R 如何使用ggplot2从一组宽数据生成堆叠条形图？
我有以下数据集：R 如何使用ggplot2从一组宽数据生成堆叠条形图？,r,ggplot2,R,Ggplot2,我有以下数据集： Date Treatment Precipitation Irrigation ET Leaching 1 5/1/2018 100% 1.4732 0.000 0.0000 1.4732 2 5/1/2018 125% 1.4732 0.000 0.0000 1.4732 3 5/1/2018 75% 1.4732 0.000 0.0000
Date Treatment Precipitation Irrigation ET Leaching
1 5/1/2018 100% 1.4732 0.000 0.0000 1.4732
2 5/1/2018 125% 1.4732 0.000 0.0000 1.4732
3 5/1/2018 75% 1.4732 0.000 0.0000 1.4732
4 5/1/2018 50% 1.4732 0.000 0.0000 1.4732
5 5/2/2018 100% 0.0000 0.000 0.0000 0.0000
6 5/2/2018 125% 0.0000 0.000 0.0000 0.0000
7 5/2/2018 75% 0.0000 0.000 0.0000 0.0000
8 5/2/2018 50% 0.0000 0.000 0.0000 0.0000
9 5/3/2018 100% 1.5240 0.000 0.0000 1.5240
10 5/3/2018 125% 1.5240 0.000 0.0000 1.5240
11 5/3/2018 75% 1.5240 0.000 0.0000 1.5240
12 5/3/2018 50% 1.5240 0.000 0.0000 1.5240
13 5/4/2018 100% 2.3368 0.000 0.0000 2.3368
14 5/4/2018 125% 2.3368 0.000 0.0000 2.3368
15 5/4/2018 75% 2.3368 0.000 0.0000 2.3368
16 5/4/2018 50% 2.3368 0.000 0.0000 2.3368
17 5/5/2018 100% 0.0000 0.000 0.0000 0.0000
18 5/5/2018 125% 0.0000 0.000 0.0000 0.0000
19 5/5/2018 75% 0.0000 0.000 0.0000 0.0000
20 5/5/2018 50% 0.0000 0.000 0.0000 0.0000
21 5/6/2018 100% 0.7620 0.000 0.0000 0.7620
22 5/6/2018 125% 0.7620 0.000 0.0000 0.7620
23 5/6/2018 75% 0.7620 0.000 0.0000 0.7620
24 5/6/2018 50% 0.7620 0.000 0.0000 0.7620
25 5/7/2018 100% 0.0000 0.000 0.0000 0.0000
26 5/7/2018 125% 0.0000 0.000 0.0000 0.0000
27 5/7/2018 75% 0.0000 0.000 0.0000 0.0000
28 5/7/2018 50% 0.0000 0.000 0.0000 0.0000
29 5/8/2018 100% 0.0000 0.000 0.0000 0.0000
30 5/8/2018 125% 0.0000 0.000 0.0000 0.0000
31 5/8/2018 75% 0.0000 0.000 0.0000 0.0000
32 5/8/2018 50% 0.0000 0.000 0.0000 0.0000
33 5/9/2018 100% 3.3020 0.000 0.0000 3.3020
34 5/9/2018 125% 3.3020 0.000 0.0000 3.3020
35 5/9/2018 75% 3.3020 0.000 0.0000 3.3020
36 5/9/2018 50% 3.3020 0.000 0.0000 3.3020
37 5/10/2018 100% 0.0000 0.000 0.0000 0.0000
38 5/10/2018 125% 0.0000 0.000 0.0000 0.0000
39 5/10/2018 75% 0.0000 0.000 0.0000 0.0000
40 5/10/2018 50% 0.0000 0.000 0.0000 0.0000
41 5/11/2018 100% 0.9906 0.000 0.0000 0.9906
42 5/11/2018 125% 0.9906 0.000 0.0000 0.9906
43 5/11/2018 75% 0.9906 0.000 0.0000 0.9906
44 5/11/2018 50% 0.9906 0.000 0.0000 0.9906
45 5/12/2018 100% 0.0000 0.000 0.0000 0.0000
46 5/12/2018 125% 0.0000 0.000 0.0000 0.0000
47 5/12/2018 75% 0.0000 0.000 0.0000 0.0000
48 5/12/2018 50% 0.0000 0.000 0.0000 0.0000
49 5/13/2018 100% 0.0000 0.000 0.0000 0.0000
50 5/13/2018 125% 0.0000 0.000 0.0000 0.0000
51 5/13/2018 75% 0.0000 0.000 0.0000 0.0000
