相互绘制多个年度时间序列
我有一个数据框，其中包含31个站点的各种气候测量值的每日观测值，这是因素。每个站都有许多年的日常观测值，并且有效地，每个站都有唯一的记录年数和唯一的观测值。
例如数据，我将其细分为13个站，每个唯一水年观测一次。
NAME DATE PRCP calendar_year month day water_year water_date
<fct> <date> <dbl> <fct> <int> <int> <fct> <date>
102 FLORENCE 0.2 SSE, OR US 2007-12-05 0 2007 12 5 2007 2006-12-05
103 FLORENCE 0.2 SSE, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
104 FLORENCE 0.2 SSE, OR US 2009-12-16 0.9 2009 12 16 2009 2008-12-16
105 FLORENCE 0.2 SSE, OR US 2010-10-19 0 2010 10 19 2010 2009-10-19
106 FLORENCE 0.2 SSE, OR US 2012-07-10 0 2012 7 10 2012 2012-07-10
107 FLORENCE 0.5 NE, OR US 2007-12-12 0 2007 12 12 2007 2006-12-12
108 FLORENCE 0.5 NE, OR US 2008-01-01 0 2008 1 1 2008 2008-01-01
109 FLORENCE 0.6 E, OR US 2008-01-01 0 2008 1 1 2008 2008-01-01
110 FLORENCE 0.9 NW, OR US 2007-12-22 0.09 2007 12 22 2007 2006-12-22
111 FLORENCE 0.9 NW, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
112 FLORENCE 0.9 NW, OR US 2009-10-01 0.02 2009 10 1 2009 2008-10-01
113 FLORENCE 0.9 NW, OR US 2010-10-01 0.03 2010 10 1 2010 2009-10-01
114 FLORENCE 0.9 NW, OR US 2011-10-01 0.02 2011 10 1 2011 2010-10-01
115 FLORENCE 0.9 NW, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
116 FLORENCE 0.9 NW, OR US 2013-10-01 0.92 2013 10 1 2013 2012-10-01
117 FLORENCE 0.9 NW, OR US 2014-10-01 0.01 2014 10 1 2014 2013-10-01
118 FLORENCE 0.9 NW, OR US 2015-10-01 0 2015 10 1 2015 2014-10-01
119 FLORENCE 0.9 NW, OR US 2016-10-01 0.15 2016 10 1 2016 2015-10-01
120 FLORENCE 0.9 NW, OR US 2017-10-01 0.2 2017 10 1 2017 2016-10-01
121 FLORENCE 0.9 NW, OR US 2018-01-01 0 2018 1 1 2018 2018-01-01
122 FLORENCE 1.8 NW, OR US 2007-12-14 0 2007 12 14 2007 2006-12-14
123 FLORENCE 1.8 NW, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
124 FLORENCE 1.8 NW, OR US 2009-10-25 0 2009 10 25 2009 2008-10-25
125 FLORENCE 1.8 NW, OR US 2010-10-05 0.01 2010 10 5 2010 2009-10-05
126 FLORENCE 1.8 NW, OR US 2011-10-01 0.02 2011 10 1 2011 2010-10-01
127 FLORENCE 1.8 NW, OR US 2012-10-02 0 2012 10 2 2012 2011-10-02
128 FLORENCE 1.8 NW, OR US 2013-10-01 0.570 2013 10 1 2013 2012-10-01
129 FLORENCE 1.8 NW, OR US 2014-10-01 0.02 2014 10 1 2014 2013-10-01
130 FLORENCE 1.8 NW, OR US 2015-10-01 0.02 2015 10 1 2015 2014-10-01
131 FLORENCE 1.8 NW, OR US 2016-10-01 0.08 2016 10 1 2016 2015-10-01
132 FLORENCE 1.8 NW, OR US 2017-10-01 0.23 2017 10 1 2017 2016-10-01
133 FLORENCE 1.8 NW, OR US 2018-01-01 0.01 2018 1 1 2018 2018-01-01
134 FLORENCE 2.1 NNW, OR US 2007-12-17 0.96 2007 12 17 2007 2006-12-17
135 FLORENCE 2.1 NNW, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
136 FLORENCE 2.1 NNW, OR US 2009-10-01 0 2009 10 1 2009 2008-10-01
137 FLORENCE 2.1 NNW, OR US 2010-10-01 0.03 2010 10 1 2010 2009-10-01
138 FLORENCE 2.1 NNW, OR US 2011-10-01 0 2011 10 1 2011 2010-10-01
139 FLORENCE 2.1 NNW, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
140 FLORENCE 2.1 NNW, OR US 2013-12-26 0 2013 12 26 2013 2012-12-26
