I have a table that stores, number of fruits sold on each day. Stores number of items sold on particular date.
CREATE TABLE data
(
code VARCHAR2(50) NOT NULL,
amount NUMBER(5) NOT NULL,
DATE VARCHAR2(50) NOT NULL,
);
Sample data
code |amount| date
------+------+------------
aple | 1 | 01/01/2010
aple | 2 | 02/02/2010
orange| 3 | 03/03/2010
orange| 4 | 04/04/2010
I need to write a query, to list out, how many apple and orange sold for jan and february?
--total apple for jan
select sum(amount) from mg.drum d where date >='01/01/2010' and cdate < '01/02/2020' and code = 'aple';
--total apple for feb
select sum(amount) from mg.drum d where date >='01/02/2010' and cdate < '01/03/2020' and code = 'aple';
--total orange for jan
select sum(amount) from mg.drum d where date >='01/01/2010' and cdate < '01/02/2020' and code = 'orange';
--total orange for feb
select sum(amount) from mg.drum d where date >='01/02/2010' and cdate < '01/03/2020' and code = 'orange';
If I need to calculate for more months, more fruits, its tedious.is there a short query to write?
Can I combine at least for the months into 1 query? So 1 query to get total for each month for 1 fruit?
You can use conditional aggregation such as
SELECT TO_CHAR("date",'MM/YYYY') AS "Month/Year",
SUM( CASE WHEN code = 'apple' THEN amount END ) AS apple_sold,
SUM( CASE WHEN code = 'orange' THEN amount END ) AS orange_sold
FROM data
WHERE "date" BETWEEN date'2020-01-01' AND date'2020-02-29'
GROUP BY TO_CHAR("date",'MM/YYYY')
where date is a reserved keyword, cannot be a column name unless quoted.
Demo
select sum(amount), //date.month
from mg.drum
group by //date.month
//data.month Here you can give experssion which will return month number or name.
If you are dealing with months, then you should include the year as well. I would recommend:
SELECT TRUNC(date, 'MON') as yyyymm, code,
SUM(amount)
FROM t
GROUP BY TRUNC(date, 'MON'), code;
You can add a WHERE clause if you want only some dates or codes.
This will return a separate row for each row that has data. That is pretty close to the results from your four queries -- but this does not return 0 values.
select to_char(date_col,'MONTH') as month, code, sum(amount)
from mg.drum
group by to_char(date_col,'MONTH'), code
Related
I have a dataset in bigquery which contains order_date: DATE and customer_id.
order_date | CustomerID
2019-01-01 | 111
2019-02-01 | 112
2020-01-01 | 111
2020-02-01 | 113
2021-01-01 | 115
2021-02-01 | 119
I try to count distinct customer_id between the months of the previous year and the same months of the current year. For example, from 2019-01-01 to 2020-01-01, then from 2019-02-01 to 2020-02-01, and then who not bought in the same period of next year 2020-01-01 to 2021-01-01, then 2020-02-01 to 2021-02-01.
The output I am expect
order_date| count distinct CustomerID|who not buy in the next period
2020-01-01| 5191 |250
2020-02-01| 4859 |500
2020-03-01| 3567 |349
..........| .... |......
and the next periods shouldn't include the previous.
I tried the code below but it works in another way
with customers as (
select distinct date_trunc(date(order_date),month) as dates,
CUSTOMER_WID
from t
where date(order_date) between '2018-01-01' and current_date()-1
)
select
dates,
customers_previous,
customers_next_period
from
(
select dates,
count(CUSTOMER_WID) as customers_previous,
count(case when customer_wid_next is null then 1 end) as customers_next_period,
from (
select prev.dates,
prev.CUSTOMER_WID,
next.dates as next_dates,
next.CUSTOMER_WID as customer_wid_next
from customers as prev
left join customers
as next on next.dates=date_add(prev.dates,interval 1 year)
and prev.CUSTOMER_WID=next.CUSTOMER_WID
) as t2
group by dates
)
order by 1,2
Thanks in advance.
If I understand correctly, you are trying to count values on a window of time, and for that I recommend using window functions - docs here and here a great article explaining how it works.
That said, my recommendation would be:
SELECT DISTINCT
periods,
COUNT(DISTINCT CustomerID) OVER 12mos AS count_customers_last_12_mos
FROM (
SELECT
order_date,
FORMAT_DATE('%Y%m', order_date) AS periods,
customer_id
FROM dataset
)
WINDOW 12mos AS ( # window of last 12 months without current month
PARTITION BY periods ORDER BY periods DESC
ROWS BETWEEN 12 PRECEEDING AND 1 PRECEEDING
)
I believe from this you can build some customizations to improve the aggregations you want.
