' AND '2019-09-01'
AND `id` NOT IN (SELECT
`id`
FROM
`table1`
WHERE
`sendtime` < '2019-08-01');
Check for the minimum sendtime for each user:
SELECT id
FROM table1
GROUP BY id
HAVING MIN(sendtime) BETWEEN '2019-08-01' AND '2019-09-01'
If you want the number of these ids:
SELECT COUNT(*) counter
FROM (
SELECT id
FROM table1
GROUP BY id
HAVING MIN(sendtime) BETWEEN '2019-08-01' AND '2019-09-01'
) t
You can use two levels of aggregation:
select date_format(min_sendtime, '%Y-%m') yyyy_mm, count(*) no_clients
from (
select id, min(sendtime) min_sendtime
from table1
group by id
) t
where min_sendtime >= date_format(current_date, '%Y-%m-01') - interval 1 year
group by yyyy_mm
order by yyyy_mm
This gives you one row for each of the last twelve months (that has a least one customer that received their first email), with the count of "new" email over the month.
I have a table that stores each order made by a user, recording the date it was made , the amount and the user id. I am trying to create a query that returns the weekly transactions from Monday to Sunday for the last 12 weeks for a particular user. I am using the following query:
SELECT COUNT(*) AS Orders,
SUM(amount) AS Total,
DATE_FORMAT(transaction_date,'%m/%Y') AS Week
FROM shop_orders
WHERE user_id = 123
AND transaction_date >= now()-interval 3 month
GROUP BY YEAR(transaction_date), WEEKOFYEAR(transaction_date)
ORDER BY DATE_FORMAT(transaction_date,'%m/%Y') ASC
This produces the following result:
This however does not return the weeks where the user has made 0 orders, does not sum the orders from Monday to Sunday and does not return the weeks ordered from 1 to 12. Is there a way to achieve these things?
One way to accomplish this is with an self outer join (in this case, I use a right outer join, but of course a left outer join would work as well).
To start your weeks on Monday, subtract the result of WEEKDAY from your column transaction_date with DATE_SUB, as proposed in the most upvoted answer here.
SELECT
COALESCE(t1.Orders, 0) AS `Orders`,
COALESCE(t1.Total, 0) AS `Total`,
t2.Week AS `Week`
FROM
(
SELECT
COUNT(*) AS `Orders`,
SUM(amount) AS `Total`,
DATE(DATE_SUB(transaction_date, INTERVAL(WEEKDAY(transaction_date)) DAY)) AS `Week`
FROM
shop_orders
WHERE 1=1
AND user_id = 123
AND transaction_date >= NOW() - INTERVAL 12 WEEK
GROUP BY
3
) t1 RIGHT JOIN (
SELECT
DATE(DATE_SUB(transaction_date, INTERVAL(WEEKDAY(transaction_date)) DAY)) AS `Week`
FROM
shop_orders
WHERE
transaction_date >= NOW() - INTERVAL 12 WEEK
GROUP BY
1
ORDER BY
1
) t2 USING (Week)
To return the weeks with no Orders you have to create a table with all the weeks.
For the order order by the same fields in the group by
I have two tables: Processes and Validations; p and v respectively.
For each process there are many validations.
The aim is to:
Retrieve the latest validation for each process.
Generate a
dynamic date (Due_Date) as to when the next validation is due (being 365 days
after the latest validation date).
Filter the results to any due
dates that fall in the current month.
In short terms; I want to see what processes are due to be validated in the current month.
I'm 99% there with the query code. Having read through some posts on here I'm fairly certain I'm on the right track. My problem is that my query still returns all of the results for each process, instead of the top 1.
FYI: The processes table uses "Process_ID" as a primary key; whereas the Validations Table uses "Validation_Process_ID" as a foreign key.
Code at present :
Select p.Process_ID,
p.Process_Name,
v.Validation_Date,
Date_Add(v.Validation_Date, Interval 365 Day) as Due_Date
From processes_active p
left JOIN processes_validations v
on p.Process_ID = (select v.validation_process_id
from processes_validations
order by validation_date desc
limit 1)
Having Month(Due_Date) = Month(Now()) and Year(Due_Date) = Year(Now())
Any help would be thoroughly appreciated! I'm probably pretty close just can't sort that final section!
Thanks
Your actual query is wrong, the subquery will return the very latest record in your validation table, instead of returning the latest per process id.
You should decompose to get what you need.
1) compute the latest validation for each process in the validation table:
SELECT validation_process_id, MAX(validation_date) AS maxdate
FROM processes_validations
GROUP BY validation_process_id
2) For each process in the process table, get the latest validation, and compute the next validation date (use interval 1 YEAR and not 365 DAY... think leap years)
SELECT p.Process_ID, p.Process_Name, v.maxdate,
Date_Add(v.maxdate, Interval 1 year) as Due_Date
FROM processes_active p
LEFT JOIN
(
SELECT validation_process_id, MAX(validation_date) AS maxdate
FROM processes_validations
GROUP BY validation_process_id
)
ON p.Process_ID = v.validation_process_id
3) Filter to keep only the due_date this month. This can be done with a WHERE on query 2, I just make a nested query for your understanding
SELECT * FROM
(
SELECT p.Process_ID, p.Process_Name, v.maxdate,
Date_Add(v.maxdate, Interval 1 year) as Due_Date
FROM processes_active p
LEFT JOIN
(
SELECT validation_process_id, MAX(validation_date) AS maxdate
FROM processes_validations
GROUP BY validation_process_id
)
ON p.Process_ID = v.validation_process_id
) T
WHERE Month(Due_Date) = Month(Now()) and Year(Due_Date) = Year(Now())
I have a table, activity that looks like the following:
date | user_id |
Thousands of users and multiple dates and activity for all of them. I want to pull a query that will, for every day in the result, give me the total active users in the last 30 days. The query I have now looks like the following:
select date, count(distinct user_id) from activity where date > date_sub(date, interval 30 day) group by date
This gives me total unique users on only that day; I can't get it to give me the last 30 for each date. Help is appreciated.
