用单独的线型在ggplot2中绘制缺失值 [英] Plotting missing values in ggplot2 with a separate line type

问题描述

我正在使用ggplot2创建线图，但是缺少以NaN表示的数据.我的线图当前未在缺失值之间添加任何线.但是，我想用虚线连接丢失的数据，而所有已知数据都用实线连接.

这是我当前图的代码，下面是我的数据框和图的一小部分.

  #make ggplots用于所有数据集Q4_plot<-ggplot(数据= Q4，映射= aes(x =年，y = Q4))+geom_line()+geom_point()+实验室(标题="C.finmarchicus种群的第4季分析")+ylab("Anamoly")+scale_y_discrete(lim = c(-1.5，-1.0，-0.5，0.0，0.5，1.0，1.5))#数据帧子集>dput(Q4)结构(列表(年= c(1980，1981，1982，1983，1984，1985，1986，1987、1988、1989、1990、1991、1992、1993、1994、1995、1996、1997，1998、1999、2000、2001、2002、2003、2004、2005、2006、2007、2008，2009、2010、2011、2012、2013、2014、2015、2016、2017)，Q4 = c(-0.2902210281654，-0.4349222339894、0.6085474376776、0.8492088796228、0.5017554154123，0.4848742371842、0.483138540113、1.134146387603、1.095609559681，0.8630386289353、0.1163274274306，-0.3398165357991，-0.1474840957078，-1.344090916262、0.3518846850911，-0.03353853195848，-0.07481708144361，0.2717396470301，-1.43888104698，-0.4838212547847，-0.8460008644647，1.061274634085、0.1433575405896、0.6949323748611、0.4219329126636，-0.1924723455514，-0.2699464637352，NaN，0.4931694954279、0.7079867355531，-0.243929992349、0.9881050229247，-0.2275292445512，NaN，0.3237764596434，-0.3144133941847，0.6111879054247，NaN))，row.names = c(NA，-38L)，类别= c("tbl_df"，"tbl"，"data.frame")) 

这是我的图现在的样子，我想在实线不相交的区域中添加一条虚线.

很抱歉，我是否是新用户?

解决方案

这是一种自动化的解决方案，它依赖于识别丢失数据两侧的点并将它们输入到单独的 geom_line 中.

>

 差距<-my_data％>％filter(is.na(lead(Annual))& row_number()！= n()|is.na(lag(Annual))&row_number()！= 1)％&％;％#需要为每对点建立一个单独的组.#我希望如果某个点两边都有NA的话，它将打破...#有人有更好的主意吗?变异(group = cumsum(row_number()%% 2))ggplot(数据= my_data，映射= aes(x =年，y =年))+geom_line()+geom_line(数据=间隙，aes(组=组)，线型=虚线")+geom_point()+实验室(标题="C.finmarchicus种群的年度异常") 

假数据:

  set.seed(0)my_data = data.frame(年份= 2000:2019，年度=样本(c(-5:5，NA_integer_)，10)) 

I am creating a line plot using ggplot2, but I have missing data that is denoted by NaN. My line plot is currently not adding any line between the missing values. However, I want to connect the missing data with a dotted line, while all known data is connected with a solid line.

Here is my code for the current plot, with a small subset of my data frame and and image of the plot below.

#make ggplots for all data sets  

Q4_plot <- ggplot(data = Q4, mapping = aes(x = Year, y = Q4)) +
  geom_line() +
  geom_point() +
  labs(title = "Quarter 4 Anamolies of C. finmarchicus Population") +
  ylab("Anamoly") +
  scale_y_discrete(lim = c(-1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5)) 

#subset of data frame

> dput(Q4)
structure(list(Year = c(1980, 1981, 1982, 1983, 1984, 1985, 1986, 
1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 
1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 
2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017), Q4 = c(-0.2902210281654, 
-0.4349222339894, 0.6085474376776, 0.8492088796228, 0.5017554154123, 
0.4848742371842, 0.483138540113, 1.134146387603, 1.095609559681, 
0.8630386289353, 0.1163274274306, -0.3398165357991, -0.1474840957078, 
-1.344090916262, 0.3518846850911, -0.03353853195848, -0.07481708144361, 
0.2717396470301, -1.43888104698, -0.4838212547847, -0.8460008644647, 
1.061274634085, 0.1433575405896, 0.6949323748611, 0.4219329126636, 
-0.1924723455514, -0.2699464637352, NaN, 0.4931694954279, 0.7079867355531, 
-0.243929992349, 0.9881050229247, -0.2275292445512, NaN, 0.3237764596434, 
-0.3144133941847, 0.6111879054247, NaN)), row.names = c(NA, -38L
), class = c("tbl_df", "tbl", "data.frame"))

This is what my plot looks like now, and I want to add a dotted line in the areas where the solid line is disjointed.

I apologize if this is badly asked or worded, I am a new R user.

解决方案

Here's an automated solution which relies on identifying the points on either side of missing data and feeding those into a separate geom_line.

gaps <- my_data %>%
  filter(is.na(lead(Annual)) & row_number() != n() |
          is.na(lag(Annual)) & row_number() != 1) %>%
  # This is needed to make a separate group for each pair of points.
  #  I expect it will break if a point ever has NA's on both sides...
  #  Anyone have a better idea?
  mutate(group = cumsum(row_number() %% 2))

ggplot(data = my_data, mapping = aes(x = Year, y = Annual)) +
  geom_line() +
  geom_line(data = gaps, aes(group = group), linetype = "dashed") +
  geom_point() + 
  labs(title = "Annual Anomalies of C. finmarchicus Population")

fake data:

set.seed(0)
my_data = data.frame(Year = 2000:2019,
                     Annual = sample(c(-5:5, NA_integer_), 10))

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