Window LAG

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COVID-19 Data

Notes on the data: This data was assembled based on work done by Rodrigo Pombo based on John Hopkins University, based on World Health Organisation. The data was assembled 21st April 2020 - there are no plans to keep this data set up to date.

Window Function

The SQL Window functions include LAG, LEAD, RANK and NTILE. These functions operate over a "window" of rows - typically these are rows in the table that are in some sense adjacent.

Introducing the covid table

The example uses a WHERE clause to show the cases in 'Italy' in March 2020.

Modify the query to show data from Spain

SELECT name, DAY(whn),
 confirmed, deaths, recovered
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

SELECT name, DAY(whn),
 confirmed, deaths, recovered
 FROM covid
WHERE name = 'Spain'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

Introducing the LAG function

Note for MySQL: If you are using the MariaDB engine you will hit the bug https://jira.mariadb.org/browse/MDEV-23866

• You can use the Microsoft SQL Server engine instead
• You can include this line before each query:

SET @@sql_mode='ANSI';

The LAG function is used to show data from the preceding row or the table. When lining up rows the data is partitioned by country name and ordered by the data whn. That means that only data from Italy is considered.

Modify the query to show confirmed for the day before.

SELECT name, DAY(whn), confirmed,
   LAG(whn, 1) OVER (PARTITION BY name ORDER BY whn)
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

SELECT name, DAY(whn), confirmed,
   LAG(confirmed, 1) OVER (partition by name ORDER BY whn) AS dbf
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

LAG operation

Here is the correct query showing the cases for the day before:

SELECT name, DAY(whn), confirmed,
   LAG(confirmed, 1) OVER (partition by name ORDER BY whn) AS lag
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3
ORDER BY whn

Notice how the values in the LAG column match the value of the row diagonally above and to the left.

name	DAY(whn)	confirmed	dbf
Italy	1	1694	null
Italy	2	2036	1694
Italy	3	2502	2036
Italy	4	3089	2502
Italy	5	3858	3089
Italy	6	4636	3858
Italy	7	5883	4636
Italy	8	7375	5883
Italy	9	9172	7375
Italy	10	10149	9172
...

Number of new cases

The number of confirmed case is cumulative - but we can use LAG to recover the number of new cases reported for each day.

Show the number of new cases for each day, for Italy, for March.

SELECT name, DAY(whn), confirmed,
   LAG(confirmed, 1) OVER (PARTITION BY name ORDER BY whn)
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

SELECT name, DAY(whn), confirmed -
   LAG(confirmed, 1) OVER (PARTITION BY name ORDER BY whn) as new
 FROM covid
WHERE name = 'Italy'
AND MONTH(whn) = 3 AND YEAR(whn) = 2020
ORDER BY whn

Weekly changes

The data gathered are necessarily estimates and are inaccurate. However by taking a longer time span we can mitigate some of the effects.

You can filter the data to view only Monday's figures WHERE WEEKDAY(whn) = 0.

Show the number of new cases in Italy for each week in 2020 - show Monday only.

SELECT name, DATE_FORMAT(whn,'%Y-%m-%d'), confirmed
 FROM covid
WHERE name = 'Italy'
AND WEEKDAY(whn) = 0 AND YEAR(whn) = 2020
ORDER BY whn

SELECT name,DATE_FORMAT(whn,'%Y-%m-%d'),
  confirmed-LAG(confirmed,1) OVER (ORDER BY whn) "new this week"
  FROM covid
 WHERE name='Italy' and WEEKDAY(whn) = 0 AND YEAR(whn) = 2020

LAG using a JOIN

You can JOIN a table using DATE arithmetic. This will give different results if data is missing.

Show the number of new cases in Italy for each week - show Monday only.

In the sample query we JOIN this week tw with last week lw using the DATE_ADD function.

SELECT tw.name, DATE_FORMAT(tw.whn,'%Y-%m-%d'), 
 tw.confirmed, lw.confirmed
 FROM covid tw LEFT JOIN covid lw ON 
  DATE_ADD(lw.whn, INTERVAL 1 WEEK) = tw.whn
   AND tw.name=lw.name
WHERE tw.name = 'Italy'
ORDER BY tw.whn

SELECT tw.name, DATE_FORMAT(tw.whn,'%Y-%m-%d'), 
 tw.confirmed - lw.confirmed
 FROM covid tw LEFT JOIN covid lw ON 
  DATE_ADD(lw.whn, INTERVAL 1 WEEK) = tw.whn
   AND tw.name=lw.name
WHERE tw.name = 'Italy'
AND WEEKDAY(tw.whn) = 0
ORDER BY tw.whn

RANK()

This query shows the number of confirmed cases together with the world ranking for cases for the date '2020-04-20'. The number of COVID deaths is also shown.

United States has the highest number, Spain is number 2...

Notice that while Spain has the second highest confirmed cases, Italy has the second highest number of deaths due to the virus.

Add a column to show the ranking for the number of deaths due to COVID.

SELECT 
   name,
   confirmed,
   RANK() OVER (ORDER BY confirmed DESC) rc,
   deaths
  FROM covid
WHERE whn = '2020-04-20'
ORDER BY confirmed DESC

SELECT 
   name,
   confirmed,
   RANK() OVER (ORDER BY confirmed DESC) rc,
   deaths,
   RANK() OVER (ORDER BY deaths DESC) rc
  FROM covid
WHERE whn = '2020-04-20'
ORDER BY confirmed DESC

Infection rate

This query includes a JOIN t the world table so we can access the total population of each country and calculate infection rates (in cases per 100,000).

Show the infection rate ranking for each country. Only include countries with a population of at least 10 million.

SELECT 
   world.name,
   ROUND(100000*confirmed/population,2)
  FROM covid JOIN world ON covid.name=world.name
WHERE whn = '2020-04-20' AND population > 10000000
ORDER BY population DESC

SELECT 
   world.name,
   ROUND(100000*confirmed/population,2),
   RANK() OVER (ORDER BY 100000*confirmed/population) AS rank
  FROM covid JOIN world ON covid.name=world.name
WHERE whn = '2020-04-20' AND population > 10000000
ORDER BY population DESC

Turning the corner

For each country that has had at least 20000 new cases in a single day, show name of country, the date of the peak number of new cases and the peak value.

SELECT name,DATE_FORMAT(whn,'%Y-%m-%d'),
  newCases AS peakNewCases
FROM (
SELECT name,whn,newCases,
  RANK() OVER 
    (PARTITION BY name ORDER BY newCases DESC) rnc
FROM
(
  SELECT name, whn,
     confirmed -
     LAG(confirmed, 1) OVER
      (PARTITION BY name ORDER BY whn) as newCases
   FROM covid
) AS x
) AS y
WHERE rnc = 1 AND newCases>=20000
ORDER BY name