52 5/13/2018 50% 0.0000 0.000 0.0000 0.0000
53 5/14/2018 100% 0.3048 0.000 0.0000 0.3048
54 5/14/2018 125% 0.3048 0.000 0.0000 0.3048
55 5/14/2018 75% 0.3048 0.000 0.0000 0.3048
56 5/14/2018 50% 0.3048 0.000 0.0000 0.3048
57 5/15/2018 100% 0.0000 0.000 0.0000 0.0000
58 5/15/2018 125% 0.0000 0.000 0.0000 0.0000
59 5/15/2018 75% 0.0000 0.000 0.0000 0.0000
60 5/15/2018 50% 0.0000 0.000 0.0000 0.0000
61 5/16/2018 100% 0.0000 0.000 0.0000 0.0000
62 5/16/2018 125% 0.0000 0.000 0.0000 0.0000
63 5/16/2018 75% 0.0000 0.000 0.0000 0.0000
64 5/16/2018 50% 0.0000 0.000 0.0000 0.0000
65 5/17/2018 100% 0.0000 0.762 0.0000 0.7620
66 5/17/2018 125% 0.0000 0.762 0.0000 0.7620
67 5/17/2018 75% 0.0000 0.762 0.0000 0.7620
68 5/17/2018 50% 0.0000 0.762 0.0000 0.7620
69 5/18/2018 100% 0.0000 0.000 0.0000 0.0000
70 5/18/2018 125% 0.0000 0.000 0.0000 0.0000
71 5/18/2018 75% 0.0000 0.000 0.0000 0.0000
72 5/18/2018 50% 0.0000 0.000 0.0000 0.0000
73 5/19/2018 100% 0.0000 0.000 0.0000 0.0000
74 5/19/2018 125% 0.0000 0.000 0.0000 0.0000
75 5/19/2018 75% 0.0000 0.000 0.0000 0.0000
76 5/19/2018 50% 0.0000 0.000 0.0000 0.0000
77 5/20/2018 100% 0.0000 0.762 0.3048 0.4572
78 5/20/2018 125% 0.0000 0.762 0.3048 0.4572
79 5/20/2018 75% 0.0000 0.762 0.3048 0.4572
80 5/20/2018 50% 0.0000 0.762 0.3048 0.4572
81 5/21/2018 100% 0.0000 0.000 0.1016 0.0000
82 5/21/2018 125% 0.0000 0.000 0.1016 0.0000
83 5/21/2018 75% 0.0000 0.000 0.1016 0.0000
84 5/21/2018 50% 0.0000 0.000 0.1016 0.0000
85 5/22/2018 100% 0.0000 0.000 0.2794 0.0000
86 5/22/2018 125% 0.0000 0.000 0.2794 0.0000
87 5/22/2018 75% 0.0000 0.000 0.2794 0.0000
88 5/22/2018 50% 0.0000 0.000 0.2794 0.0000
89 5/23/2018 100% 0.0000 0.000 0.3810 0.0000
90 5/23/2018 125% 0.0000 0.000 0.3810 0.0000
91 5/23/2018 75% 0.0000 0.000 0.3810 0.0000
92 5/23/2018 50% 0.0000 0.000 0.3810 0.0000
93 5/24/2018 100% 0.0000 0.000 0.3080 0.0000
94 5/24/2018 125% 0.0000 0.000 0.3080 0.0000
95 5/24/2018 75% 0.0000 0.000 0.3080 0.0000
96 5/24/2018 50% 0.0000 0.000 0.3080 0.0000
97 5/25/2018 100% 0.0000 1.016 0.3572 0.0000
98 5/25/2018 125% 0.0000 1.016 0.3572 0.0000
99 5/25/2018 75% 0.0000 1.016 0.3572 0.0000
100 5/25/2018 50% 0.0000 1.016 0.3572 0.0000
101 5/26/2018 100% 0.0000 0.000 0.4588 0.0000
102 5/26/2018 125% 0.0000 0.000 0.4588 0.0000
103 5/26/2018 75% 0.0000 0.000 0.4588 0.0000
104 5/26/2018 50% 0.0000 0.000 0.4588 0.0000
105 5/27/2018 100% 0.0000 1.016 0.5842 0.0000
106 5/27/2018 125% 0.0000 1.016 0.5842 0.0000
107 5/27/2018 75% 0.0000 1.016 0.5842 0.0000
108 5/27/2018 50% 0.0000 1.016 0.5842 0.0000