141 FLORENCE 2.1 NNW, OR US 2014-10-07 0 2014 10 7 2014 2013-10-07
142 FLORENCE 2.1 NNW, OR US 2016-05-21 0 2016 5 21 2016 2016-05-21
143 FLORENCE 2.1 NNW, OR US 2017-12-26 0 2017 12 26 2017 2016-12-26
144 FLORENCE 2.9 NNW, OR US 2007-12-16 0.07 2007 12 16 2007 2006-12-16
145 FLORENCE 2.9 NNW, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
146 FLORENCE 2.9 NNW, OR US 2009-10-01 0.03 2009 10 1 2009 2008-10-01
147 FLORENCE 2.9 NNW, OR US 2010-10-02 0.05 2010 10 2 2010 2009-10-02
148 FLORENCE 2.9 NNW, OR US 2011-10-01 0.02 2011 10 1 2011 2010-10-01
149 FLORENCE 2.9 NNW, OR US 2012-10-02 0 2012 10 2 2012 2011-10-02
150 FLORENCE 2.9 NNW, OR US 2013-10-01 0.580 2013 10 1 2013 2012-10-01
151 FLORENCE 2.9 NNW, OR US 2014-10-01 0.02 2014 10 1 2014 2013-10-01
152 FLORENCE 2.9 NNW, OR US 2015-10-01 0 2015 10 1 2015 2014-10-01
153 FLORENCE 2.9 NNW, OR US 2016-10-04 0.580 2016 10 4 2016 2015-10-04
154 FLORENCE 2.9 NNW, OR US 2017-10-01 0.2 2017 10 1 2017 2016-10-01
155 FLORENCE 2.9 NNW, OR US 2018-01-01 0 2018 1 1 2018 2018-01-01
156 FLORENCE 5.4 N, OR US 2007-12-22 0.03 2007 12 22 2007 2006-12-22
157 FLORENCE 5.4 N, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
158 FLORENCE 5.4 N, OR US 2009-10-01 0.07 2009 10 1 2009 2008-10-01
159 FLORENCE 5.4 N, OR US 2010-10-01 0.03 2010 10 1 2010 2009-10-01
160 FLORENCE 5.4 N, OR US 2011-10-03 0.65 2011 10 3 2011 2010-10-03
161 FLORENCE 5.4 N, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
162 FLORENCE 5.4 N, OR US 2013-10-01 0.6 2013 10 1 2013 2012-10-01
163 FLORENCE 5.4 N, OR US 2014-10-01 0 2014 10 1 2014 2013-10-01
164 FLORENCE 5.4 N, OR US 2015-10-01 0 2015 10 1 2015 2014-10-01
165 FLORENCE 5.4 N, OR US 2016-11-01 0.21 2016 11 1 2016 2015-11-01
166 FLORENCE 5.4 N, OR US 2017-11-11 0.9 2017 11 11 2017 2016-11-11
167 FLORENCE 5.4 N, OR US 2018-01-01 0 2018 1 1 2018 2018-01-01
168 FLORENCE 5.4 S, OR US 2007-12-08 0.42 2007 12 8 2007 2006-12-08
169 FLORENCE 5.4 S, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
170 FLORENCE 5.4 S, OR US 2009-10-01 0 2009 10 1 2009 2008-10-01
171 FLORENCE 5.4 S, OR US 2010-10-01 0.03 2010 10 1 2010 2009-10-01
172 FLORENCE 5.4 S, OR US 2011-10-01 0 2011 10 1 2011 2010-10-01
173 FLORENCE 5.4 S, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
174 FLORENCE 5.4 S, OR US 2013-10-01 0.6 2013 10 1 2013 2012-10-01
175 FLORENCE 5.4 S, OR US 2014-10-02 0 2014 10 2 2014 2013-10-02
176 FLORENCE 5.4 S, OR US 2015-01-01 0 2015 1 1 2015 2015-01-01
177 FLORENCE 5.8 S, OR US 2007-12-01 0.02 2007 12 1 2007 2006-12-01
178 FLORENCE 5.8 S, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
179 FLORENCE 5.8 S, OR US 2009-10-01 0.02 2009 10 1 2009 2008-10-01
180 FLORENCE 5.8 S, OR US 2010-10-01 0.01 2010 10 1 2010 2009-10-01
181 FLORENCE 5.8 S, OR US 2011-10-01 0 2011 10 1 2011 2010-10-01
182 FLORENCE 5.8 S, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
