I have a table
date
measure
value
2022-12-09
A
10
2022-12-09
B
2
2022-12-03
A
300
2022-12-03
B
30
i need to have new rows C=A/B
date
measure
value
2022-12-09
A
10
2022-12-09
B
2
2022-12-09
C
5
2022-12-03
A
300
2022-12-03
B
30
2022-12-03
C
10
how it can be done
Using conditional aggregation along with a union we can try:
SELECT date, measure, value FROM yourTable
UNION ALL
SELECT
date,
'C',
MAX(CASE WHEN measure = 'A' THEN value END) /
MAX(CASE WHEN measure = 'B' THEN value END)
FROM yourTable
GROUP BY date
ORDER BY date, measure;
Related
For example I have a table like this:
CREATE TABLE sales (
id int NOT NULL PRIMARY KEY,
sku text NOT NULL,
date date NOT NULL,
amount real NOT NULL,
CONSTRAINT date_sku UNIQUE (sku,date)
)
Is there anyway to check for each sku if every 2 days average sales is bigger than for example 14 amount sold. I want to find date ranges, the percentage and amount it sold in those days.
dbfiddle
for example for sku B in my example, it sold 15 at 2022-01-01 and 20 at 2022-01-02 and the average is 17.5 for these 2 days which is bigger than 14 therefore it will appear in my result and the change is 17.5 / 14 = 1.25.
Again for the next 2 days we have 20 at 2022-01-02 and 13 at 2022-01-03. Therefore the average is 16.5 which is bigger than 14 and it will appear in the result
but for 13 at 2022-01-03 and 12 at 2022-01-04 and the average is about 12.5. Because 12.5 is not bigger than 14, it will not appear in the result.
my desired output with 14 amount example is:
sku start_date end_date amount_sold change_rate
B 2022-01-01 2022-01-02 17.5 1.25
B 2022-01-02 2022-01-03 16.5 1.17
D 2022-01-01 2022-01-02 28 2
I tried using CASE WHEN but I know that it wont work for large data like one year:
SELECT *
FROM (
SELECT sku,
AVG(CASE WHEN date BETWEEN '2022-01-01' AND '2022-01-02' THEN amount END) AS first_in,
AVG(CASE WHEN date BETWEEN '2022-01-02' AND '2022-01-03' THEN amount END) AS second_in,
AVG(CASE WHEN date BETWEEN '2022-01-03' AND '2022-01-04' THEN amount END) AS third_in
FROM sales
GROUP BY sku
) AS t
WHERE first_in > 14
OR second_in > 14
OR third_in > 14
As a general rule, use the LEAD (or LAG) to retrieve data from the next or previous record. At least this is what I did before you asked for possibly several days. Other window functions are suitable for your need if you want more than 1 day:
SELECT *, averageamount/14
FROM (
SELECT sku, date,
MAX(date) OVER w AS nextdate,
AVG(amount) OVER w AS averageAmount
FROM sales
WINDOW w AS (PARTITION BY sku ORDER BY date RANGE BETWEEN '0 day' PRECEDING AND '2 days' FOLLOWING )
) s
WHERE averageAmount > 14
This above select all the ranges that are up to 3 days long (days D, D+1 and D+2). You may want to remove the ranges that are less than 3 days long by appending the additional condition:
AND nextdate >= date + interval '2 days'
I'm trying to add a column on this table and stuck for a little while
ID
Category 1
Date
Data1
A
1
2022-05-30
21
B
2
2022-05-21
15
A
2
2022-05-02
33
A
1
2022-02-11
3
B
2
2022-05-01
19
A
1
2022-05-15
null
A
1
2022-05-20
11
A
2
2022-04-20
22
to
ID
Category 1
Date
Data1
Picked_Data
A
1
2022-05-30
21
11
B
2
2022-05-21
15
19
A
2
2022-05-02
33
22
A
1
2022-02-11
3
some number or null
B
2
2022-05-01
19
some number or null
A
1
2022-05-15
null
some number or null
A
1
2022-05-20
11
some number or null
A
2
2022-04-20
22
some number or null
The logic is to partition by Category1 and ID then pick the latest none null value within the past 28 days. If there is no data exist, it'll be null
For the first row, ID = A and Category 1, it will pick 7th row as they are in the same category, ID and the date difference is <= 28. It skipped row 4th and 6th as the date is too far back and null value.
I've tried querying this by
select first_value(Data1) over (partition bty Category1 order by case when Data1 is not null and Date between Date - Inteverval 28 DAY and Date then 1 else 2) as Picked_Data
but it's picking incorrect rows,my guess is this query
Date between Date - Inteverval 28 DAY and Date
is not picking the correct date.. could anyone give me advise/suggestion how I could twick this query?