109 5/28/2018 100% 0.0000 0.000 0.4064 0.0000
110 5/28/2018 125% 0.0000 0.000 0.4064 0.0000
111 5/28/2018 75% 0.0000 0.000 0.4064 0.0000
112 5/28/2018 50% 0.0000 0.000 0.4064 0.0000
113 5/29/2018 100% 0.0000 0.635 0.5334 0.0000
114 5/29/2018 125% 0.0000 0.635 0.5334 0.0000
115 5/29/2018 75% 0.0000 0.635 0.5334 0.0000
116 5/29/2018 50% 0.0000 0.635 0.5334 0.0000
117 5/30/2018 100% 0.0000 0.000 0.1270 0.0000
118 5/30/2018 125% 0.0000 0.000 0.1270 0.0000
119 5/30/2018 75% 0.0000 0.000 0.1270 0.0000
120 5/30/2018 50% 0.0000 0.000 0.1270 0.0000
121 5/31/2018 100% 0.0000 0.000 0.4064 0.0000
122 5/31/2018 125% 0.0000 0.000 0.4064 0.0000
123 5/31/2018 75% 0.0000 0.000 0.4064 0.0000
124 5/31/2018 50% 0.0000 0.000 0.4064 0.0000
125 6/1/2018 100% 0.0000 0.000 0.3810 0.0000
126 6/1/2018 125% 0.0000 0.000 0.3810 0.0000
127 6/1/2018 75% 0.0000 0.000 0.3810 0.0000
128 6/1/2018 50% 0.0000 0.000 0.3810 0.0000
129 6/2/2018 100% 0.7366 0.000 0.1270 0.0000
130 6/2/2018 125% 0.7366 0.000 0.1270 0.0000
131 6/2/2018 75% 0.7366 0.000 0.1270 0.0000
132 6/2/2018 50% 0.7366 0.000 0.1270 0.0000
133 6/3/2018 100% 0.0762 0.000 0.2032 0.0000
134 6/3/2018 125% 0.0762 0.000 0.2032 0.0000
135 6/3/2018 75% 0.0762 0.000 0.2032 0.0000
136 6/3/2018 50% 0.0762 0.000 0.2032 0.0000
137 6/4/2018 100% 0.0000 0.000 0.4572 0.0000
138 6/4/2018 125% 0.0000 0.000 0.4572 0.0000
139 6/4/2018 75% 0.0000 0.000 0.4572 0.0000
140 6/4/2018 50% 0.0000 0.000 0.4572 0.0000
141 6/5/2018 100% 0.7112 0.000 0.4572 0.0000
142 6/5/2018 125% 0.7112 0.000 0.4572 0.0000
143 6/5/2018 75% 0.7112 0.000 0.4572 0.0000
144 6/5/2018 50% 0.7112 0.000 0.4572 0.0000
145 6/6/2018 100% 0.0000 0.762 0.2794 0.0000
146 6/6/2018 125% 0.0000 0.762 0.2794 0.0000
147 6/6/2018 75% 0.0000 0.762 0.2794 0.0000
148 6/6/2018 50% 0.0000 0.762 0.2794 0.0000
149 6/7/2018 100% 0.2032 0.000 0.5080 0.0000
150 6/7/2018 125% 0.2032 0.000 0.5080 0.0000
151 6/7/2018 75% 0.2032 0.000 0.5080 0.0000
152 6/7/2018 50% 0.2032 0.000 0.5080 0.0000
153 6/8/2018 100% 0.1270 1.016 0.2286 0.0000
154 6/8/2018 125% 0.1270 1.016 0.2286 0.0000
155 6/8/2018 75% 0.1270 1.016 0.2286 0.0000
156 6/8/2018 50% 0.1270 1.016 0.2286 0.0000
157 6/9/2018 100% 0.0000 0.000 0.4064 0.0000
158 6/9/2018 125% 0.0000 0.000 0.4064 0.0000
159 6/9/2018 75% 0.0000 0.000 0.4064 0.0000
160 6/9/2018 50% 0.0000 0.000 0.4064 0.0000
161 6/10/2018 100% 0.0000 0.000 0.2286 0.0000
162 6/10/2018 125% 0.0000 0.000 0.2286 0.0000
163 6/10/2018 75% 0.0000 0.000 0.2286 0.0000
164 6/10/2018 50% 0.0000 0.000 0.2286 0.0000
165 6/11/2018 100% 0.0000 1.016 0.4572 0.0000