183 FLORENCE 5.8 S, OR US 2013-10-01 0.75 2013 10 1 2013 2012-10-01
184 FLORENCE 5.8 S, OR US 2014-01-01 0 2014 1 1 2014 2014-01-01
185 FLORENCE 5.9 NNE, OR US 2007-11-29 0.41 2007 11 29 2007 2006-11-29
186 FLORENCE 5.9 NNE, OR US 2008-10-03 0.39 2008 10 3 2008 2007-10-03
187 FLORENCE 5.9 NNE, OR US 2009-10-01 0.01 2009 10 1 2009 2008-10-01
188 FLORENCE 5.9 NNE, OR US 2010-10-01 0.05 2010 10 1 2010 2009-10-01
189 FLORENCE 5.9 NNE, OR US 2011-10-01 0.02 2011 10 1 2011 2010-10-01
190 FLORENCE 5.9 NNE, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
191 FLORENCE 5.9 NNE, OR US 2013-10-01 0.43 2013 10 1 2013 2012-10-01
192 FLORENCE 5.9 NNE, OR US 2014-10-01 0 2014 10 1 2014 2013-10-01
193 FLORENCE 5.9 NNE, OR US 2015-10-10 0.69 2015 10 10 2015 2014-10-10
194 FLORENCE 5.9 NNE, OR US 2016-10-01 0.11 2016 10 1 2016 2015-10-01
195 FLORENCE 5.9 NNE, OR US 2017-01-01 0.24 2017 1 1 2017 2017-01-01
196 FLORENCE 6 N, OR US 2007-11-19 0.04 2007 11 19 2007 2006-11-19
197 FLORENCE 6 N, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
198 FLORENCE 6 N, OR US 2009-10-01 0 2009 10 1 2009 2008-10-01
199 FLORENCE 6 N, OR US 2010-01-01 0.7 2010 1 1 2010 2010-01-01
200 FLORENCE NUMBER 2, OR US 2006-10-01 0 2006 10 1 2006 2005-10-01
201 FLORENCE NUMBER 2, OR US 2007-10-01 0 2007 10 1 2007 2006-10-01
202 FLORENCE NUMBER 2, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
203 FLORENCE NUMBER 2, OR US 2009-10-01 0 2009 10 1 2009 2008-10-01
204 FLORENCE NUMBER 2, OR US 2010-10-01 0.04 2010 10 1 2010 2009-10-01
205 FLORENCE NUMBER 2, OR US 2011-10-01 0.9 2011 10 1 2011 2010-10-01
206 FLORENCE NUMBER 2, OR US 2012-10-01 0 2012 10 1 2012 2011-10-01
207 FLORENCE NUMBER 2, OR US 2013-10-01 0.46 2013 10 1 2013 2012-10-01
208 FLORENCE NUMBER 2, OR US 2014-10-01 0 2014 10 1 2014 2013-10-01
209 FLORENCE NUMBER 2, OR US 2015-10-01 0 2015 10 1 2015 2014-10-01
210 FLORENCE NUMBER 2, OR US 2016-10-01 0.77 2016 10 1 2016 2015-10-01
211 FLORENCE NUMBER 2, OR US 2017-10-01 0.06 2017 10 1 2017 2016-10-01
212 FLORENCE NUMBER 2, OR US 2018-01-01 0 2018 1 1 2018 2018-01-01
213 FLORENCE, OR US 1909-10-01 0.580 1909 10 1 1909 1908-10-01
214 FLORENCE, OR US 1910-10-01 0.49 1910 10 1 1910 1909-10-01
215 FLORENCE, OR US 1911-10-01 0.03 1911 10 1 1911 1910-10-01
216 FLORENCE, OR US 1912-10-01 0.07 1912 10 1 1912 1911-10-01
217 FLORENCE, OR US 1913-10-01 0 1913 10 1 1913 1912-10-01
218 FLORENCE, OR US 1914-10-01 0.24 1914 10 1 1914 1913-10-01
219 FLORENCE, OR US 1915-10-01 0.25 1915 10 1 1915 1914-10-01
220 FLORENCE, OR US 1916-10-01 0.03 1916 10 1 1916 1915-10-01
221 FLORENCE, OR US 1917-10-01 0 1917 10 1 1917 1916-10-01
222 FLORENCE, OR US 1918-10-01 0 1918 10 1 1918 1917-10-01
223 FLORENCE, OR US 1919-10-01 0.6 1919 10 1 1919 1918-10-01
224 FLORENCE, OR US 1920-10-01 1.22 1920 10 1 1920 1919-10-01
225 FLORENCE, OR US 1921-10-01 0 1921 10 1 1921 1920-10-01
226 FLORENCE, OR US 1922-10-01 0.03 1922 10 1 1922 1921-10-01
