Insights from Data with BigQuery: Challenge Lab

Insights from Data with BigQuery: Challenge Lab

Query 1: 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: 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'
group by subregion1_name
)

select count(*) as count_of_states
from deaths_by_states
where death_count > 100

Query 3: 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'
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: 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='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: 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: 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: 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:

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: 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

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

REF: Qwiklabs SupportQwiklabs Support 

Link lab:: link