August 2022
Beginner to intermediate
463 pages
9h 22m
Chinese
Content preview from Tableau Prep即学即用
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94
｜
第
11
章
•
重复的记录：重复记录是在数据准备之前，还是在这个过程的前几个步骤中产
生的？
•
丢失的数据：是否有某些值没有出现在数据集中，但应该有？是否在你期望值
的地方存在空值？
如果你有很多数据集，检查所有这些因素可能会相当耗时，但有一些方法可以使这
项任务变得更容易和更直观。
11.2
为什么可视化数据集很重要
进行数据集概要分析，最重要的策略之一是可视化。
11.2.1
安斯库姆四要素
如果你读过任何关于数据可视化的书籍，那么你很可能已经看到了
Anscombe
（安
斯库姆）的要素，这是对为什么描述性统计（最小值、最大值、平均值等）不足以
理解数据集中的真实情况的最好论证。
1973
年，
Francis Anscombe
构建了四个由
x
和
y
值对组成的数据集（见图
11-1
）。
图
11
-
1
：Anscombe 的数据集
｜
95
数据概要分析
从图
11-1
中可以看出，数值范围很大，但四组数据的描述性统计信息基本相同，即：
•
均值：
x
=9
，
y
=7.5
。
•
样本方差：
x
＝
11
，
y
＝
4.5
。
•
相关性、线性回归、确定系数都类似于小数点后两三位。
然而，当把每一组的各个数据点进行可视化展示时，我们可以看到，这些数据集实
际上是非常不同的（见图
11-2
）。
图
11
-
2
：安斯库姆的可视化展示
因此，为了充分准备数据，你必须用一些基本的方式将数据可视化──此时还不一 ...
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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.