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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18
｜
第
1
章
pandas
为数据框对象提供了多种基本的探索性统计图，箱线图就是其中之一。
ax = (state['Population']/1_000_000).plot.box()
ax.set_ylabel('Population (millions)')
从图
1-2
中我们可以立刻看出，美国各州人口的中位数大约是
500
万，有一半的州的人
口大致在
200
万和
700
万之间
，还有一些人口特别多的离群值。箱子的顶部和底部分别
是第
75
个百
分位数和第
25
个百分位数，箱子中的横线表示中位数。两条虚线称为
须
（
whisker
）
，分别从箱子的顶部和底部延伸出去，表示数据的极差。箱线图有多种变体，在
R
函数
boxplot
的文档
[R-base-2015]
中有一些例子。默认情况下，这个
R
函数可以将须延
伸到箱子外面最远的点，除非它超过了
1.5
倍的四分位距
。
Matplotlib
使用了同样的实现方
式，但其他软件可能使用了不同的规则。
所有在须之外的数据都被绘制为一个单独的点或圆圈（通常被看作离群点）。
1.5.2
频数表和直方图
一个变量的频数表将变量范围分为多个段，每个段的间隔相等，它可以表示出每个段中有
多少个变量值。表
1-5
给出了
R
语言中一个表示美国各州人口分布的频数表。
breaks <- seq(from=min(state[['Population']]),
to=max(state[['Population']]), length=11)
pop_freq <- cut(state[['Population']], ...
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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.