I got a problem while trying to count the entries that were created in a month for the last 6 months.
The table looks like this:
A B C D
Year Month Startingdate Identifier
-----------------------------------------
2019 3 2019-03-12 OAM_1903121
2019 2 2019-03-21 OAM_1902211
And the result should look like:
A B C
Year Month Amount of orders
---------------------------------
2019 3 26
2019 2 34
This is what I have so far, but it doesn't get me the proper results:
SELECT year, month, COUNT(Startingdate) as Amount
FROM table
WHERE Startingdate > ((TRUNC(add_months(sysdate,-3) , 'MM'))-1)
GROUP BY year, month
I have not tested it, but it should work:
select year, month, count(Stringdate) as Amount_of_order
from table
where Stringdate between add_months(sysdate, -6) and sysdate
group by year, month;
Let me know.
Try that :
SELECT YEAR(Startingdate) AS [Year], MONTH(Startingdate) AS [Month], COUNT(*) AS Amount
FROM table
WHERE Startingdate > DATEADD(MONTH, -6, GETDATE())
GROUP BY YEAR(Startingdate), MONTH(Startingdate)
ORDER BY YEAR(Startingdate), MONTH(Startingdate) DESC
I think your issue is the filtering. If so, this should handle the most recent six full months:
SELECT year, month, COUNT(*) as num_orders
FROM table
WHERE Startingdate >= TRUNC(add_months(sysdate, -6) , 'MM')
GROUP BY year, month;
Related
Edit: #shawnt00 has the correct answer. Thank you very much!
I am having trouble accurately doing a year over year comparison by month but at any point during the month. For example for August 2022 vs 2021, I want to compare August 1 - August 25, rather than full month of August 2021.
I am also using a daily date field.
I want the final result to basically be:
Product_ID, Year, Month, PY_Sales, CY_Sales
Edit: I have daily totals. Some products do have not sales on certain days though:
product_id
sale_date
units
1
2021-01-01
5
2
2021-01-02
4
...
...
...
1
2021-06-05
2
2
2022-01-06
1
2
2022-08-15
9
This is the code I have, but it doesn't do MTD. So 2021 August is the entire month of August and I want it the same dates for 2022. I used this code because some products do not have sales on certain months.
WITH cte AS
(
SELECT
PRODUCT_ID,
EXTRACT(YEAR FROM SALE_DATE) AS Year,
EXTRACT(MONTH FROM SALE_DATE) AS Month,
CONCAT(EXTRACT(YEAR FROM SALE_DATE), '-',EXTRACT(MONTH FROM SALE_DATE)) AS Year_Month,
SUM(Units) AS Units
FROM data
WHERE Product_ID = 1
AND DATE(SALE_DATE) >= '2019-01-01'
GROUP BY 1, 2, 3
),
diff AS
(
SELECT
COALESCE(c.PRODUCT_ID, p.PRODUCT_ID) AS Product_ID,
COALESCE(c.Year, p.Year + 1) AS Year,
COALESCE(c.Month, p.Month) AS Month,
IFNULL(c.Units, 0) AS Current_Units,
IFNULL(p.Units, 0) AS Previous_Units,
NULLIF(((IFNULL(c.Units, 0) - IFNULL(p.Units,0)) / p.Units),0) * 100 AS Percent_Change
FROM CTE c
FULL OUTER JOIN CTE p ON c.PRODUCT_ID = p.PRODUCT_ID AND c.Year = p.Year + 1 AND c.Month = p.Month
WHERE c.Year <= EXTRACT(YEAR FROM CURRENT_DATE())
ORDER BY 2, c.Year, c.Month
)
SELECT *
FROM diff
--This is to avoid dividing by 0
WHERE diff.Previous_Units > 0
--AND Percent_Change <= -.5
You could just roll up two different monthly totals and then switch for the current month comparison:
with agg as (
select
PRODUCT_ID,
extract(year from SALE_DATE) as yr,
extract(month from SALE_DATE) as mth,
sum(Units) as Units,
sum(case when extract(day from SALE_DATE) <= extract(day from current_date())
then Units end) as UnitsMTD
from data
where date(SALE_DATE) >= '2019-01-01' -- one year before report output
group by 1, 2, 3
)
select c.Yr, c.Mth, c.PRODUCT_ID,
case when Yr = extract(year from current_date())
and Mth = extract(month from current_date())
then (c.UnitsMTD - p.UnitsMTD) / p.UnitsMTD
else (c.Units - p.Units ) / p.Units
end as Percent_Change
from agg c left outer join agg p
on p.Product_ID = c.Product_ID and p.Yr = c.Yr - 1 and p.Mth = c.Mth
order by c.Yr, c.Mth, c.PRODUCT_ID;
Note my earlier comment about leap years. This will treat February 28 of the year following a leap year as an "MTD" month. You might need to handle that differently inside the case expression.
