Here is a dashboard I created in Tableau with global COVID-19 data from all of 2020.
Below are SQL queries from a Google Cloud Challenge using COVID-19 data:
-- Query 1: Total Confirmed Cases
-- Build a query that will answer - What was the total count of confirmed cases on Apr 15, 2020?
-- The query needs to return a single row containing the sum of confirmed cases across all countries.
-- The name of the column should be total_cases_worldwide.
SELECT
sum(cumulative_confirmed) as total_cases_worldwide
FROM `bigquery-public-data.covid19_open_data.covid19_open_data`
where date='2020-04-15'
-- Query 2: Worst Affected Areas
-- Build a query for answering - How many states in the US had more than 100 deaths on Apr 10, 2020?
-- The query needs to list the output in the field - count_of_states.
with deaths_by_states as (
SELECT
subregion1_name as state,
sum(cumulative_deceased) as death_count
FROM `bigquery-public-data.covid19_open_data.covid19_open_data`
where country_name="United States of America" and date='2020-04-10' and subregion1_name is NOT NULL
group by subregion1_name
)
select
count(*) as count_of_states
from deaths_by_states
where death_count > 100
/*
Query 3: Identifying Hotspots
Build a query that will answer - List all the states in the United States of America that had more than 1000 confirmed cases on Apr 10, 2020?
The query needs to return the State Name and the corresponding confirmed cases arranged in descending order.
Name of the fields to return - state and total_confirmed_cases.
*/
SELECT
subregion1_name as state,
sum(cumulative_confirmed) as total_confirmed_cases
FROM `bigquery-public-data.covid19_open_data.covid19_open_data`
where country_name="United States of America" and date='2020-04-10' and subregion1_name is NOT NULL
group by subregion1_name
having total_confirmed_cases > 1000
order by total_confirmed_cases desc
/*
- AT - Verify the structure of the query and if it contains:
- Fields as state and total_confirmed_cases
- country_region=US and date=’2020-04-10’
- Has a group by province_state
- Has a having clause on total_confirmed_cases > 1000
- Has a order by clause on total_confirmed_cases and mentions desc
*/
-- Query 4: Fatality Ratio
-- Build a query for answering - What was the case-fatality ratio in Italy for the month of April 2020? Case-fatality ratio here is defined as (total deaths / total confirmed cases) * 100.
-- Write a query to return the ratio for the month of April 2020 and containing the following fields in the output - total_confirmed_cases, total_deaths, case_fatality_ratio.
SELECT
sum(cumulative_confirmed) as total_confirmed_cases,
sum(cumulative_deceased) as total_deaths,
(sum(cumulative_deceased)/sum(cumulative_confirmed)) * 100 as case_fatality_ratio
FROM `bigquery-public-data.covid19_open_data.covid19_open_data`
where country_name="Italy" AND date BETWEEN '2020-04-01'and '2020-04-30'
/*
AT - Verify the structure of the query and if it contains:
- Fields contain total_confirmed_cases, total_deaths, case_fatality_ratio
- country_region=’Italy’ and date=’2020-04-30’
*/
-- Query 5: Identifying specific day
-- Build a query for answering - On what day did the total number of deaths cross 10000 in Italy?
-- The query should return the date in the format : yyyy-mm-dd.
SELECT
date
FROM `bigquery-public-data.covid19_open_data.covid19_open_data`
where country_name="Italy" and cumulative_deceased>10000
order by date asc
limit 1
-- Query 6: Finding days with zero net new cases
-- The following query is written to identify the number of days in India between 21 Feb 2020 and 15 March 2020 when there were zero increases in the number of confirmed cases. However it is not executing properly. You need to update the query to complete it and obtain the result.
WITH india_cases_by_date AS (
SELECT
date,
SUM( cumulative_confirmed ) AS cases
FROM
`bigquery-public-data.covid19_open_data.covid19_open_data`
WHERE
country_name ="India"
AND date between '2020-02-21' and '2020-03-15'
GROUP BY
date
ORDER BY
date ASC
)
, india_previous_day_comparison AS
(SELECT
date,
cases,
LAG(cases) OVER(ORDER BY date) AS previous_day,
cases - LAG(cases) OVER(ORDER BY date) AS net_new_cases
FROM india_cases_by_date
)
select
count(*)
from india_previous_day_comparison
where net_new_cases=0
-- Query 7: Doubling rate
-- Using the previous query as a template, write a query to find out the dates on which the confirmed cases increased
-- by more than 10% compared to the previous day (indicating a doubling rate of ~ 7 days) in the US between the dates March 22, 2020 and April 20, 2020.
