ggplot2 上的堆积条形图显示错误数据
[英]Stacked bar chart on ggplot2 presenting wrong data
问题描述
SOLVED: the issue was that the classes were set as characters rather than factor/numeric
已解决：问题是类被设置为字符而不是因子/数字
I am trying to make a stacked bar chart from a long format data frame which I've created.我正在尝试从我创建的长格式数据框制作堆积条形图。 The bar chart does come up correctly format wise but the data is incorrect to what is in the data frame.条形图确实以正确的格式出现，但数据与数据框中的数据不正确。 Here is my data:这是我的数据：
1 Macrolides X3 2.85
2 Penicillins X3 6.64
3 Cephalosporins X3 1.70
4 Quinolones X3 1.36
5 Tetracyclines X3 1.19
6 Macrolides Belgium 2.62
7 Penicillins Belgium 16.28
8 Cephalosporins Belgium 1.59
9 Quinolones Belgium 2.69
10 Tetracyclines Belgium 2.10
11 Macrolides Bulgaria 2.49
12 Penicillins Bulgaria 8.05
13 Cephalosporins Bulgaria 2.32
14 Quinolones Bulgaria 1.99
15 Tetracyclines Bulgaria 1.71
16 Macrolides Cyprus 2.86
17 Penicillins Cyprus 14.43
18 Cephalosporins Cyprus 5.41
19 Quinolones Cyprus 4.10
20 Tetracyclines Cyprus 3.27
21 Macrolides Czech 3.25
22 Penicillins Czech 7.60
23 Cephalosporins Czech 1.62
24 Quinolones Czech 1.22
25 Tetracyclines Czech 2.27
26 Macrolides Denmark 2.34
27 Penicillins Denmark 10.29
28 Cephalosporins Denmark 0.03
29 Quinolones Denmark 0.51
30 Tetracyclines Denmark 1.70
31 Macrolides Estonia 2.06
32 Penicillins Estonia 4.22
33 Cephalosporins Estonia 0.88
34 Quinolones Estonia 0.81
35 Tetracyclines Estonia 1.89
36 Macrolides Finland 1.23
37 Penicillins Finland 6.61
38 Cephalosporins Finland 2.33
39 Quinolones Finland 0.88
40 Tetracyclines Finland 4.09
41 Macrolides France 2.63
42 Penicillins France 15.62
43 Cephalosporins France 2.67
44 Quinolones France 2.00
45 Tetracyclines France 3.16
46 Macrolides Germany 2.09
47 Penicillins Germany 4.10
48 Cephalosporins Germany 2.61
49 Quinolones Germany 1.51
50 Tetracyclines Germany 2.74
51 Macrolides Greece 8.55
52 Penicillins Greece 12.87
53 Cephalosporins Greece 8.91
54 Quinolones Greece 2.89
55 Tetracyclines Greece 2.31
56 Macrolides Hungary 2.42
57 Penicillins Hungary 6.69
58 Cephalosporins Hungary 1.92
59 Quinolones Hungary 1.97
60 Tetracyclines Hungary 1.38
61 Macrolides Iceland 1.40
62 Penicillins Iceland 12.08
63 Cephalosporins Iceland 0.62
64 Quinolones Iceland 1.02
65 Tetracyclines Iceland 5.05
66 Macrolides Ireland 3.63
67 Penicillins Ireland 10.65
68 Cephalosporins Ireland 1.21
69 Quinolones Ireland 0.91
70 Tetracyclines Ireland 2.60
71 Macrolides Italy 4.98
72 Penicillins Italy 14.55
73 Cephalosporins Italy 2.55
74 Quinolones Italy 3.45
75 Tetracyclines Italy 0.53
76 Macrolides Lativa 1.03
77 Penicillins Lativa 5.59
78 Cephalosporins Lativa 0.57
79 Quinolones Lativa 0.91
80 Tetracyclines Lativa 2.38
81 Macrolides Lithuania 1.44
82 Penicillins Lithuania 6.99
83 Cephalosporins Lithuania 0.80
84 Quinolones Lithuania 0.83
85 Tetracyclines Lithuania 1.38
86 Macrolides Luxembourg 3.46
87 Penicillins Luxembourg 13.96
88 Cephalosporins Luxembourg 4.18
89 Quinolones Luxembourg 2.94
90 Tetracyclines Luxembourg 2.04
91 Macrolides Malta 2.97
92 Penicillins Malta 9.80
93 Cephalosporins Malta 5.04
94 Quinolones Malta 1.79
95 Tetracyclines Malta 1.02
96 Macrolides Netherlands 1.31
97 Penicillins Netherlands 4.36
98 Cephalosporins Netherlands 0.04
99 Quinolones Netherlands 0.87
100 Tetracyclines Netherlands 2.66
101 Macrolides Norway 1.55
102 Penicillins Norway 6.77
103 Cephalosporins Norway 0.12
104 Quinolones Norway 0.54
105 Tetracyclines Norway 2.77
106 Macrolides Poland 2.89
107 Penicillins Poland 9.43
108 Cephalosporins Poland 2.44
109 Quinolones Poland 1.23
110 Tetracyclines Poland 2.10
111 Macrolides Portugal 3.37
112 Penicillins Portugal 12.08
113 Cephalosporins Portugal 1.81
114 Quinolones Portugal 2.97
115 Tetracyclines Portugal 0.71
116 Macrolides Slovenia 1.89
117 Penicillins Slovenia 9.67
118 Cephalosporins Slovenia 0.40
119 Quinolones Slovenia 1.10
120 Tetracyclines Slovenia 0.04
121 Macrolides Spain 1.88
122 Penicillins Spain 12.64
123 Cephalosporins Spain 1.56
124 Quinolones Spain 2.54
125 Tetracyclines Spain 0.70
126 Macrolides Sweden 0.43
127 Penicillins Sweden 7.09
128 Cephalosporins Sweden 0.20
129 Quinolones Sweden 0.77
130 Tetracyclines Sweden 3.33
131 Macrolides UK 2.71
132 Penicillins UK 8.60
