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
｜
33
Grade Charged off Current Fully paid Late Total
C 6023 88 928 23 147 2777 120 875
0.050 0.736 0.191 0.023 0.268
D 5007 53 281 13 681 2308 74 277
0.067 0.717 0.184 0.031 0.165
E 2842 24 639 5949 1374 34 804
0.082 0.708 0.171 0.039 0.077
F 1526 8444 2328 606 12 904
0.118 0.654 0.180 0.047 0.029
G 409 1990 643 199 3241
0.126 0.614 0.198 0.061 0.007
Total 22 671 321 185 97 316 9789 450 961
列联表可以只包含计数，也可以包含列百分比和总数百分比。
Excel
的数据透视表可能是
最常用的列联表创建工具。在
R
中，
descr
包中的
CrossTable
函数可以生成列联表。用来
创建表
1-8
的代码如下：
library(descr)
x_tab <- CrossTable(lc_loans$grade, lc_loans$status,
prop.c=FALSE, prop.chisq=FALSE, prop.t=FALSE)
在
Python
中，
pivot_table
方法可以创建数据透视表。使用
aggfunc
参数可以得到计数 ...
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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.