Derive Insights from BigQuery Data: Challenge Lab.md

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Derive Insights from Data with BigQuery: Challenge Lab

Query 1: Total Confirmed Cases

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

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

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

Query 4: 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"

Query 5: Identifying specific day

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

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

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

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

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

Create a 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

• Open EXPLORE DATA
• Select Explore with Data Studio
• AUTHORIZE
• You can view the chart here