Like  most  other relational database products, 
    PostgreSQL supports
    aggregate functions.
    An aggregate function computes a single result from multiple input rows.
    For example, there are aggregates to compute the
    count, sum,
    avg (average), max (maximum) and
    min (minimum) over a set of rows.
   
As an example, we can find the highest low-temperature reading anywhere with
SELECT max(temp_lo) FROM weather;
max ----- 46 (1 row)
If we wanted to know what city (or cities) that reading occurred in, we might try
SELECT city FROM weather WHERE temp_lo = max(temp_lo); WRONG
    but this will not work since the aggregate
    max cannot be used in the
    WHERE clause.  (This restriction exists because
    the WHERE clause determines the rows that will
    go into the aggregation stage; so it has to be evaluated before
    aggregate functions are computed.)
    However, as is often the case
    the query can be restated to accomplish the intended result, here
    by using a subquery:
SELECT city FROM weather
    WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
city --------------- San Francisco (1 row)
This is OK because the subquery is an independent computation that computes its own aggregate separately from what is happening in the outer query.
Aggregates are also very useful in combination with GROUP BY clauses. For example, we can get the maximum low temperature observed in each city with
SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city;
city | max ---------------+----- Hayward | 37 San Francisco | 46 (2 rows)
which gives us one output row per city. Each aggregate result is computed over the table rows matching that city. We can filter these grouped rows using HAVING:
SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city
    HAVING max(temp_lo) < 40;
city | max ---------+----- Hayward | 37 (1 row)
which gives us the same results for only the cities that have all temp_lo values below 40. Finally, if we only care about cities whose names begin with "S", we might do
SELECT city, max(temp_lo)
    FROM weather
    WHERE city LIKE 'S%'(1)
    GROUP BY city
    HAVING max(temp_lo) < 40;
It is important to understand the interaction between aggregates and SQL's WHERE and HAVING clauses. The fundamental difference between WHERE and HAVING is this: WHERE selects input rows before groups and aggregates are computed (thus, it controls which rows go into the aggregate computation), whereas HAVING selects group rows after groups and aggregates are computed. Thus, the WHERE clause must not contain aggregate functions; it makes no sense to try to use an aggregate to determine which rows will be inputs to the aggregates. On the other hand, HAVING clauses always contain aggregate functions. (Strictly speaking, you are allowed to write a HAVING clause that doesn't use aggregates, but it's wasteful: The same condition could be used more efficiently at the WHERE stage.)
Observe that we can apply the city name restriction in WHERE, since it needs no aggregate. This is more efficient than adding the restriction to HAVING, because we avoid doing the grouping and aggregate calculations for all rows that fail the WHERE check.