问题描述
我正计划在一个时间序列图中绘制几条趋势线,以便我可以看到跨越几个时间限制的趋势变化。我设法在整个时间序列中绘制了一个线性趋势,但我希望也许能在2007年至2010年以及2010年至2013年绘制更多的趋势,这将有助于我解决2007年至2010年之间的稳定趋势以及2010年之间的下降趋势和2013。我使用了以下代码:
data <- read.csv("sample.csv",header = T,sep = ",",dec = ".")
head(data)
data$Year <- as.Date(data$ï..Date,format = "%m/%d/%Y")
class(data$Year)
attach(data)
time_plot <- ggplot(data,aes(x = Year,y = SPM)) +
geom_line(color = 'black',size = 1.3) + geom_point(color = "blue",size = 1.3) +
scale_x_date(date_labels = "%Y",date_breaks = "1 year") + xlab(label = "Time (Years)") + ylab(label = "Concentration") +
theme_bw() + stat_smooth(
method = "lm",formula = y ~ x,size = 0.75,se = T,color = "blue",fill = "#9AE5D7"
) + stat_poly_eq(
face = "bold",parse = T,aes(label = ..eq.label..),label.x.npc = 0.5,label.y.npc = 0.1,size = 6,coef.digits = 4
) +
theme(
plot.title = element_text(
size = 17,face = "bold",colour = "black"
),axis.title.x = element_text(
size = 20,axis.title.y = element_text(
size = 20,axis.text.x = element_text(
size = 18,axis.text.y = element_text(
size = 18,strip.text.x = element_text(
size = 16,strip.text.y = element_text(
size = 16,axis.line.x = element_line(color = "black",size = 1),axis.line.y = element_line(color = "black",axis.ticks = element_line(color = "black",size = 1.2),axis.ticks.length = unit(0.2,"cm"),panel.border = element_rect(
colour = "black",fill = NA,size = 1
),legend.title = element_blank(),legend.position = c(.8,.2),) +
stat_fit_glance(
method = 'lm',method.args = list(formula = y ~ x),geom = 'text',aes(label = paste(
"P-value = ",signif(..p.value..,digits = 4),sep = ""
)),label.x = "left",label.y = "top",)
返回了以下图形:
但是,我希望生成这样的图,其中将包含多个趋势线:
之前,堆栈溢出中有一个帖子,similar to my query,但它是针对“ python”的。我在想是否可以在R中使用ggplot2做类似的事情?如果您能花一些时间为我指出一些解决问题的方法,或者提出一些可以帮助我生成此类数字的教程,网站或软件包,将不胜感激。我还可以使用黄金软件的绘图仪,这将是获得此类数据的更好平台吗?我将数据集附在下面:
ï..Date SPM Year
1 1/1/2007 6.412 2007-01-01
2 2/1/2007 7.827 2007-02-01
3 3/1/2007 6.816 2007-03-01
4 4/1/2007 8.021 2007-04-01
5 5/1/2007 6.130 2007-05-01
6 6/1/2007 4.982 2007-06-01
7 7/1/2007 3.776 2007-07-01
8 8/1/2007 4.764 2007-08-01
9 9/1/2007 5.699 2007-09-01
10 10/1/2007 7.264 2007-10-01
11 11/1/2007 8.168 2007-11-01
12 12/1/2007 7.518 2007-12-01
13 1/1/2008 7.157 2008-01-01
14 2/1/2008 7.996 2008-02-01
15 3/1/2008 5.806 2008-03-01
16 4/1/2008 5.388 2008-04-01
17 5/1/2008 6.535 2008-05-01
18 6/1/2008 3.715 2008-06-01
19 7/1/2008 4.723 2008-07-01
20 8/1/2008 4.259 2008-08-01
21 9/1/2008 5.524 2008-09-01
22 10/1/2008 7.755 2008-10-01
23 11/1/2008 8.393 2008-11-01
24 12/1/2008 5.702 2008-12-01
25 1/1/2009 5.816 2009-01-01
26 2/1/2009 5.954 2009-02-01
27 3/1/2009 5.142 2009-03-01
28 4/1/2009 6.286 2009-04-01
29 5/1/2009 7.408 2009-05-01
30 6/1/2009 5.866 2009-06-01
31 7/1/2009 7.188 2009-07-01
