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.

Modify the query to show data from Spain

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

Introducing the LAG function

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
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
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.

nameDAY(whn)confirmeddbf
Italy11694null
Italy220361694
Italy325022036
Italy430892502
Italy538583089
Italy646363858
Italy758834636
Italy873755883
Italy991727375
Italy10101499172
...

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
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
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 - show Monday only.

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

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()

The query shown shows the number of confirmed cases together with the world ranking for cases.

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.

Include the ranking for the number of deaths in the table.

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

The query shown 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 infect rate ranking for each country. Only include countries with a population of at least 10 million.

SELECT 
   world.name,
   ROUND(100000*confirmed/population,0)
  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,0),
   RANK() OVER (ORDER BY 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 last 1000 new cases in a single day, show the date of the peak number of new cases.

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>1000
ORDER BY whn