I have a transaction table that looks something like this.
userid
orderDate
amount
111
2021-11-01
20
112
2021-09-07
17
111
2021-11-21
17
I want to count how many distinct customers (userid) that bought from our store this month also bought from our store in the previous month. For example, in February 2020, we had 20 customers and out of these 20 customers 7 of them also bought from our store in the previous month, January 2020. I want to do this for all the previous months so ending up with something like.
year
month
repeated customers
2020
01
11
2020
02
7
2020
03
9
I have written this but this only works for only the current month. How would I iterate or rewrite it to get the table as shown above.
WITH CURRENT_PERIOD AS (
SELECT DISTINCT userid
FROM table1
WHERE DATE(orderDate) BETWEEN DATE_TRUNC(CURRENT_DATE(),MONTH) AND DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)
),
PREVIOUS_PERIOD AS (
SELECT DISTINCT userid
FROM table1
WHERE DATE(orderDate) BETWEEN DATE_TRUNC(DATE_SUB(CURRENT_DATE(), INTERVAL 1 MONTH),MONTH) AND LAST_DAY(DATE_SUB(CURRENT_DATE(), INTERVAL 1 MONTH))
)
SELECT count(1)
FROM CURRENT_PERIOD RC
WHERE RC.userid IN (SELECT DISTINCT userid FROM PREVIOUS_PERIOD)
You can summarize to get one record per month, use lag(), and then aggregate:
select yyyymm,
countif(prev_yyyymm = date_add(yyyymm, interval -1 month)
from (select userid, date_trunc(order_date, month) as yyyymm,
lag(date_trunc(order_date, month)) over (partition by userid order by date_trunc(order_date, month)) as prev_yyyymm
from table1
group by 1, 2
) t
group by yyyymm
order by yyyymm;
I have a table with the following columns:
(client_id, start_contract_date, end_contract_date)
Every client has a start_contract_date but some clients have a NULL for end_contract_date since they may still be active today.
If we check for a certain date D, a client is active if D is between start_contract_date and end_contract_date (or start_contract_date <= D, if end_contract_date is NULL.)
I want to count, for each month of each year, over 2016 until today, how many customers are active. My problem is that I do not know how to LOOP on the months and years.
I have a partial solution. I can count how many active clients for a specific month of a specific year.
SELECT 2016 as year , 7 as month, count(id_client)
FROM table
WHERE
EXTRACT(year from start_contract_date)<=2016
AND EXTRACT(month from start_contract_date)<=7
AND (EXTRACT(year from end_contract_date)>=2016 OR end_contract_date IS NULL)
AND (EXTRACT(month from end_contract_date)>=7 OR end_contract_date IS NULL)
;
So, how can I run a nested for loop that would be something like
FOR y IN 2016..2017
FOR m IN 1..12
I want the output to be
Year , Month , Count
2016 , 1 , 234
2016 , 2 , 54
…
2017 , 12 , 543
Use the function generate_series() to generate arbitrary series of months, e.g.:
select extract(year from d) as year, extract(month from d) as month
from generate_series('2017-11-01'::date, '2018-02-01', '1 month') d
year | month
------+-------
2017 | 11
2017 | 12
2018 | 1
2018 | 2
(4 rows)
Use the above and the function date_trunc() to extract year-month value from dates:
select extract(year from d) as year, extract(month from d) as month, count(id_client)
from generate_series('2016-01-01'::date, '2019-03-01', '1 month') d
left join my_table
on date_trunc('month', start_contract_date) <= date_trunc('month', d)
and (end_contract_date is null or date_trunc('month', end_contract_date) >= date_trunc('month', d))
group by d
order by d
Note also that the conditions in your query contain logical error.