-- The query needs to return the list of dates, the confirmed cases on that day, the confirmed cases the previous day and the percentage increase in cases between the days.
-- Use the following names for the returned fields: Date, Confirmed_Cases_On_Day, Confirmed_Cases_Previous_Day and Percentage_Increase_In_Cases.
WITH us_cases_by_date AS (
SELECT
date,
SUM(cumulative_confirmed) AS cases
FROM
`bigquery-public-data.covid19_open_data.covid19_open_data`
WHERE
country_name="United States of America"
AND date between '2020-03-22' and '2020-04-20'
GROUP BY
date
ORDER BY
date ASC
)
, us_previous_day_comparison AS
(SELECT
date,
cases,
LAG(cases) OVER(ORDER BY date) AS previous_day,
cases - LAG(cases) OVER(ORDER BY date) AS net_new_cases,
(cases - LAG(cases) OVER(ORDER BY date))*100/LAG(cases) OVER(ORDER BY date) AS percentage_increase
FROM us_cases_by_date
)
select
Date,
cases as Confirmed_Cases_On_Day,
previous_day as Confirmed_Cases_Previous_Day,
percentage_increase as Percentage_Increase_In_Cases
from us_previous_day_comparison
where percentage_increase > 10
-- Query 8: Recovery rate
-- Build a query to list the recovery rates of countries arranged in descending order (limit to 10) up to the date May 10, 2020.
-- Restrict the query to only those countries having more than 50K confirmed cases.
-- The query needs to return the following fields: country, recovered_cases, confirmed_cases, recovery_rate.
WITH cases_by_country AS (
SELECT
country_name AS country,
sum(cumulative_confirmed) AS cases,
sum(cumulative_recovered) AS recovered_cases
FROM
bigquery-public-data.covid19_open_data.covid19_open_data
WHERE
date = '2020-05-10'
GROUP BY
country_name
)
, recovered_rate AS
(SELECT
country,
cases,
recovered_cases,
(recovered_cases * 100)/cases AS recovery_rate
FROM cases_by_country
)
SELECT
country,
cases AS confirmed_cases,
recovered_cases,
recovery_rate
FROM recovered_rate
WHERE cases > 50000
ORDER BY recovery_rate desc
LIMIT 10
-- Query 9: CDGR Cumulative Daily Growth Rate
-- The following query is trying to calculate the CDGR on May 10, 2020(Cumulative Daily Growth Rate) for France since the day the first case was reported.
-- The first case was reported on Jan 24, 2020.
-- The CDGR is calculated as: ((last_day_cases/first_day_cases)^1/days_diff)-1)
-- Where :
-- last_day_cases is the number of confirmed cases on May 10, 2020
-- first_day_cases is the number of confirmed cases on Feb 02, 2020
-- days_diff is the number of days between Feb 02 - May 10, 2020
-- The query isn’t executing properly as it contains an error. Can you fix the error to make the query execute successfully?
WITH
france_cases AS (
SELECT
date,
SUM(cumulative_confirmed) AS total_cases
FROM
`bigquery-public-data.covid19_open_data.covid19_open_data`
WHERE
country_name="France"
AND date IN ('2020-01-24',
'2020-05-10')
GROUP BY
date
ORDER BY
date)
, summary as (
SELECT
total_cases AS first_day_cases,
LEAD(total_cases) OVER(ORDER BY date) AS last_day_cases,
DATE_DIFF(LEAD(date) OVER(ORDER BY date),date, day) AS days_diff
FROM
france_cases
LIMIT 1
)
select
first_day_cases,
last_day_cases,
days_diff,
POW((last_day_cases/first_day_cases),
(1/days_diff))-1 as cdgr
from summary
/*
AT - Execute student query and check for:
- last_day_cases = 177094
- days_diff = 107
- cdgr is in between 11.22 - 11.23
*/
-- Datastudio report:
-- Create a Datastudio report that plots the following for the United States:
-- Number of Confirmed Cases
-- Number of Deaths
-- Date range : 2020-03-15 to 2020-04-30
SELECT
date,
SUM(cumulative_confirmed) AS country_cases,
SUM(cumulative_deceased) AS country_deaths
FROM
`bigquery-public-data.covid19_open_data.covid19_open_data`
WHERE
date BETWEEN '2020-03-15'
AND '2020-04-30'
AND country_name ="United States of America"
GROUP BY date