166 6/11/2018 125% 0.0000 1.016 0.4572 0.0000
ggplot(data, aes(fill="response source"", y=response, x=date)) +
geom_bar(position="fill", stat="identity")
提前感谢您提供的任何帮助，如果我在帖子中出错，需要更改任何内容，请告诉我。因为我对堆栈溢出非常缺乏经验。我们可以使用
pivot\u longerlibrary(dplyr)
library(tidyr)
library(lubridate)
library(ggplot2)
df1 %>%
mutate(Date = mdy(Date)) %>%
pivot_longer(cols = Precipitation:Leaching,
names_to = "response_source", values_to = "response") %>%
ggplot(aes(fill= response_source, y=response, x=Date)) +
geom_bar(position="fill", stat="identity")
df1非常感谢您！我不知道这是可能的。我按照您编写的方式运行代码，但得到的响应是，尽管加载了tidyr，但我找不到函数“pivot_longer”。我在这里做错了什么吗？@Trev你加载了library（tidyr）
如果是，你能检查一下packageVersion（'tidyr'）
，如果你有一个旧版本的tidyr
，可能会重新安装新版本的tidyr谢谢@akrun。这就解决了问题，尽管代码仍然不适用于我。当我尝试只更改数据集而不进行ggplot时，我得到错误“error:Unknown columnresponse\u source
Callrlang:：last\u error（）
以查看回溯”。你知道为什么会发生这种情况吗？@Trev我在pivot\u longer
中创建了这个列，即df1%>%mutate（Date=mdy（Date））%%>%pivot\u longer（cols=deposition:learch，names\u to=“response\u source”，values\u to=“response”）
你能在这一步之后检查一下列名吗我的错误，看来我只是错误地更新了软件包。现在一切正常，再次感谢您抽出时间来帮助我！
df1 <- structure(list(Date = c("5/1/2018", "5/1/2018", "5/1/2018", "5/1/2018",
"5/2/2018", "5/2/2018", "5/2/2018", "5/2/2018", "5/3/2018", "5/3/2018",
"5/3/2018", "5/3/2018", "5/4/2018", "5/4/2018", "5/4/2018", "5/4/2018",
"5/5/2018", "5/5/2018", "5/5/2018", "5/5/2018", "5/6/2018", "5/6/2018",
"5/6/2018", "5/6/2018", "5/7/2018", "5/7/2018", "5/7/2018", "5/7/2018",
"5/8/2018", "5/8/2018", "5/8/2018", "5/8/2018", "5/9/2018", "5/9/2018",
"5/9/2018", "5/9/2018", "5/10/2018", "5/10/2018", "5/10/2018",
"5/10/2018", "5/11/2018", "5/11/2018", "5/11/2018", "5/11/2018",
"5/12/2018", "5/12/2018", "5/12/2018", "5/12/2018", "5/13/2018",
"5/13/2018", "5/13/2018", "5/13/2018", "5/14/2018", "5/14/2018",
"5/14/2018", "5/14/2018", "5/15/2018", "5/15/2018", "5/15/2018",
"5/15/2018", "5/16/2018", "5/16/2018", "5/16/2018", "5/16/2018",
"5/17/2018", "5/17/2018", "5/17/2018", "5/17/2018", "5/18/2018",
"5/18/2018", "5/18/2018", "5/18/2018", "5/19/2018", "5/19/2018",
"5/19/2018", "5/19/2018", "5/20/2018", "5/20/2018", "5/20/2018",
"5/20/2018", "5/21/2018", "5/21/2018", "5/21/2018", "5/21/2018",
"5/22/2018", "5/22/2018", "5/22/2018", "5/22/2018", "5/23/2018",
"5/23/2018", "5/23/2018", "5/23/2018", "5/24/2018", "5/24/2018",
"5/24/2018", "5/24/2018", "5/25/2018", "5/25/2018", "5/25/2018",
"5/25/2018", "5/26/2018", "5/26/2018", "5/26/2018", "5/26/2018",
"5/27/2018", "5/27/2018", "5/27/2018", "5/27/2018", "5/28/2018",
"5/28/2018", "5/28/2018", "5/28/2018", "5/29/2018", "5/29/2018",
