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Integrate BigQuery Data and Google Workspace using Apps Script: Challenge Lab
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Integrate BigQuery Data and Google Workspace using Apps Script: Challenge Lab
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* Go to **BigQuery**
* Go to **Resources** > Add Data > Explore public datasets
* Select **COVID-19 Open Data** > **VIEW DATASET**
### Query 1: Total Confirmed Cases
```sql
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
```sql
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
```sql
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
```sql
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
```sql
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
```sql
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
```sql
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
```sql
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
```sql
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
```
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