I have a dataset where I need to find out New subscribers revenue.
These are subscribers that are paying either weekly or monthly depending on the subscription they are on.
The unique identifier is "customer" and the data is at timestamp level, but I want it rolled up at monthly level.
Now for each month, we need to find out revenue for only NEW subscribers.
Basically, imagine customers being on monthly/weekly subscriptions and we only want their FIRST Payments to be counted here.
Here's a sample dataset and
created customer amount
16-Feb-18 14:03:55 cus_BwcisIF1YR1UlD 33300
16-Feb-18 14:28:13 cus_BpLsCvjuubYZAe 156250
15-Feb-18 19:19:14 cus_C3vT6uVBqJC1wz 50000
14-Feb-18 23:00:24 cus_BME5vNeXAeZSN2 162375
9-Feb-18 14:27:26 cus_BpLsCvjuubYZAe 156250
....and so on...
here is the final desired output
yearmonth new_amount
Jan - 2018 100000
Feb - 2018 2000
Dec - 2017 100002
This needs to be done in MySQL interface.
Basically, you want to filter the data to the first customer. One method of doing this involves a correlated subquery.
The rest is just aggregating by year and month. So, overall the query is not that complicated, but it does consist of two distinct parts:
select year(created) as yyyy, month(created) as mm,
count(*) as num_news,
sum(amount) as amount_news
from t
where t.created = (select min(t2.created)
from t t2
where t2.customer = t.customer
)
group by yyyy, mm
We can have sql subquery for only the 1st payment of the new customer with
amount for every month and year
The query is as follows
SELECT month(created) as mm,year(created) as yyyy,
sum(amount) as new_amount
FROM t
WHERE t.created=(select min(t2.created) from t t2 where
t2.customer=t.customer)
Related
I have a SQL Table of logins as a data source, and each row has an id, timestamp and user_id.
Similar to this:
id
timestamp
user_id
1
2022-01-01T15:17:13.000Z
234
2
2022-01-02T15:17:13.000Z
235
I want to build a report that shows an aggregate of logins by year. So something like (for all months, just using January as an example.):
Year
Active Users in January
Logins in January
2019
500
10000
2020
600
10002
Essentially, the active users would be grouping the rows of logins by user_id, and the logins would just aggregate the timestamps by month.
Is this kind of view something I build using a SQL query?
You may use aggregation here:
SELECT
YEAR(timestamp) AS Year,
COUNT(DISTINCT user_id) AS `Active Users in January`,
COUNT(*) AS `Logins in January`
FROM yourTable
WHERE
MONTH(timestamp) = 1
GROUP BY
YEAR(timestamp);
The number of active users is given by the distinct count of users for a given year, in the month of January. The number of logins is just the number of entries for a given year in January.
If you want to report for all months and all years, then use:
SELECT
DATE_FORMAT(timestamp, '%Y-%m') AS ym,
COUNT(DISTINCT user_id) AS `Active Users per month`,
COUNT(*) AS `Logins in month`
FROM yourTable
GROUP BY 1;
I have a database that contain a record from 2017-2021. But I need an sql code to calculate sales monthly for just 2017 alone.
It's a two different table I'm trying to call in the coding
SELECT sum(itemPrice) From article,
Month(TransactionDate) FROM transactionid WHERE
year(TransactionDate) = 2017 group by 1
If I understand your query properly, it looks like you have 2 tables called article and transactionid. I assume these 2 tables have a relationship together which I called article_id in the example below.
This would be pretty close to what you need, you just need set the correct column names:
SELECT MONTH(TransactionDate) as month, SUM(itemPrice) as total_sales
FROM article
JOIN transactionid ON transactionid.article_id = article.id
WHERE YEAR(TransactionDate) = 2017
GROUP BY MONTH(TransactionDate)
ORDER BY month;
I have been tasked to find how many users performed a transaction in every month in 2020
I know i have two tables to work with.
Table Name: Receipts|Columns: receipt_id, collection_id, user_id, amount
Table Name: Games |Columns: game_id, collection_id, game_date_time
i tried this but I dont think it makes sense or works
select month(games.game_date_time) AS Month, sum(receipts.id) from bills
join games on bills.collection_id = games.collection_id
WHERE YEAR(games.game_date_time) = 2020
group by receipts.user_id, month(games.game_date_time)
order by month(games.game_date_time)
Use COUNT() to get a count, not SUM(). And if you want a count of users, without counting the same user twice, use COUNT(DISTINCT user_id), don't put user_id in the grouping.
