October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Content preview from 数据科学中的实用统计学(第2版)
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探索性数据分析
｜
35
ggplot(data=airline_stats, aes(airline, pct_carrier_delay)) +
ylim(0, 50) +
geom_violin() +
labs(x='', y='Daily % of Delayed Flights')
seaborn
包的
violinplot
方法也可以生成小提琴图：
ax = sns.violinplot(airline_stats.airline, airline_stats.pct_carrier_delay,
inner='quartile', color='white')
ax.set_xlabel('')
ax.set_ylabel('Daily % of Delayed Flights')
得到的图形为图
1-11
。如图所示，阿拉斯加航空公司的数据分布集中在
0
附近，其次是达
美（
Delta
）航空公司
。这种现象在箱线图中就没有这么明显。你可以在绘图中添加
geom_
boxplot
命令，将小提琴图与箱线图结合（给图片着色的话，效果最好）。
图 1-11：由于航空公司控制所导致的航班延误百分比的小提琴图
1.8.4
多个变量的可视化
通过
条件
（
conditioning
）这个概念，可以轻松地将用来比较两个变量的图表类型——散点
图、六边形分箱图和箱线图——推广到多个变量的比较。例如，图
1-8
展示
了房屋面积与
应纳税额之间的关系。我们观察到，一部分房屋具有更高的每平方英尺应纳税额。研究得
更深入一些会发现，图
1-12 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.