I have a table as follows
user_id date month year visiting_id
123 11-04-2017 APRIL 2017 4500
123 12-05-2017 MAY 2017 4567
123 13-05-2017 MAY 2017 4568
123 17-05-2017 MAY 2017 4569
123 22-05-2017 MAY 2017 4570
123 11-06-2017 JUNE 2017 4571
123 12-06-2017 JUNE 2017 4572
I want to calculate the visiting count for the current month and last month at the monthly level as follows:
user_id month year visit_count_this_month visit_count_last_month
123 APRIL 2017 1 0
123 MAY 2017 4 1
123 JUNE 2017 2 4
I was able to calculate visit_count_this_month using the following query
SELECT v.user_id, v.month, v.year,
SUM(is_visit_this_month) as visit_count_this_month
FROM
(SELECT user_id, date, month, year,
CASE WHEN TO_CHAR(date, 'MM/YYYY') = TO_CHAR(date, 'MM/YYYY')
THEN 1 ELSE 0
END as is_visit_this_month
FROM visits
GROUP BY user_id, date, month, year
HAVING user_id = 123) v
GROUP BY v.user_id, v.month, v.year
However, I'm stuck with calculating visit_count_last_month. Similar to this, I also want to calculate visit_count_last_2months.
Can somebody help?
You can use a LATERAL JOIN like this:
SELECT user_id, month, year, COUNT(*) as visit_count_this_month, visit_count_last_month
FROM visits v
CROSS JOIN LATERAL (
SELECT COUNT(*) as visit_count_last_month
FROM visits
WHERE user_id = v.user_id
AND date = (CAST(v.date AS date) - interval '1 month')
) l
GROUP BY user_id, month, year, visit_count_last_month;
SQLFiddle - http://sqlfiddle.com/#!15/393c8/2
Assuming there are values for every month, you can get the counts per month first and use lag to get the previous month's values per user.
SELECT T.*
,COALESCE(LAG(visits,1) OVER(PARTITION BY USER_ID ORDER BY year,mth),0) as last_month_visits
,COALESCE(LAG(visits,2) OVER(PARTITION BY USER_ID ORDER BY year,mth),0) as last_2_month_visits
FROM (
SELECT user_id, extract(month from date) as mth, year, COUNT(*) as visits
FROM visits
GROUP BY user_id, extract(month from date), year
) T
If there can be missing months, it is best to generate all months within a specified timeframe and left join ing the table on to that. (This example shows it for all the months in 2017).
select user_id,yr,mth,visits
,coalesce(lag(visits,1) over(PARTITION BY USER_ID ORDER BY yr,mth),0) as last_month_visits
,coalesce(lag(visits,2) OVER(PARTITION BY USER_ID ORDER BY yr,mth),0) as last_2_month_visits
from (select u.user_id,extract(year from d.dt) as yr, extract(month from d.dt) as mth,count(v.visiting_id) as visits
from generate_series(date '2017-01-01', date '2017-12-31',interval '1 month') d(dt)
cross join (select distinct user_id from visits) u
left join visits v on extract(month from v.dt)=extract(month from d.dt) and extract(year from v.dt)=extract(year from d.dt) and u.user_id=v.user_id
group by u.user_id,extract(year from d.dt), extract(month from d.dt)
) t
I have a table with a date column. I wanted to get the count of months and display them in the order of months. Months should be displayed as 'Jan', 'Feb' etc. If I use to_char function, the order by happens on text. I can use extract(month from dt), but that will also display month in number format. This is part of a report and month should be displayed in 'Mon' format only.
SELECT to_char(dt,'Mon'), COUNT(*) FROM tb GROUP BY to_char(dt,'Mon') ORDER BY to_char(dt,'Mon');
to_char | count
---------+-------
Dec | 1
Jan | 1
Jul | 2
select month, total
from (
select
extract(month from dt) as month_number,
to_char(dt,'mon') as month,
count(*) as total
from tb
group by 1, 2
) s
order by month_number