PRQL – A proposal for a better SQL(github.com)

    SELECT TOP 20
        title,
        country,
        AVG(salary) AS average_salary,
        SUM(salary) AS sum_salary,
        AVG(gross_salary) AS average_gross_salary,
        SUM(gross_salary) AS sum_gross_salary,
        AVG(gross_cost) AS average_gross_cost,
        SUM(gross_cost) AS sum_gross_cost,
        COUNT(*) as count
    FROM (
        SELECT
            title,
            country,
            salary,
            (salary + payroll_tax) AS gross_salary,
            (salary + payroll_tax + healthcare_cost) AS gross_cost
        FROM employees
        WHERE country = 'USA'
    ) emp
    WHERE gross_cost > 0
    GROUP BY title, country
    ORDER BY sum_gross_cost
    HAVING count > 200

    ...
    filter gross_cost > 0
    aggregate by:[title, country] [
        average salary,
        sum gross_salary,
        average gross_cost,
        let sum_gc = sum gross_cost,
        count,
    ]
    sort sum_gc

    from employees
     filter country = "USA"                           # Each line transforms the previous result.
     let gross_salary = salary + payroll_tax          # This _adds_ a column / variable.
     let gross_cost   = gross_salary + benefits_cost  # Variables can use other variables.
     filter gross_cost > 0
     aggregate by:[title, country] [                  # `by` are the columns to group by.
          average salary,                              # These are the calcs to run on the groups.
          sum     salary,
          average gross_salary,
          sum     gross_salary,
          average gross_cost,
          sum     gross_cost,
          count,
 ]
     sort sum_gross_cost                              # Uses the auto-generated column name.
     filter count > 200
     take 20

    select
        sum(blah) over window_abc,
        avg(blah) over window_abc
    from table_xyz
    window window_abc as (partition by x order by y)

    SELECT
        date,
        CASE WHEN is_valid_price
            THEN price_adjusted / LAG(price_adjusted, 1) OVER w - 1 + dividend_return
            ELSE NULL
        END AS return_total,
        CASE WHEN is_valid_price
            THEN price_adjusted_usd / LAG(price_adjusted_usd, 1) OVER w - 1 + dividend_return
            ELSE NULL
        END AS return_usd,
        CASE WHEN is_valid_price
            THEN price_adjusted / LAG(price_adjusted, 1) OVER w - 1 + dividend_return - interest_rate / 252
            ELSE NULL
        END AS return_excess,
        CASE WHEN is_valid_price
            THEN price_adjusted_usd / LAG(price_adjusted_usd, 1) OVER w - 1 + dividend_return - interest_rate / 252
            ELSE NULL
        END AS return_usd_excess
    FROM
        prices
    WINDOW
        w AS (PARTITION BY sec_id ORDER BY date)
    ;

  * https://github.com/mrumkovskis/tresql
  * https://www.htsql.org/doc/overview.html
  * https://github.com/cytosm/cytosm

  select
    salary + payroll_tax as _gross_salary,
    _gross_salary + benefits_cost as gross_cost,
    ...etc...

      from population
    select country, rollup(city), count(*)
      sort

    select country, city, count(*)
      from population
     group by country, rollup(city)
     order by country, city

    from employees
    filter country = "USA"                         # Each line transforms the previous result.
    gross_salary = salary + payroll_tax            # This _adds_ a column / variable.
    gross_cost   = gross_salary + healthcare_cost  # Variable can use other variables.
    filter gross_cost > 0
    aggregate split:[title, country] [             # Split are the columns to group by.
        average salary,                            # These are the calcs to run on the groups.
        sum     salary,
        average gross_salary,
        sum     gross_salary,
        average gross_cost,
        sum     gross_cost,
        count,
    ]
    sort sum_gross_cost                            # Uses the auto-generated column name.
    filter count > 200
    take 20

    from employees
    filter country = "USA"                         # Each line transforms the previous result.
    gross_salary = salary + payroll_tax            # This _adds_ a column / variable.
    gross_cost   = gross_salary + healthcare_cost  # Variable can use other variables.
    filter gross_cost > 0