"5/29/2018", "5/29/2018", "5/30/2018", "5/30/2018", "5/30/2018",
"5/30/2018", "5/31/2018", "5/31/2018", "5/31/2018", "5/31/2018",
"6/1/2018", "6/1/2018", "6/1/2018", "6/1/2018", "6/2/2018", "6/2/2018",
"6/2/2018", "6/2/2018", "6/3/2018", "6/3/2018", "6/3/2018", "6/3/2018",
"6/4/2018", "6/4/2018", "6/4/2018", "6/4/2018", "6/5/2018", "6/5/2018",
"6/5/2018", "6/5/2018", "6/6/2018", "6/6/2018", "6/6/2018", "6/6/2018",
"6/7/2018", "6/7/2018", "6/7/2018", "6/7/2018", "6/8/2018", "6/8/2018",
"6/8/2018", "6/8/2018", "6/9/2018", "6/9/2018", "6/9/2018", "6/9/2018",
"6/10/2018", "6/10/2018", "6/10/2018", "6/10/2018", "6/11/2018"
), Treatment = c("100%", "125%", "75%", "50%", "100%", "125%",
"75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%",
"50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%",
"100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%",
"125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%",
"75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%",
"50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%",
"100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%",
"125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%",
"75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%",
"50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%",
"100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%",
"125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%",
"75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%",
"50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%",
"100%", "125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%",
"125%", "75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%",
"75%", "50%", "100%", "125%", "75%", "50%", "100%", "125%", "75%",
"50%", "100%", "125%", "75%", "50%", "100%"), Precipitation = c(1.4732,
1.4732, 1.4732, 1.4732, 0, 0, 0, 0, 1.524, 1.524, 1.524, 1.524,
2.3368, 2.3368, 2.3368, 2.3368, 0, 0, 0, 0, 0.762, 0.762, 0.762,
0.762, 0, 0, 0, 0, 0, 0, 0, 0, 3.302, 3.302, 3.302, 3.302, 0,
0, 0, 0, 0.9906, 0.9906, 0.9906, 0.9906, 0, 0, 0, 0, 0, 0, 0,
0, 0.3048, 0.3048, 0.3048, 0.3048, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.7366, 0.7366, 0.7366, 0.7366, 0.0762, 0.0762, 0.0762, 0.0762,
0, 0, 0, 0, 0.7112, 0.7112, 0.7112, 0.7112, 0, 0, 0, 0, 0.2032,
0.2032, 0.2032, 0.2032, 0.127, 0.127, 0.127, 0.127, 0, 0, 0,
0, 0, 0, 0, 0, 0), Irrigation = c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.762, 0.762, 0.762, 0.762,
0, 0, 0, 0, 0, 0, 0, 0, 0.762, 0.762, 0.762, 0.762, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.016, 1.016, 1.016, 1.016,
