如何解决比较 R 中的三个变量并通过在 ggplot 上分组来映射它
我想比较 R 中的三个变量。我在弄清楚分析这些数据的编码时遇到了麻烦,想知道是否有人可以提供帮助。
此表查看邮政编码,按行业和类型(A、B、C、D)将它们分开。我想基本上按 zip 中的类型(A、B、C、D)总结所有值。从那里我想排除特定数字以下的所有 zip 以仅查看相关数据点。
最后 - 我试图在美国地图 ggplot 上绘制此图 - 按行业按颜色绘制所有用户...但 ggplot 不直观,我无法正确绘制点。
原始数据:https://docs.google.com/spreadsheets/d/1R1NeFTuvvhqnxG-SgABevJjPflyaG_P1btmwyD2hB-c/edit?usp=sharing
到目前为止我的代码:
ftable(body_industry$postalcode,body_industry$industry,body_industry$reclass_bodytype)
#My initial thought was to use addmargins(ftable(body_industry...)
but this doesn't seem to be working as the data set doesn't sum up properly.
Zip Industry A B C D
94801 artistic 0 0 0 0
banking 0 0 0 0
clerical 0 0 0 0
computer 0 1 0 0
construction 1 0 0 0
education 1 0 0 0
entertainment 0 0 0 0
executive 0 0 0 0
hospitality 0 0 0 0
law 0 0 0 0
medicine 0 0 0 0
military 0 0 0 0
political 0 0 0 0
retired 0 0 0 0
sales 0 0 0 1
science 0 0 0 0
student 0 0 0 0
transportation 0 0 0 0
unemployed 0 0 0 0
94803 artistic 2 2 2 1
banking 2 2 1 0
clerical 0 2 1 0
computer 0 2 0 1
construction 5 2 0 0
education 1 4 4 0
entertainment 2 2 0 0
executive 2 0 0 0
hospitality 0 2 0 0
law 2 0 1 0
medicine 2 5 3 0
military 0 1 1 0
political 1 1 0 0
retired 0 1 0 0
sales 2 5 0 0
science 2 4 0 0
student 4 0 3 1
transportation 0 1 1 0
unemployed 0 0 0 0
94804 artistic 4 10 7 2
banking 5 0 3 0
clerical 0 2 3 1
computer 7 6 5 2
construction 7 7 6 0
education 11 8 9 1
entertainment 4 1 3 1
executive 3 4 3 1
hospitality 2 7 3 0
law 2 5 0 1
medicine 9 7 6 1
military 2 2 0 0
political 3 0 1 0
retired 0 1 2 1
sales 10 6 0 2
science 10 5 3 1
student 13 15 13 5
transportation 1 1 1 0
unemployed 1 1 3 0
94806 artistic 4 2 0 2
banking 1 2 3 0
clerical 1 1 0 0
computer 4 2 2 0
construction 4 4 3 1
education 8 1 4 0
entertainment 1 0 0 0
executive 1 3 0 0
hospitality 0 2 3 0
law 1 1 2 0
medicine 4 4 2 1
military 2 2 1 0
political 1 3 0 1
retired 0 0 0 0
sales 6 6 3 0
science 3 4 2 1
student 10 5 6 2
transportation 3 2 2 0
unemployed 0 1 3 1
94901 artistic 22 9 13 7
banking 20 10 6 1
clerical 2 0 5 1
computer 21 12 4 6
construction 18 2 1 0
education 18 17 14 3
entertainment 11 7 3 0
executive 13 4 3 5
hospitality 7 4 2 0
law 5 4 4 0
medicine 28 18 12 3
military 0 0 0 0
political 3 3 0 0
retired 4 2 3 1
sales 27 13 9 3
science 15 1 4 0
student 10 18 5 10
transportation 0 0 2 0
unemployed 0 1 2 1
94904 artistic 4 1 0 1
banking 7 3 1 0
clerical 0 1 0 0
computer 1 2 1 0
construction 1 0 0 0
education 1 2 1 1
entertainment 0 0 1 0
executive 5 5 0 0
hospitality 1 0 0 0
law 0 1 0 1
medicine 5 3 3 1
military 0 0 0 0
political 1 0 0 0
retired 0 0 0 0
sales 5 2 1 0
science 5 1 2 0
student 0 2 0 0
transportation 0 0 0 0
unemployed 0 0 0 0
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