Consider below approach
select *,
first_value(data1 ignore nulls) over past_28_days as picked_data
from your_table
window past_28_days as (
partition by id, category_1
order by unix_date(date)
range between 29 preceding and 1 preceding
)
if applied to sample data in your question - output is
Consider below approach:
with sample_data as (
select 'A' as ID, 1 as category_1, date('2022-05-30') as date, 21 as data1,
union all select 'B' as ID, 2 as category_1, date('2022-05-21') as date, 15 as data1,
union all select 'A' as ID, 2 as category_1, date('2022-05-02') as date, 33 as data1,
union all select 'A' as ID, 1 as category_1, date('2022-02-11') as date, 3 as data1,
union all select 'B' as ID, 2 as category_1, date('2022-05-01') as date, 19 as data1,
union all select 'A' as ID, 1 as category_1, date('2022-05-15') as date, NULL as data1,
union all select 'A' as ID, 1 as category_1, date('2022-05-20') as date, 11 as data1,
union all select 'A' as ID, 2 as category_1, date('2022-04-20') as date, 22 as data1,
),
with_next_data as (
select *,
lag(date) over (partition by ID,category_1 order by date) as next_date,
lag(data1) over (partition by ID,category_1 order by date) as next_data,
from sample_data
)
select
id,
category_1,
date,
data1,
if(date_diff(date, next_date,day) <= 28, next_data, null) as picked_data
from with_next_data
Output:
I have this data, where I want to generate the last row "on the fly" from the first two:
Group
1yr
2yrs
3yrs
date
code
Port
19
-15
88
1/1/2020
arp
Bench
10
-13
66
1/1/2020
arb
Diff
9
2
22
I am trying to subtract the Port & Bench returns and have the difference on the new row. How can I do this?
Here's my code so far:
Select
date
Group,
Code,
1 yr returnp,
2 yrs returnp,
3yrs return
From timetable
union
Select
date,
Group,
Code,
1 yr returnb,
2 yrs returnb,
3yrs returnb
From timetable
Seems to me that a UNION ALL in concert with a conditional aggregation should do the trick
Note the sum() is wrapped in an abs() to match desired results
Select *
From YourTable
Union All
Select [Group] = 'Diff'
,[1yr] = abs(sum([1yr] * case when [Group]='Bench' then -1 else 1 end))
,[2yrs] = abs(sum([2yrs] * case when [Group]='Bench' then -1 else 1 end))
,[3yrs] = abs(sum([3yrs] * case when [Group]='Bench' then -1 else 1 end))
,[date] = null
,[code] = null
from YourTable
Results
Group 1yr 2yrs 3yrs date code
Port 19 -15 88 2020-01-01 arp
Bench 10 -13 66 2020-01-01 arb
Diff 9 2 22 NULL NULL
If you know there is always 2 rows, something like this would work
SELECT * FROM timetable
UNION ALL
SELECT
MAX(1yr) - MIN(1yr),
MAX(2yrs) - MIN(2yrs),
MAX(3yrs) - MIN(3yrs),
null,
null,
FROM timetable
I have data which looks like this:
Name
Date
Bal
John
2022-01-01
10
John
2022-01-02
4
John
2022-01-03
7
David
2022-01-01
13
David
2022-01-02
15
David
2022-01-03
20
I want the Bal column populated under date column, like:
Name
2022-01-01
2022-01-02
2022-01-03
John
10
4
7
David
13
15
20
What I tried is
SELECT
NAME,
CASE WHEN DATE= '2022-01-01' THEN EOD_BALANCE ELSE NULL END "01-Jan-22",
CASE WHEN DATE= '2022-01-02' THEN EOD_BALANCE ELSE NULL END "02-Jan-22"
FROM TABL1
but I am not getting the required results. Below are the results from query in first answer:
You want a pivot query here, which means you should aggregate by name and then take the max of the CASE expressions:
SELECT
NAME,
MAX(CASE WHEN DATE = '2022-01-01' THEN EOD_BALANCE END) AS "01-Jan-22",
MAX(CASE WHEN DATE = '2022-01-02' THEN EOD_BALANCE END) AS "02-Jan-22",
MAX(CASE WHEN DATE = '2022-01-03' THEN EOD_BALANCE END) AS "03-Jan-22"
FROM TABL1
GROUP BY NAME;
I have a table that looks like below where day, client_name and order_value are stored/
select day, client_name, order_value
from sample_table
day
client_name
order_value
2021-01-01
A
100
2021-01-01
A
100
2021-01-02
A
200
2021-01-03
A
100
2021-01-01
B
300
2021-01-01
B
400
2021-01-01
C
500
2021-01-02
C
500
2021-01-02
C
500
and I want to get the sum of order_value per client by day, but days in columns.
Basically, I want my result to come out something like this.
client_name
2021-01-01
2021-01-02
2021-01-03
A
200
200
100
B
700
Null
Null
C
500
1000
Null
If you know what the days are, you can use conditional aggregation:
select client_name,
sum(case when date = '2021-01-01' then order_value end) as date_20210101,
sum(case when date = '2021-01-02' then order_value end) as date_20210102,
sum(case when date = '2021-01-03' then order_value end) as date_20210103
from t
group by client_name ;
If you don't know the specific dates (i.e., you want them based on the data or a variable number), then you need to use dynamic SQL. That means that you construct the SQL statement as a string and then execute it.