You can generate the periods using unnest(generate_date_array()). Then use joins to bring in the customers from the previous 12 months and the next 12 months. Finally, aggregate and count the customers:
select period,
count(distinct c_prev.customer_wid),
count(distinct c_next.customer_wid)
from unnest(generate_date_array(date '2020-01-01', date '2021-01-01', interval '1 month')) period join
customers c_prev
on c_prev.order_date <= period and
c_prev.order_date > date_add(period, interval -12 month) left join
customers c_next
on c_next.customer_wid = c_prev.customer_wid and
c_next.order_date > period and
c_next.order_date <= date_add(period, interval 12 month)
group by period;
I have three columns
year | money | id
2020 100 01
2020 100 01
2019 50 02
2018 50 03
2020 40 04
results should be
Year | Money | total people
2020 | 240 | 4
** AS first two ids are the same, I tried it as below
select year, sum(money), Count( Distinct id) from table
group by year
But the result shows 4 people which is the correct but wrong sum, as it is counting all of the money
You can aggregate and then aggregate again:
select max(year), sum(money), count(*)
from (select distinct year, money, id
from t
) t;
You can use SUM() and COUNT(DISTINCT x).
For example:
select
year,
sum(money) as money,
(select count(distinct id) from t) as total_people
from t
where year = 2020
group by year;
Result:
YEAR MONEY TOTAL_PEOPLE
----- ------ ------------
2020 240 4
See running example at db<>fiddle.
Not the most performant, but if you wish to avoid a derived table, you can do
select distinct
max(year) over (),
sum(money) over (),
count(*) over ()
from t
group by year, money, id;
And if you want this grouped by year, you can define the partitions in the over clause
My good reference has been
Convert Month Number to Month Name Function in SQL
So far I have:
SELECT Detail.ItemCode, SUM(Detail.QuantityOrdered) AS Total_Quantity, Header.OrderDate
FROM Detail INNER
JOIN rHeader ON Detail.SalesOrderNo = Header.SalesOrderNo
WHERE Header.OrderDate >= dateadd("m", -4, Date())
GROUP BY Detail.ItemCode, OrderDate
ORDER BY SUM(Detail.QuantityOrdered) DESC;
It filters my results and it shows only last four months result from today's month.
I'd like to have each month's sales quantity sum, and its month to name function.
For instance:
ItemCode | 10 or October | 11 | 12 | 1
PM | 200 | 200 | 200 | 200
Update: I did try the following line of code, but my date is in the form of 12/26/2016. Is there anyway that I can play with it?? Thank you!
SELECT MonthName( month , DateAdd( month , #MonthNumber , 0 ) - 1 )
In an Access query you should be able to use the MonthName function to convert a month number (e.g., 10) into a month name (e.g., 'October').
For example, if you have a query that returns a date of birth (DOB)...
SELECT [DOB] FROM [Clients] WHERE [ID]=1
DOB
----------
1977-05-15
.. you can return the name of the month in which they were born using
SELECT MonthName(Month([DOB])) AS MonthOfBirth FROM [Clients] WHERE [ID]=1
MonthOfBirth
------------
May
I have this query:
select count(distinct orderid), employeeinfo.Name
from orderinfo, employeeinfo
where preparedate = '2014-11-10'
and prepareby = employeeid
group by employeeinfo.name
It outputs data like
1 | Jeff
4 | Bob
5 | Steve
Is there a way to make this work for a date range so that I can graph the data in excel?
if I want to line graph data for every day for the month of December
I'm not sure, what's your expected output, but to get a date range, you could use:
select count(distinct orderid), employeeinfo.Name
from orderinfo, employeeinfo
where preparedate <= '2014-11-30' AND preparedate >= '2014-11-01'
and prepareby = employeeid
group by employeeinfo.name
I know it's just late in the day and my brain is just fried....
Using Teradata, I need to COUNT DISTINCT MEMBERS that haven't had a TRANS in the past six months and also COUNT the number of TRANS they had historically (prior to the six months). We can just assume the cutoff date to be 01/01/2012. All table is contained in a single table.
For example:
Member | Tran Date
123 | 01/01/2011
789 | 06/01/2011
123 |10/31/2011
678 | 04/03/2011
789 | 06/01/2012
So 2 members had a total of 3 transactions dated prior to 1/1/2012 with no transactions later than 1/1/2012.
In this example, my result would be:
MEMBERS | TRANS
2 | 3
Try this solution:
SELECT
COUNT(DISTINCT member_id) AS MEMBERS,
COUNT(*) AS TRANS
FROM
tbl
WHERE
member_id NOT IN
(
SELECT DISTINCT member_id
FROM tbl
WHERE trans_date > '2012-01-01'
)
You can't do it in one SQL statement. Use subqueries. This is TSQL coz I am unfamiliar with Teradata.
DECLARE #CUTOFF DATETIME = DATEADD(MO,-6,GETDATE()) --6MTHS AGO
SELECT COUNT(MEMBERID) AS MEMBERS, SUM(TRANSCOUNT) AS TRANS FROM (
SELECT DISTINCT
MEMBERID,
(SELECT COUNT(*) TRANSDATE WHERE TRANSDATA.MEMBERID = MEMBER.MEMBERIF) AS TRANSCOUNT
FROM MEMBER WHERE NOT EXISTS
(SELECT * FROM TRANSDATA, MEMBER WHERE
TRANSDATA.MEMBERID = MEMBER.MEMBERIF
AND TRANDATE > #CUTOFF)
)