32 8/1/2009 3.729 2009-08-01
33 9/1/2009 4.284 2009-09-01
34 10/1/2009 6.392 2009-10-01
35 11/1/2009 6.642 2009-11-01
36 12/1/2009 6.365 2009-12-01
37 1/1/2010 6.999 2010-01-01
38 2/1/2010 6.906 2010-02-01
39 3/1/2010 6.205 2010-03-01
40 4/1/2010 3.497 2010-04-01
41 5/1/2010 2.278 2010-05-01
42 6/1/2010 3.510 2010-06-01
43 7/1/2010 4.112 2010-07-01
44 8/1/2010 5.469 2010-08-01
45 9/1/2010 5.402 2010-09-01
46 10/1/2010 5.365 2010-10-01
47 11/1/2010 6.412 2010-11-01
48 12/1/2010 7.384 2010-12-01
49 1/1/2011 7.660 2011-01-01
50 2/1/2011 7.380 2011-02-01
51 3/1/2011 7.880 2011-03-01
52 4/1/2011 5.971 2011-04-01
53 5/1/2011 6.944 2011-05-01
54 6/1/2011 3.911 2011-06-01
55 7/1/2011 4.438 2011-07-01
56 8/1/2011 3.266 2011-08-01
57 9/1/2011 4.554 2011-09-01
58 10/1/2011 7.247 2011-10-01
59 11/1/2011 7.607 2011-11-01
60 12/1/2011 7.791 2011-12-01
61 1/1/2012 9.193 2012-01-01
62 2/1/2012 7.312 2012-02-01
63 3/1/2012 3.753 2012-03-01
64 4/1/2012 3.458 2012-04-01
65 5/1/2012 1.211 2012-05-01
66 6/1/2012 2.052 2012-06-01
67 7/1/2012 2.055 2012-07-01
68 8/1/2012 3.804 2012-08-01
69 9/1/2012 5.728 2012-09-01
70 10/1/2012 6.501 2012-10-01
71 11/1/2012 5.177 2012-11-01
72 12/1/2012 4.829 2012-12-01
任何帮助,建议或建议将不胜感激。预先感谢。
解决方法
您只需对原始数据帧的子集重复geom_smooth
调用:
ggplot(data,aes(x = Year,y = SPM)) +
geom_line(color = 'black',size = 1.3) +
geom_point(color = "blue",size = 1.3) +
stat_smooth(method = "lm",formula = y ~ x,size = 0.75,se = TRUE,color = "blue",fill = "#9AE5D7") +
stat_smooth(method = "lm",color = "red",fill = "red",alpha = 0.2,data = data[data$Year < as.Date("2009-06-01"),]) +
stat_smooth(method = "lm",color = "forestgreen",fill = "forestgreen",data = data[data$Year >= as.Date("2009-06-01"),]) +
stat_poly_eq(face = "bold",parse = TRUE,aes(label = ..eq.label..),label.x.npc = 0.5,label.y.npc = 0.1,size = 6,coef.digits = 4) +
stat_fit_glance(method = 'lm',method.args = list(formula = y ~ x),geom = 'text',aes(label = paste(
"P-value = ",signif(..p.value..,digits = 4),sep = ""
)),label.x = "left",label.y = "top") +
scale_x_date(date_labels = "%Y",date_breaks = "1 year") +
labs(x = "Time (Years)",y = "Concentration") +
theme_bw() +
theme(plot.title = element_text(size = 17,face = "bold"),axis.title.x = element_text(size = 20,axis.title.y = element_text(size = 20,axis.text.x = element_text(size = 18,axis.text.y = element_text(size = 18,strip.text.x = element_text(size = 16,strip.text.y = element_text(size = 16,axis.line.x = element_line(color = "black",size = 1),axis.line.y = element_line(color = "black",axis.ticks = element_line(color = "black",size = 1.2),axis.ticks.length = unit(0.2,"cm"),panel.border = element_rect(fill = NA,legend.title = element_blank(),legend.position = c(.8,.2))
在这种情况下,总体趋势相当恒定,因此背景蓝线被两个部分线段遮盖了。