To do this you need a list of the dates and join that against the activities.
As such this should do it. A sub query to get the list of dates and then a count of user_id (or you could use COUNT(*) as I presume user_id cannot be null):-
SELECT date, COUNT(user_id)
FROM
(
SELECT DISTINCT date, DATE_ADD(b.date, INTERVAL -30 DAY) AS date_minus_30
FROM activity
) date_ranges
INNER JOIN activity
ON activity.date BETWEEN date_ranges.date_minus_30 AND date_ranges.date
GROUP BY date
However if there can be multiple records for a user_id on any particular date but you only want the count of unique user_ids on a date you need to count DISTINCT user_id (although note that if a user id occurs on 2 different dates within the 30 day date range they will only be counted once):-
SELECT activity.date, COUNT(DISTINCT user_id)
FROM
(
SELECT DISTINCT date, DATE_ADD(b.date, INTERVAL -30 DAY) AS date_minus_30
FROM activity
) date_ranges
INNER JOIN activity
ON activity.date BETWEEN date_ranges.date_minus_30 AND date_ranges.date
GROUP BY date
A bit cruder would be to just join the activity table against itself based on the date range and use COUNT(DISTINCT ...) to just eliminate the duplicates:-
SELECT a.date, COUNT(DISTINCT a.user_id)
FROM activity a
INNER JOIN activity b
ON a.date BETWEEN DATE_ADD(b.date, INTERVAL -30 DAY) AND b.date
GROUP by a.date
I have 3 tables:
doctors (id, name) -> has_many:
patients (id, doctor_id, name) -> has_many:
health_conditions (id, patient_id, note, created_at)
Every day each patient gets added a health condition with a note from 1 to 10 where 10 is a good health (full recovery if you may).
What I want to extract is the following 3 statistics for the last 30 days (month):
- how many patients got better
- how many patients got worst
- how many patients remained the same
These statistics are global so I don't care right now of statistics per doctor which I could extract given the right query.
The trick is that the query needs to extract the current health_condition note and compare with the average of past days (this month without today) so one needs to extract today's note and an average of the other days excluding this one.
I don't think the query needs to define who went up/down/same since I can loop and decide that. Just today vs. rest of the month will be sufficient I guess.
Here's what I have so far which obv. doesn't work because it only returns one result due to the limit applied:
SELECT
p.id,
p.name,
hc.latest,
hcc.average
FROM
pacients p
INNER JOIN (
SELECT
id,
pacient_id,
note as LATEST
FROM
health_conditions
GROUP BY pacient_id, id
ORDER BY created_at DESC
LIMIT 1
) hc ON(hc.pacient_id=p.id)
INNER JOIN (
SELECT
id,
pacient_id,
avg(note) AS average
FROM
health_conditions
GROUP BY pacient_id, id
) hcc ON(hcc.pacient_id=p.id AND hcc.id!=hc.id)
WHERE
date_part('epoch',date_trunc('day', hcc.created_at))
BETWEEN
(date_part('epoch',date_trunc('day', hc.created_at)) - (30 * 86400))
AND
date_part('epoch',date_trunc('day', hc.created_at))
The query has all the logic it needs to distinguish between what is latest and average but that limit kills everything. I need that limit to extract the latest result which is used to compare with past results.
Something like this assuming created_at is of type date
select p.name,
hc.note as current_note,
av.avg_note
from patients p
join health_conditions hc on hc.patient_id = p.id
join (
select patient_id,
avg(note) as avg_note
from health_conditions hc2
where created_at between current_date - 30 and current_date - 1
group by patient_id
) avg on t.patient_id = hc.patient_id
where hc.created_at = current_date;
This is PostgreSQL syntax. I'm not sure if MySQL supports date arithmetics the same way.
Edit:
This should get you the most recent note for each patient, plus the average for the last 30 days:
select p.name,
hc.created_at as last_note_date
hc.note as current_note,
t.avg_note
from patients p
join health_conditions hc
on hc.patient_id = p.id
and hc.created_at = (select max(created_at)
from health_conditions hc2
where hc2.patient_id = hc.patient_id)
join (
select patient_id,
avg(note) as avg_note
from health_conditions hc3
where created_at between current_date - 30 and current_date - 1
group by patient_id
) t on t.patient_id = hc.patient_id
SELECT SUM(delta < 0) AS worsened,
SUM(delta = 0) AS no_change,
SUM(delta > 0) AS improved
FROM (
SELECT patient_id,
SUM(IF(DATE(created_at) = CURDATE(),note,NULL))
- AVG(IF(DATE(created_at) < CURDATE(),note,NULL)) AS delta
FROM health_conditions
WHERE DATE(created_at) BETWEEN CURDATE() - INTERVAL 1 MONTH AND CURDATE()
GROUP BY patient_id
) t