Task 1:- make a changes in data according

SELECT sum(cumulative_confirmed) as total_cases_worldwide

FROM `bigquery-public-data.covid19_open_data.covid19_open_data`

WHERE date='2020-05-25'

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Task 2:- Worst affected areas

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 > 300

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Task 3:-Identifying hotspots

SELECT * FROM (

SELECT subregion1_name as state, sum(cumulative_confirmed) as total_confirmed_cases

FROM `bigquery-public-data.covid19_open_data.covid19_open_data`

WHERE country_code="US" AND date='2020-04-10' AND subregion1_name is NOT NULL

GROUP BY subregion1_name

ORDER BY total_confirmed_cases DESC

)

WHERE total_confirmed_cases > 3000

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Task 4:- Fatality ratio

NOTE :- look carefully in may there are 31 day and april 30 so please make the changes according

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 '2020-05-01'and '2020-05-31'

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Task 5:- Identifying specific day

SELECT date

FROM `bigquery-public-data.covid19_open_data.covid19_open_data`

where country_name="Italy" and cumulative_deceased>16000

order by date asc

limit 1

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Task 6:- Finding days with zero net new cases

NOTE:- please check the start date and end date carefully

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 '2020-02-23' and '2020-03-11'

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

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Task 7:-

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 > 5

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Task 8:-

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 5

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Task 9:- Here we change the date

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',

'2020-04-10')

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, POWER((last_day_cases/first_day_cases),(1/days_diff))-1 as cdgr

from summary

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Task 10:- Create a Looker Studio report

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 '2020-03-20'

AND '2020-04-23'

AND country_name ="United States of America"

GROUP BY date