ch7.

7.md

@@ -581,3 +581,54 @@ lengths
 | --- | --- | --- |
 | chocolate | [ 4.75 6.55 5.25] | 3 |
 | strawberry | [ 3.55 5.25] | 2 |
+
+### 示例：NBA 薪水
+
+`nba`表包含了 2015~2016 年 NBA 球员的数据。 我们早些时候审查了这些数据。 回想一下，薪水以百万美元计算。
+
+```py
+nba1 = Table.read_table('nba_salaries.csv')
+nba = nba1.relabeled("'15-'16 SALARY", 'SALARY')
+nba
+```
+
+
+| PLAYER | POSITION | TEAM | SALARY |
+| --- | --- | --- | --- |
+| Paul Millsap | PF | Atlanta Hawks | 18.6717 |
+| Al Horford | C | Atlanta Hawks | 12 |
+| Tiago Splitter | C | Atlanta Hawks | 9.75625 |
+| Jeff Teague | PG | Atlanta Hawks | 8 |
+| Kyle Korver | SG | Atlanta Hawks | 5.74648 |
+| Thabo Sefolosha | SF | Atlanta Hawks | 4 |
+| Mike Scott | PF | Atlanta Hawks | 3.33333 |
+| Kent Bazemore | SF | Atlanta Hawks | 2 |
+| Dennis Schroder | PG | Atlanta Hawks | 1.7634 |
+| Tim Hardaway Jr. | SG | Atlanta Hawks | 1.30452 |
+
+（省略了 407 行）
+
+（1）每支球队为球员的工资支付了多少钱？
+
+唯一涉及的列是`TEAM`和`SALARY`。 我们必须按`TEAM`对这些行进行分组，然后对这些分类的工资进行求和。
+
+```py
+teams_and_money = nba.select('TEAM', 'SALARY')
+teams_and_money.group('TEAM', sum)
+```
+
+
+| TEAM | SALARY sum |
+| --- | --- |
+| Atlanta Hawks | 69.5731 |
+| Boston Celtics | 50.2855 |
+| Brooklyn Nets | 57.307 |
+| Charlotte Hornets | 84.1024 |
+| Chicago Bulls | 78.8209 |
+| Cleveland Cavaliers | 102.312 |
+| Dallas Mavericks | 65.7626 |
+| Denver Nuggets | 62.4294 |
+| Detroit Pistons | 42.2118 |
+| Golden State Warriors | 94.0851 |
+
+（省略了 20 行）