I need a query to compare one Saturday's total sales with the rest of the year's average Saturday's total sales

Question

My data set's fields are ts, quantity, unit_price

I first need to run sum(quanitiy * unit_price) to get my sales number

ts(time stamp) is formatted like this - 2019-01-15 14:55:00 UTC

Answer 1

Is this what you want?

select avg(case when datecol = ? then total end) as sales_your_date,
       avg(case when datecol <> ? then total end) as sales_other       
from (select date(t.ts) as dte, sum(t.quantity * t.unit_price) as total
      from t
      where ts >= timestamp('2018-01-01') and
            ts < timestamp('2019-01-01')
      group by dte
     ) t
where extract(dayofweek from datecol) = 6  -- Saturday

This is not much different from your previous question. The same idea works, just with aggregating the data first.

? is for the date you care about.

Answer 2

Below is for BigQuery Standard SQL

#standardSQL
SELECT DATE(ts) AS sale_date, quanitiy * unit_price AS sale_total, 
  ROUND((SUM(quanitiy * unit_price) OVER() - quanitiy * unit_price) / (COUNT(1) OVER() - 1), 2) AS sale_rest_average
FROM `project.dataset.table`
WHERE EXTRACT(DAYOFWEEK FROM DATE(ts)) = 7
AND EXTRACT(YEAR FROM DATE(ts)) = 2018  

In case if you timestamp field is of TIMESTAMP data type (vs STRING) you can use just

WHERE EXTRACT(DAYOFWEEK FROM ts) = 7
AND EXTRACT(YEAR FROM ts) = 2018