ggplot面积图奇怪地绘图
我正在尝试使用geom_area（）函数绘制时间（x轴）上的床（y轴）数量，并按等级（5级）对颜色分组。
我有一个包含866,520行的海量数据集，因此我在下面仅提供了一个数据外观示例。数据范围是2015年1月1日至2018年7月1日。
> head(Test, 100)
Date Rating Beds Location
(Date) (Fact) (Num) (Char)
1 2015-09-01 Unrated 22 f51f5385
2 2015-10-01 Unrated 22 f51f5385
3 2015-11-01 Unrated 22 f51f5385
4 2015-12-01 Inadequate 22 f51f5385
5 2016-01-01 Inadequate 22 f51f5385
6 2016-02-01 Inadequate 22 f51f5385
7 2016-03-01 Inadequate 22 f51f5385
8 2016-04-01 Inadequate 22 f51f5385
9 2016-05-01 Inadequate 22 f51f5385
10 2016-06-01 Inadequate 22 f51f5385
11 2016-07-01 Inadequate 22 f51f5385
12 2016-08-01 Requires improvement 22 f51f5385
13 2016-09-01 Requires improvement 22 f51f5385
14 2016-10-01 Requires improvement 22 f51f5385
15 2016-11-01 Requires improvement 22 f51f5385
16 2016-12-01 Requires improvement 22 f51f5385
17 2017-01-01 Requires improvement 22 f51f5385
18 2017-02-01 Requires improvement 22 f51f5385
19 2017-03-01 Requires improvement 22 f51f5385
20 2017-04-01 Requires improvement 22 f51f5385
21 2017-05-01 Requires improvement 22 f51f5385
22 2017-06-01 Requires improvement 22 f51f5385
23 2017-07-01 Requires improvement 22 f51f5385
24 2017-08-01 Requires improvement 22 f51f5385
25 2017-09-01 Requires improvement 22 f51f5385
26 2017-10-01 Requires improvement 22 f51f5385
27 2017-11-01 Requires improvement 22 f51f5385
28 2017-12-01 Requires improvement 22 f51f5385
29 2018-01-01 Requires improvement 22 f51f5385
30 2018-02-01 Requires improvement 22 f51f5385
31 2018-03-01 Requires improvement 22 f51f5385
32 2018-04-01 Requires improvement 22 f51f5385
33 2018-05-01 Requires improvement 22 f51f5385
34 2018-06-01 Requires improvement 22 f51f5385
35 2018-07-01 Requires improvement 22 f51f5385
36 2015-09-01 Unrated 0 840eef42
37 2015-10-01 Unrated 0 840eef42
38 2015-11-01 Unrated 0 840eef42
39 2015-12-01 Unrated 0 840eef42
40 2016-01-01 Unrated 0 840eef42
41 2016-02-01 Unrated 0 840eef42
42 2016-03-01 Unrated 0 840eef42
43 2016-04-01 Unrated 0 840eef42
44 2016-05-01 Unrated 0 840eef42
45 2016-06-01 Unrated 0 840eef42
46 2016-07-01 Unrated 0 840eef42
47 2016-08-01 Unrated 0 840eef42
48 2016-09-01 Unrated 0 840eef42
49 2016-10-01 Unrated 0 840eef42
50 2016-11-01 Unrated 0 840eef42
51 2016-12-01 Unrated 0 840eef42
52 2015-09-01 Good 0 d774c8a9
53 2015-10-01 Good 0 d774c8a9
54 2015-11-01 Good 0 d774c8a9
55 2015-12-01 Good 0 d774c8a9
56 2016-01-01 Good 0 d774c8a9
57 2016-02-01 Good 0 d774c8a9
58 2016-03-01 Good 0 d774c8a9
59 2016-04-01 Good 0 d774c8a9
60 2016-05-01 Good 0 d774c8a9
61 2016-06-01 Good 0 d774c8a9
62 2016-07-01 Good 0 d774c8a9
63 2016-08-01 Good 0 d774c8a9
64 2016-09-01 Good 0 d774c8a9
65 2016-10-01 Good 0 d774c8a9
66 2016-11-01 Good 0 d774c8a9
67 2016-12-01 Good 0 d774c8a9
68 2017-01-01 Good 0 d774c8a9
69 2017-02-01 Good 0 d774c8a9
70 2017-03-01 Good 0 d774c8a9
71 2017-04-01 Good 0 d774c8a9
72 2017-05-01 Good 0 d774c8a9
73 2017-06-01 Good 0 d774c8a9
74 2017-07-01 Good 0 d774c8a9
75 2017-08-01 Requires improvement 0 d774c8a9
76 2017-09-01 Requires improvement 0 d774c8a9
77 2017-10-01 Requires improvement 0 d774c8a9
78 2017-11-01 Requires improvement 0 d774c8a9
79 2017-12-01 Requires improvement 0 d774c8a9
80 2018-01-01 Requires improvement 0 d774c8a9
81 2018-02-01 Requires improvement 0 d774c8a9
82 2018-03-01 Requires improvement 0 d774c8a9
83 2018-04-01 Requires improvement 0 d774c8a9