0, 0, 0, 0, 1.016, 1.016, 1.016, 1.016, 0, 0, 0, 0, 0.635, 0.635,
0.635, 0.635, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.762, 0.762, 0.762, 0.762,
0, 0, 0, 0, 1.016, 1.016, 1.016, 1.016, 0, 0, 0, 0, 0, 0, 0,
0, 1.016), ET = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.3048,
0.3048, 0.3048, 0.3048, 0.1016, 0.1016, 0.1016, 0.1016, 0.2794,
0.2794, 0.2794, 0.2794, 0.381, 0.381, 0.381, 0.381, 0.308, 0.308,
0.308, 0.308, 0.3572, 0.3572, 0.3572, 0.3572, 0.4588, 0.4588,
0.4588, 0.4588, 0.5842, 0.5842, 0.5842, 0.5842, 0.4064, 0.4064,
0.4064, 0.4064, 0.5334, 0.5334, 0.5334, 0.5334, 0.127, 0.127,
0.127, 0.127, 0.4064, 0.4064, 0.4064, 0.4064, 0.381, 0.381, 0.381,
0.381, 0.127, 0.127, 0.127, 0.127, 0.2032, 0.2032, 0.2032, 0.2032,
0.4572, 0.4572, 0.4572, 0.4572, 0.4572, 0.4572, 0.4572, 0.4572,
0.2794, 0.2794, 0.2794, 0.2794, 0.508, 0.508, 0.508, 0.508, 0.2286,
0.2286, 0.2286, 0.2286, 0.4064, 0.4064, 0.4064, 0.4064, 0.2286,
0.2286, 0.2286, 0.2286, 0.4572), Leaching = c(1.4732, 1.4732,
1.4732, 1.4732, 0, 0, 0, 0, 1.524, 1.524, 1.524, 1.524, 2.3368,
2.3368, 2.3368, 2.3368, 0, 0, 0, 0, 0.762, 0.762, 0.762, 0.762,
0, 0, 0, 0, 0, 0, 0, 0, 3.302, 3.302, 3.302, 3.302, 0, 0, 0,
0, 0.9906, 0.9906, 0.9906, 0.9906, 0, 0, 0, 0, 0, 0, 0, 0, 0.3048,
0.3048, 0.3048, 0.3048, 0, 0, 0, 0, 0, 0, 0, 0, 0.762, 0.762,
0.762, 0.762, 0, 0, 0, 0, 0, 0, 0, 0, 0.4572, 0.4572, 0.4572,
0.4572, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0)), class = "data.frame", row.names = c("1", "2", "3",
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15",
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26",
"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37",
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48",
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59",
"60", "61", "62", "63", "64", "65", "66", "67", "68", "69", "70",
"71", "72", "73", "74", "75", "76", "77", "78", "79", "80", "81",
"82", "83", "84", "85", "86", "87", "88", "89", "90", "91", "92",
"93", "94", "95", "96", "97", "98", "99", "100", "101", "102",
"103", "104", "105", "106", "107", "108", "109", "110", "111",
"112", "113", "114", "115", "116", "117", "118", "119", "120",
"121", "122", "123", "124", "125", "126", "127", "128", "129",
"130", "131", "132", "133", "134", "135", "136", "137", "138",
"139", "140", "141", "142", "143", "144", "145", "146", "147",
"148", "149", "150", "151", "152", "153", "154", "155", "156",
"157", "158", "159", "160", "161", "162", "163", "164", "165"
))