Pryore
Reputation: 520
Ggplot area chart plotting strangely
I'm attempting to use the geom_area() function to plot a number of beds (y-axis) over time (x-axis) with color groupings by rating (5 levels).
I have a massive dataset with 866,520 rows, so I've just included a sample below of what of data looks like. The data range is from 2015-01-01 to 2018-07-01.
> 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
>
My dput output:
> 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")
This is my code using the big dataset:
ggplot(Beds_total, aes(x = Date, y = Beds, fill = Rating))+
geom_area(color = "black", alpha = .4)
However, this generates the following plot:
Any ideas what's going wrong, I first assumed there was something going wrong with the smoothing.
Upvotes: 1
Views: 79
Answers (1)
MrFlick
Reputation: 206207
I think your data is just a bit too messy for ggplot to handle. Your data should be clean and ready for plotting when you send it to ggplot(). You seem to have multiple counts for each date/rating since you have different locations. I'm going to assume you just wanted to add together the values from different locations. You can do that with dplyr/tidyr prior to plotting. For example
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)
And here's what that returns for the sample data
Upvotes: 1
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