227 FLORENCE, OR US 1949-12-08 0 1949 12 8 1949 1948-12-08
228 FLORENCE, OR US 1950-10-01 0 1950 10 1 1950 1949-10-01
229 FLORENCE, OR US 1951-01-01 0.32 1951 1 1 1951 1951-01-01
230 FLORENCE, OR US 2004-10-01 0 2004 10 1 2004 2003-10-01
231 FLORENCE, OR US 2005-10-01 0.88 2005 10 1 2005 2004-10-01
232 FLORENCE, OR US 2006-10-01 0 2006 10 1 2006 2005-10-01
233 FLORENCE, OR US 2007-10-01 0.33 2007 10 1 2007 2006-10-01
234 FLORENCE, OR US 2008-10-01 0 2008 10 1 2008 2007-10-01
235 FLORENCE, OR US 2009-10-01 0 2009 10 1 2009 2008-10-01
236 FLORENCE, OR US 2010-10-01 0.04 2010 10 1 2010 2009-10-01
237 FLORENCE, OR US 2011-10-01 0.75 2011 10 1 2011 2010-10-01
238 FLORENCE, OR US 2012-10-02 0 2012 10 2 2012 2011-10-02
239 FLORENCE, OR US 2013-10-01 0.63 2013 10 1 2013 2012-10-01
240 FLORENCE, OR US 2014-10-01 0 2014 10 1 2014 2013-10-01
241 FLORENCE, OR US 2015-10-01 0 2015 10 1 2015 2014-10-01
242 FLORENCE, OR US 2016-10-01 0.16 2016 10 1 2016 2015-10-01
243 FLORENCE, OR US 2017-01-01 0.53 2017 1 1 2017 2017-01-01
我的目标是：
- 每个NAME
- 每现存水年
- 针对water_date创建所有PRCP值的点/平滑图
- 按名称合并
因此，得出的图将是y轴上的PRCP，x轴上的water_date以及按每个water_year（可用于该NAME）分组的点/平滑点，它们彼此重叠。总共将有31个地块，每个名称一个。
对于给定名称的PRCP，针对每单个water_year的water_date绘制一个简单的方法是：
ggplot(srb_clean %>% filter(NAME == "made up name" & water_year == "1902") ,aes(water_date, PRCP)) +
geom_point(na.rm=TRUE) +
geom_smooth(colour = "red",size = 1)
此代码将为一年的数据生成图表，而所需的输出将为该NAME的每一年数据提供一个点/平滑组。
我正在寻找一种方法来自动化创建这些图的每个过程，并使用PRCP x water_date（按water_year分组）为每个名称输出一个图。
做这样的R的最优雅或最标准的方法是什么？我是一名编程新手，并且对如何以编程方式解决此问题有些困惑，尤其是在R中。
UPDATE＃1（改进的示例数据和问题）
更新＃3（解决方案）
Parfait的解决方案效果很好。可以将其与类似于上面的代码一起使用，以输出类似于以下内容的图：
1 个答案:
答案 0 :(得分：1)
由于您需要在一年中使用相同的x轴日期，因此请考虑将 water_date 中的所有年份更新为当前没有行保留的普通年份，例如2099-2100。
然后使用by（通过一个或多个因子将数据帧切成较小的子集的功能）为每个不同的 NAME 生成图的列表。要忽略 2099 ，请使用scales库来绘制月份和日期：%b-%d（月份名称）%m-%d（月份编号）。另外，将 water_year 作为图例系列的填充因子。
library(ggplot2)
library(scales)
...
# TEMP HELPER VARIABLE
df$wt_date_char <- as.character(df$water_date)
# REPLACE EVERY YEAR FOR 2099 OR 2100
# CONDITIONALLY UPDATE YEAR BY MONTH NUMEBR
df$pseudo_water_date <- ifelse(substr(df$wt_date_char, 6, 7) %in% paste0("0", as.character(seq(1,9))),
gsub("^(.*?)\\-", "2099-", df$wt_date_char),
gsub("^(.*?)\\-", "2100-", df$wt_date_char)
)
df$pseudo_water_date <- as.Date(df$pseudo_water_date, origin="1970-01-01")
df$wt_date_char <- NULL
# BUILD PLOT LIST
plot_list <- by(srb_clean, srb_clean$NAME, function(sub)
ggplot(sub, aes(pseudo_water_date, PRCP, fill=factor(water_year))) +
geom_point(na.rm=TRUE) +
geom_smooth(colour = "red", size = 1) +
ggtitle(sub$NAME[[1]]) +
labs(title="Water Year", x="Water Date", y="Precipitation") +
theme(plot.title = element_text(hjust = 0.5)) +
scale_x_date(labels = date_format("%b-%d"))
)
# OUTPUT INDIVIDUAL PLOTS
plot_list[[1]]
plot_list[[2]]
plot_list[[3]]
...
# OUTPUT ALL PLOTS
plot_list
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