| h1a.sql | The name, age, and
earnings of all players ordered from the player with the most earnings to
the player with the least earnings
SELECT name, age, earnings |
| h1b.sql | The name, country, age,
number of top 10 finishes, and earnings for all those players that
have had five or more top ten finishes
SELECT name, country, age,
top10s, earnings |
| h1c.sql | The name, country, number
of events played in, number of cuts made, and the percentage of cuts made,
ordered from the player with the highest cut percentage to the players with
the lowest cut percentage for all players from the USA
SELECT name, country, events, cutsmade, (cutsmade/events)*100 as
PercCutsMade |
| h1d.sql | A non-repeating list of
the countries that players are from.
SELECT DISTINCT country |
| h1e.sql | The average earnings for
all players.
SELECT AVG(earnings) |
| h1f.sql | The name and earnings for
all players from the USA and CANADA that have also earned more than one
million dollars.
SELECT name, earnings |
| h1g.sql | A list of countries along
with the number of players from that country and the average earnings of
players from that country.
SELECT country, count(name)
as NumPlayers, AVG(earnings) as AvgEarnings |
| h1h.sql | A list of countries along
with the number of players from that country and the average earnings of
players from that country, for those countries that have five or more
players.
SELECT country, count(name)
as NumPlayers, AVG(earnings) as AvgEarnings |
| h1i.sql | The name and earnings of
the player with the highest average drive. Do not hard code your query…
use a nesting.
SELECT name, earnings |
| h1j.sql | A list of countries and
the number of million dollar earners from that country
SELECT country, count(name)
as MillionDollarEarners |