How to calculate percent change between two values in the same column - sql

Question

I want to calculate a percent change between two values in the same column in a specific form and I have no idea if what I’m trying to do is even possible.
I have a table with 3 fields
Month, Country, Value
order_month
country
value
2021-01
UK
10
2022-02
UK
20
2021-01
France
20
2022-02
France
18
2021-01
Italy
25
2021-02
Italy
35
What I struggle to get :
order_month
country
value
2021-01
UK
10
2022-02
UK
20
diff
UK
10
2021-01
France
20
2022-01
France
18
diff
France
-2
2021-01
Italy
25
2022-02
Italy
35
diff
Italy
10
I tried many things without success. Thanks a lot if you can help me on this.

Answer 1

You can use the LEAD/LAG window functions for this. I'd propose using this to create a new column for the difference, rather than hoping to add in a new row into the result to get the difference of the two rows above it.
Schema (MySQL v8.0)
CREATE TABLE data (
`order_month` date,
`country` VARCHAR(6),
`value` INTEGER
);
INSERT INTO data
(`order_month`, `country`, `value`)
VALUES
('2021-01-01', 'UK', '10'),
('2022-02-01', 'UK', '20'),
('2021-01-01', 'France', '20'),
('2022-02-01', 'France', '18'),
('2021-01-01', 'Italy', '25'),
('2022-02-01', 'Italy', '35');
Query #1
select *,
VALUE - Lead(VALUE) OVER (PARTITION BY COUNTRY ORDER BY ORDER_MONTH DESC) as Month_vs_Month
from data;
order_month
country
value
Month_vs_Month
2022-02-01
France
18
-2
2021-01-01
France
20
2022-02-01
Italy
35
10
2021-01-01
Italy
25
2022-02-01
UK
20
10
2021-01-01
UK
10
View on DB Fiddle

Answer 2

Demo Granted I'm using SQL server but both support union, both support FIRST_VALUE analytic so... I think this will be ok...
Assumptions:
Your order_month is a string or diff will be able to be used.
the collation used supports #'s first or sort could be off.
You're ok with country being sorted.
.
WITH CTE AS (SELECT order_month, country, value
FROM data
UNION ALL
SELECT Distinct 'diff' order_month, country,
FIRST_VALUE(value) over (partition by country order by order_month DESC) -
FIRST_VALUE(value) over (partition by country order by order_month ASC) value
FROM data)
SELECT *
FROM CTE
ORDER BY country, order_month
Giving us:
+-------------+---------+-------+
| order_month | country | value |
+-------------+---------+-------+
| 2021-01-01 | France | 20 |
| 2022-02-01 | France | 18 |
| diff | France | -2 |
| 2021-01-01 | Italy | 25 |
| 2022-02-01 | Italy | 35 |
| diff | Italy | 10 |
| 2021-01-01 | UK | 10 |
| 2022-02-01 | UK | 20 |
| diff | UK | 10 |
+-------------+---------+-------+
What this does:
Generate a CTE using the first_value analytic once ordered by month asc then desc.
we then subract the older form the newer.
we then need to group and order the data so we have a CTE we select from.
I'm not a fan of overlading the order_month with diff

Answer 3

You need to create two subqueries or CTEs that isolate the values to the months you're analyzing.
Subquery example
select
country,
value as jan_value
from {{table}}
where order_month = '2022-01'
Do the same for Februrary then join the tables to create a new data set with county, jan_value, and feb_value. From this dataset you can determine difference in the values.