ggplot2 geom_area重叠而不是堆叠 [英] ggplot2 geom_area overlapping instead of stacking
问题描述
我正在尝试生成堆积区域图，但相反，ggplot会生成重叠区域。我已经尝试了其他类似于我的例子，但它们的工作原理并不适用于我。
> cx
日期类型访客
1 2009-11-23 A 2
2 2010-01-07 A 4
3 2010-01-09 A 6
4 2010 -02-07 A 8
5 2009-12-02 B 2
6 2009-12-03 B 4
7 2009-12-11 B 6
8 2010-01 -20 B 8
9 2010-01-26 B 10
10 2010-01-30 B 11
11 2010-02-01 B 12
12 2009-12-07 LU 2
13 2009-12-28 LU 4
14 2010-01-27 LU 7
15 2010-02-04 L 1
16 2010-02-22 L 2
17 2009-11-14 O 2
18 2009-11-27 O 4
19 2010-01-11 O 6
20 2010-01-13 O 8
21 2010-02-10 O 9
22 2009-11-24 R 2
23 2009-12-01 R 4
24 2009-12-13 R 6
25 2009-12-14 R 8
26 2010-01-03 R 10
27 2010-01-16 R 12
28 2010-02-06 R 13
29 2010 -02-08 R 15
30 2009-11-15 T 2
31 2009-11-19 T 4
32 2009-11-25 T 6
33 2009-11-26 T 8
34 2009- 12-09 T 10
35 2009-12-10 T 12
36 2009-12-15 T 14
37 2009-12-19 T 16
38 2009-12- 22 T 18
39 2010-02-23 T 19
40 2010-02-24 T 20
41 2010-01-21 Tr 2
42 2010-01-23 Tr 4
43 2010-01-24 Tr 6
44 2010-01-06 U 2
45 2009-11-09 V 2
46 2009-11-18 V 4
47 2009-12-16 V 6
48 2009-12-23 V 8
49 2009-12-25 V 10
50 2010-01-02 V 12
51 2010-01-12 V 14
52 2010-01-14 V 16
53 2010-01-15 V 18
54 2010-01-17 V 20
55 2010-01-19 V 22
56 2010-01-25 V 25
57 2010-02-05 V 26
> ggplot（cx）+ geom_area（aes（x = date，y = visitor，fill = type），position =stack）
这给出了一个绘图，其中每种类型都绘制为它自己的区域，并且这些图层被叠加而不是叠加。如果我对它们进行正确的分类，那么我会在较大的范围内获得一系列较小的区域，但这不是我所追求的。
我尝试了不同的位置参数，无效。
如何获得堆积区域？
<我找到了解决方案。问题是每个日期的每种类型都没有值，即有某些类型的类型没有入口的x值。
例如，类型= V在2010-01-17有游客= 20，游客在2010-01-19有= 22，所以我会为2010-01-18添加游客= 20。
我的数据是通过使用重塑包中的强制转换生成的，因此只需将add.missing = T设置为标志即可解决我的问题：
<$ （参观者融合，类型+日期〜，长度，添加失败= T）
名称（cx）[3]< - 访问者
cx < - ddply（cx，。（type），function（x）data.frame（date = x $ date，visitors = cumsum（x $ visitors）））
I'm trying to generate a stacked area plot, but instead, ggplot makes overlapping areas. I've tried other examples that seems analogous to me, but they work and mine doesn't.
> cx
date type visitors
1 2009-11-23 A 2
2 2010-01-07 A 4
3 2010-01-09 A 6
4 2010-02-07 A 8
5 2009-12-02 B 2
6 2009-12-03 B 4
7 2009-12-11 B 6
8 2010-01-20 B 8
9 2010-01-26 B 10
10 2010-01-30 B 11
11 2010-02-01 B 12
12 2009-12-07 LU 2
13 2009-12-28 LU 4
14 2010-01-27 LU 7
15 2010-02-04 L 1
16 2010-02-22 L 2
17 2009-11-14 O 2
18 2009-11-27 O 4
19 2010-01-11 O 6
20 2010-01-13 O 8
21 2010-02-10 O 9
22 2009-11-24 R 2
23 2009-12-01 R 4
24 2009-12-13 R 6
25 2009-12-14 R 8
26 2010-01-03 R 10
27 2010-01-16 R 12
28 2010-02-06 R 13
29 2010-02-08 R 15
30 2009-11-15 T 2
31 2009-11-19 T 4
32 2009-11-25 T 6
33 2009-11-26 T 8
34 2009-12-09 T 10
35 2009-12-10 T 12
36 2009-12-15 T 14
37 2009-12-19 T 16
38 2009-12-22 T 18
39 2010-02-23 T 19
40 2010-02-24 T 20
41 2010-01-21 Tr 2
42 2010-01-23 Tr 4
43 2010-01-24 Tr 6
44 2010-01-06 U 2
45 2009-11-09 V 2
46 2009-11-18 V 4
47 2009-12-16 V 6
48 2009-12-23 V 8
49 2009-12-25 V 10
50 2010-01-02 V 12
51 2010-01-12 V 14
52 2010-01-14 V 16
53 2010-01-15 V 18
54 2010-01-17 V 20
55 2010-01-19 V 22
56 2010-01-25 V 25
57 2010-02-05 V 26
> ggplot(cx) + geom_area(aes(x=date, y=visitors, fill=type), position="stack")
This gives a plot where each type is plotted as its own area, and these are overlaid instead of stacked. If I sort them right, I then get a series of smaller areas inside larger, but that's not what I'm after.
I've tried different arguments of position, to no avail.
How can I get the stacked areas?
I found the solution. The problem is that there aren't values for each type for each date, i.e. there are x-values for which certain levels of type don't have an entry.
For instance, type=V has visitors=20 at 2010-01-17, and visitors=22 at 2010-01-19, so I would add visitors=20 for 2010-01-18 as well.
My data was generated by using cast from the reshape package, so just setting add.missing=T as a flag fixed my issues:
cx <- cast(visitors.melt, type+date~., length, add.missing=T)
names(cx)[3] <- "visitors"
cx <- ddply(cx, .(type), function(x) data.frame(date=x$date, visitors=cumsum(x$visitors)))
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