July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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192
｜
第
9
章
➊
在我们分好组的表上调用
aggregate
方法，传递一个元组列表作为参数，其中包括新的
列名称和
agate
的聚合方法（利用新的列命名计算新列的值）。我们想要计算童工雇用
百分比的平均值和最大值，还有腐败感指数（
CPI
）得分的中位数和最小值。根据你的
问题和数据的不同，你可以使用不同的
agate
方法。
➋
打印新表，这样我们可以从视觉上直观比较数据。
当运行这段代码后，你会看到下面的结果：
|----------------+-----------------------------+--------+------------+----------|
| continent | cl_mean | cl_max | cpi_median | cpi_min |
|----------------+-----------------------------+--------+------------+----------|
| south america | 12,710000000000000000000000 | 33,5 | 36,0 | 24 |
| north america | 10,333333333333333333333333 | 25,8 | 34,5 | 19 |
| africa | 22,348780487804878048780487 | 49,0 | 30,0 | 8 |
| asia | 9,589473684210526315789473 ...
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