84 2018-05-01 Requires improvement 0 d774c8a9
85 2018-06-01 Requires improvement 0 d774c8a9
86 2018-07-01 Requires improvement 0 d774c8a9
87 2015-09-01 Unrated 11 4947911b
88 2015-10-01 Unrated 11 4947911b
89 2015-11-01 Unrated 11 4947911b
90 2015-12-01 Good 11 4947911b
91 2016-01-01 Good 11 4947911b
92 2016-02-01 Good 11 4947911b
93 2016-03-01 Good 11 4947911b
94 2016-04-01 Good 11 4947911b
95 2016-05-01 Good 11 4947911b
96 2016-06-01 Good 11 4947911b
97 2016-07-01 Good 11 4947911b
98 2016-08-01 Good 11 4947911b
99 2016-09-01 Good 11 4947911b
100 2016-10-01 Good 11 4947911b
>
我的输出输出：
> dput(head(Test,100))
structure(list(Date = structure(c(16679, 16709, 16740, 16770,
16801, 16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045,
17075, 17106, 17136, 17167, 17198, 17226, 17257, 17287, 17318,
17348, 17379, 17410, 17440, 17471, 17501, 17532, 17563, 17591,
17622, 17652, 17683, 17713, 16679, 16709, 16740, 16770, 16801,
16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045, 17075,
17106, 17136, 16679, 16709, 16740, 16770, 16801, 16832, 16861,
16892, 16922, 16953, 16983, 17014, 17045, 17075, 17106, 17136,
17167, 17198, 17226, 17257, 17287, 17318, 17348, 17379, 17410,
17440, 17471, 17501, 17532, 17563, 17591, 17622, 17652, 17683,
17713, 16679, 16709, 16740, 16770, 16801, 16832, 16861, 16892,
16922, 16953, 16983, 17014, 17045, 17075), class = "Date"), Rating = structure(c(5L,
5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("Good", "Inadequate", "Outstanding",
"Requires improvement", "Unrated"), class = "factor"), Beds = c(22,
22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22,
22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22,
22, 22, 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, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11), Location = c("f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385", "f51f5385",
"f51f5385", "f51f5385", "f51f5385", "840eef42", "840eef42", "840eef42",
"840eef42", "840eef42", "840eef42", "840eef42", "840eef42", "840eef42",
"840eef42", "840eef42", "840eef42", "840eef42", "840eef42", "840eef42",
"840eef42", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9", "d774c8a9",
"4947911b", "4947911b", "4947911b", "4947911b", "4947911b", "4947911b",
"4947911b", "4947911b", "4947911b", "4947911b", "4947911b", "4947911b",
"4947911b", "4947911b")), .Names = c("Date", "Rating", "Beds",
"Location"), row.names = c(NA, 100L), class = "data.frame")
这是我使用大型数据集的代码：
ggplot(Beds_total, aes(x = Date, y = Beds, fill = Rating))+
geom_area(color = "black", alpha = .4)
但是，这会生成以下图：
任何想法都出了什么问题，我首先假设平滑处理存在问题。
1 个答案:
答案 0 :(得分：1)
我认为您的数据太乱了，ggplot无法处理。当您将数据发送到ggplot()时，它应该是干净的并可以打印。由于您位于不同的位置，因此您似乎对每个日期/费率都有多个计数。我假设您只是想将来自不同位置的值加在一起。您可以在绘制之前使用dplyr/tidyr进行此操作。例如
library(dplyr)
library(tidyr)
Beds_total %>% group_by(Date, Rating) %>%
summarize(Beds=sum(Beds)) %>%
complete(Date, Rating, fill=list(Beds=0)) %>%
ggplot(aes(x = Date, y = Beds, fill=Rating))+
geom_area(color = "black", alpha = .4)
这就是示例数据的返回结果
相关问题
最新问题
- 我写了这段代码，但我无法理解我的错误
- 我无法从一个代码实例的列表中删除 None 值，但我可以在另一个实例中。为什么它适用于一个细分市场而不适用于另一个细分市场？
- 是否有可能使 loadstring 不可能等于打印？卢阿
- java中的random.expovariate()
- Appscript 通过会议在 Google 日历中发送电子邮件和创建活动
- 为什么我的 Onclick 箭头功能在 React 中不起作用？
- 在此代码中是否有使用“this”的替代方法？
- 在 SQL Server 和 PostgreSQL 上查询，我如何从第一个表获得第二个表的可视化
- 每千个数字得到
- 更新了城市边界 KML 文件的来源？