SELECT MONTH(g.game_date_time) AS month, COUNT(DISTINCT r.user_id) AS users
FROM receipts AS r
JOIN games AS g ON r.collection_id = g.collection_id
WHERE YEAR(g.game_date_time) = 2020
GROUP BY month
ORDER BY month
find how many users performed a transaction in every month in 2020
SELECT COUNT(r.user_id)
FROM receipts AS r
JOIN games AS g USING (collection_id)
WHERE YEAR(g.game_date_time) = 2020
GROUP BY r.user_id
HAVING COUNT(DISTINCT MONTH(g.game_date_time)) = MONTH(CURRENT_DATE)
This query:
Selects rows for current year only.
For each user - calculates the amount of distinct months for payments for this user and compares with current month. If user has payments in each month (including current!) these values are equal.
Count the amount of users matched this condition.
PS. The query will fail in 2021 - for to receive correct info in future use
HAVING COUNT(DISTINCT MONTH(g.game_date_time)) = CASE YEAR(CURRENT_DATE)
WHEN 2020
THEN MONTH(CURRENT_DATE)
ELSE 12
END
In oracle sql, how to get the count of newly added customers only for the month of april and may and make sure they werent there in the previous months
SELECT CUSTOMER ID , COUNT(*)
FROM TABLE
WHERE DATE BETWEEN '1-APR-2018' AND '31-MAY-2018' AND ...
If we give max (date) and min(date), we can compare the greater date to check if this customer is new , correct?
expected output is month count
april ---
may ---
should show the exact count how many new customers joined in these two months
One approach is to use aggregation:
select customer_id, min(date) as min_date
from t
group by customer_id
having min(date) >= date '2018-04-01 and
min(date) < date '2018-06-01';
This gets the list of customers (which your query seems to be doing). To get the count, just use count(*) and make this a subquery.
Hi still getting my head around MySQL so was hoping someone may be able to shed some light on this one
I have a table named customers which has the following columns
msisdn BIGINT 20
join_date DATETIME
The msisdn is a unique value to identify customers.
There is a second table named ws_billing_all which has the following structure
id INTEGER 11 (Primary Key)
msisdn BIGINT 20
event_time DATETIME
revenue INTEGER
So this table stores all transactions for each of the customers in the customers table as identified by the msisdn.
What I need to do is to determine the amount from all customers that joined on a particular day after 30 days.
So for example, on the 2nd of Dec 2010, 1,100 customers were acquired. Based on the data in ws_billing_all, how much total revenue did the customers that joined on this day generate 30 days from this date.
I will probably need another table for this but not sure and really not sure on how to go about extracting this data. Any help would be appreciated.
#Cularis was very close... You only care about those customers that joined on the ONE DAY, and want all THEIR REVENUEs earned for the next 30 days... In this scenario, a customer would never have sales prior to their join date, so I didn't add an explicit between on their actual sales dates of consideration.
SELECT
date( c.Join_Date ) DateJoined,
count( distinct c.msisdn ) DistinctMembers,
count(*) NumberOfOrders,
SUM(w.revenue) AmountOfRevenue
FROM
customers c
JOIN ws_billing_all w
ON c.msisdn = w.msisdn
AND date( w.event_time ) <= date_add( c.Join_Date, INTERVAL 30 DAY )
WHERE
c.Join_Date >= SomeDateParameterValue
group by
date( c.Join_Date )
order by
date( C.Join_Date )
EDIT -- For clarification...
If you had 150 people join on Dec 1, 45 people on Dec 2, 83 people on Dec 3, you want to see the total revenue per group of people based on the day they joined going out 30 days of their sales... So...
Joined on Number of People Total Revenue after 30 days
Dec 1 150 $21,394 (up to Dec 31)
Dec 2 45 $ 4,182 (up to Jan 1)
Dec 3 83 $ 6,829 (up to Jan 2)
Does this better clarify what you want? Then we can adjust the query...
FINAL EDIT ...
I think I have what you INTENDED (with a count of orders too that might be useful). In the future, providing a sample output of something of complex nature would be helpful, even if it was as simple as I've done here.
With respect to my WHERE clause from the customers table.... Say you only cared about customers who joined within a given time frame, or only after a given date... THIS is where you would update the clause... if you want based on ALL people, then just remove it completely.
SELECT c.msisdn, SUM(w.revenue)
FROM customers c
INNER JOIN ws_billing_all w ON c.msisdn=w.msisdn
WHERE w.event_time BETWEEN c.join_date AND DATE_ADD(c.join_date, INTERVAL 30 DAY)
GROUP BY c.msisdn
You have to join both tables on the customer id. Then select all events that happened between the join date and 30 days after that. Group by the customer id and use SUM() to get total revenue per costumer.