133 Cephalosporins UK 0.55
134 Quinolones UK 0.46
135 Tetracyclines UK 4.15
This is the code for how I made the bar chart and a picture of it.这是我如何制作条形图和它的图片的代码。 As you can see the proportions in the chart are incorrect, eg The values for Penicillin use is very high compared the rest of the antibiotics but this isn't shown on my chart.如您所见，图表中的比例是不正确的，例如，与其他抗生素相比，青霉素的使用值非常高，但这并未显示在我的图表中。 I'm not sure what I've done incorrectly.我不确定我做错了什么。
barchart <- ggplot(data=chart.new, aes(x = Country, y = DailyDosage, fill = Group, group = Group)) +
geom_bar(stat = "identity") +
coord_flip() +
scale_fill_manual(values = cbPalette) +
labs(title = "Antibiotic Consumption by Group ") +
theme(legend.position = "top")
1 个解决方案
解决方案1
2 已采纳 2020-01-06 20:55:16
Similar to @DaveGruenewald, I got the correct values using your code and data.与@DaveGruenewald 类似，我使用您的代码和数据获得了正确的值。 I noticed you had theme(legend.position = "top") while you showed a plot with legend on the side.我注意到你有 theme(legend.position = "top") 而你展示了一个带有图例的情节。 Is it the same code, for reference you can try what I have below.它是相同的代码，作为参考，您可以尝试我下面的代码。
What I used from your table above:我从上表中使用的内容：
chart.new=dput(chart.new)
structure(list(Group = structure(c(2L, 3L, 1L, 4L, 5L, 2L, 3L,
1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L,
4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L,
5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L,
2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L,
3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L,
1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L,
4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L,
5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L, 2L, 3L, 1L, 4L, 5L
), .Label = c("Cephalosporins", "Macrolides", "Penicillins",
"Quinolones", "Tetracyclines"), class = "factor"), Country = structure(c(27L,
27L, 27L, 27L, 27L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L,
6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L,
9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 12L,
12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L,
14L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 17L, 17L,
17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 19L,
20L, 20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 21L, 22L, 22L, 22L,
22L, 22L, 23L, 23L, 23L, 23L, 23L, 24L, 24L, 24L, 24L, 24L, 25L,
25L, 25L, 25L, 25L, 26L, 26L, 26L, 26L, 26L), .Label = c("Belgium",
"Bulgaria", "Cyprus", "Czech", "Denmark", "Estonia", "Finland",
"France", "Germany", "Greece", "Hungary", "Iceland", "Ireland",
"Italy", "Lativa", "Lithuania", "Luxembourg", "Malta", "Netherlands",
"Norway", "Poland", "Portugal", "Slovenia", "Spain", "Sweden",
"UK", "X3"), class = "factor"), DailyDosage = c(2.85, 6.64, 1.7,
1.36, 1.19, 2.62, 16.28, 1.59, 2.69, 2.1, 2.49, 8.05, 2.32, 1.99,
1.71, 2.86, 14.43, 5.41, 4.1, 3.27, 3.25, 7.6, 1.62, 1.22, 2.27,
2.34, 10.29, 0.03, 0.51, 1.7, 2.06, 4.22, 0.88, 0.81, 1.89, 1.23,
6.61, 2.33, 0.88, 4.09, 2.63, 15.62, 2.67, 2, 3.16, 2.09, 4.1,
2.61, 1.51, 2.74, 8.55, 12.87, 8.91, 2.89, 2.31, 2.42, 6.69,
1.92, 1.97, 1.38, 1.4, 12.08, 0.62, 1.02, 5.05, 3.63, 10.65,
1.21, 0.91, 2.6, 4.98, 14.55, 2.55, 3.45, 0.53, 1.03, 5.59, 0.57,
0.91, 2.38, 1.44, 6.99, 0.8, 0.83, 1.38, 3.46, 13.96, 4.18, 2.94,
2.04, 2.97, 9.8, 5.04, 1.79, 1.02, 1.31, 4.36, 0.04, 0.87, 2.66,
1.55, 6.77, 0.12, 0.54, 2.77, 2.89, 9.43, 2.44, 1.23, 2.1, 3.37,
12.08, 1.81, 2.97, 0.71, 1.89, 9.67, 0.4, 1.1, 0.04, 1.88, 12.64,
1.56, 2.54, 0.7, 0.43, 7.09, 0.2, 0.77, 3.33, 2.71, 8.6, 0.55,
0.46, 4.15)), class = "data.frame", row.names = c(NA, 135L))
Checking chart.new:检查 chart.new：
str(chart.new)
'data.frame': 135 obs. of 3 variables:
$ Group : Factor w/ 5 levels "Cephalosporins",..: 2 3 1 4 5 2 3 1 4 5 ...
$ Country : Factor w/ 27 levels "Belgium","Bulgaria",..: 27 27 27 27 27 1 1 1 1 1 ...
$ DailyDosage: num 2.85 6.64 1.7 1.36 1.19 ...
Using the default colors:使用默认颜色：
ggplot(data=chart.new ,aes(x = Country, y = DailyDosage, fill = Group, group = Group))+
geom_bar(stat = "identity")+ coord_flip() +
labs(title = "Antibiotic Consumption by Group ")+
theme(legend.position = "top")
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