Code Monkey home page Code Monkey logo

insights-from-data-with-bigquery-challenge-lab's Introduction

Insights-from-Data-with-BigQuery-Challenge-Lab

Task 1::=>

SELECT sum(cumulative_confirmed) as total_cases_worldwide FROM bigquery-public-data.covid19_open_data.covid19_open_data WHERE date=<change date eg'020-04-10'>


Task 2::=>

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=<change date eg'020-04-10'> and subregion1_name is NOT NULL

group by subregion1_name

)

select count(*) as count_of_states

from deaths_by_states

where death_count >


Task 3 ::=>

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=<change date eg'020-04-10'> AND subregion1_name is NOT NULL

GROUP BY subregion1_name

ORDER BY total_confirmed_cases DESC

) WHERE total_confirmed_cases >


Task 4 ::=>

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 <change month here '2020-04-01'> and < change month here '2020-04-30'>


Task 5 ::=>

SELECT date

FROM bigquery-public-data.covid19_open_data.covid19_open_data

where country_name="Italy" and cumulative_deceased>

order by date asc

limit 1


Task 6 ::=>

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 < change the date here'2020-02-21'> and <change the date here'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


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 >


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 10


Task 9 ::=>

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',

  <change the date value here'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


Task 10 ::=>

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


!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! END OF LAB !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.