使用geom_line（）连接选定NDA的点 [英] connect points across selected NAs with geom_line()

问题描述

我的问题与）：

  ggplot（data = df，aes（x = Year，y = value，gro up =变量，color =变量，shape =变量））+ 
 geom_point（size = 3）+ geom_line（data = df [！is.na（df $ value），]）
  

$ b $ p
$ b $ p
$ b $ p







$ b $
df2 [df2 $ Year == 1922，] $ value< - -999999
df2 [df2 $ Year == 1948，] $ value< - -999999
df2 <-df2 [！is.na（df2 $ value），]
df2 $ value < - as.numeric（df2 $ value）
ggplot（data = df2，aes（x = Year ，y = value，group = variable，color = variable，shape = variable））+ geom_point（size = 3）+
geom_line（）+ scale_y_continuous（limit = c（.08，.23））

解决方案

这会产生您的想要的情节，除了注释中提到的例外。

  x < -  rle（！is.na（df $ value））
x $ values [which（x （b），（b），（b），（b），（b）和（b） aes（x = Year，y = value，color = variable））+ 
 geom_point（size = 3）+ 
 geom_line（）
  

基本上，我们将 NA 编码为 FALSE ，其他所有内容都编码为 TRUE ，然后执行运行长度编码以识别 T / F 的序列。任何长度> 3的 FALSE 序列都应该保留，所以我们将它们转换为 TRUE （就好像它们不是 NA ），那么我们使用inverse rle来恢复一个索引向量，如果该行应该保留，则使用 TRUE 来恢复索引向量。最后，我们将它应用于 df 中，以用于 ggplot 。

My question is closely related to Connecting across missing values with geom_line, but it's a follow-up rather than a duplicate.

I have data with missing values NA. The data has been 'melted' in long form with package reshape2 and I am using ggplot2 to plot both geom_points() and geom_line(). In the example data, I have one group only, in my real data I have several groups. I would like to plot a geom_line() connecting data points that are not separated by more than 4 years of missing data. In other words, if there are 3 adjacent rows with NA, apply na.rm to the data.frame, while if there are at least 4 adjacent rows with NA, do not apply na.rm to the data.frame.

Edit: Note: I am replicating figures from a book, where the points are connected even when the data is missing. It would be better to use a different linetype or colour for those segments connecting missing data, together with a note in the legend explaining it.

In the following, I have a very tedious and ugly hack that will not scale up to manipulating large amounts of data. I'd be grateful for a simpler approach and particularly keen to find a simple way to count instances of consecutive NAs in the data.

### ggplot draws geom_line with NAs

# Data (real-world example, so not exactly MWE)
df <- 
structure(list(Year = c(1910, 1911, 1912, 1913, 1914, 1915, 1916, 
1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 
1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 
1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 
1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 
1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 
1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 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), variable = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L), .Label = c("France", "Germany", "Sweden", "Japan"
), class = c("ordered", "factor")), value = c(0.1724, 0.1748, 
0.1752, 0.1777, 0.1778, 0.1953, 0.2132, 0.2242, 0.222, 0.1947, 
NA, NA, NA, NA, NA, 0.113, 0.113, 0.115, 0.112, 0.111, NA, NA, 
0.114, 0.109, 0.113, 0.12, 0.137, 0.15, 0.163, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, 0.116, NA, NA, NA, NA, NA, NA, 0.11, 
NA, NA, NA, 0.122, NA, NA, NA, 0.122, NA, NA, 0.112, NA, NA, 
0.113, NA, NA, 0.101, NA, NA, 0.102, NA, NA, 0.1043, NA, NA, 
0.0906, NA, NA, 0.0964, NA, NA, 0.1052, NA, NA, 0.1043, NA, NA, 
0.1005, NA, NA, 0.1088, NA, NA, 0.101139312657167, 0.0950290025146689, 
0.0901042749371333, 0.09, 0.107249622799665, 0.108891198658843, 
0.115913495389774, 0.110684772282761, 0.113299133836267, 0.111991953059514
)), .Names = c("Year", "variable", "value"), row.names = 102:202, class = "data.frame")

The default plot:

library("ggplot2")
ggplot(data = df, aes(x = Year, y = value, group = variable, colour = variable, shape = variable)) + 
    geom_point(size = 3) + geom_line()

The plot with all NAs removed (see Connecting across missing values with geom_line):

ggplot(data = df, aes(x = Year, y = value, group = variable, colour = variable, shape = variable)) + 
    geom_point(size = 3) + geom_line(data = df[!is.na(df$value), ])

The desired plot:

df2 <- df
df2[df2$Year == 1922, ]$value <- "-999999"
df2[df2$Year == 1948, ]$value <- "-999999"
df2 <- df2[!is.na(df2$value), ]
df2$value <- as.numeric(df2$value)
ggplot(data = df2, aes(x = Year, y = value, group = variable, colour = variable, shape = variable)) + geom_point(size = 3) + 
    geom_line() + scale_y_continuous(limit = c(.08, .23))

解决方案

This produces your "desired plot", with the exception noted in the comment.

x <- rle(!is.na(df$value))
x$values[which(x$lengths>3 & !x$values)] <- TRUE
indx <- inverse.rle(x)
library(ggplot2)
ggplot(df[indx,],aes(x=Year,y=value,color=variable))+
  geom_point(size=3)+
  geom_line()

Basically, we encode NA as FALSE, and everything else as TRUE, then perform run length encoding to identify sequences of T/F. Any sequence of FALSE of length > 3 should be kept, so we convert those to TRUE (as if they were not NA), then we use inverse rle to recover an index vector with TRUE if the row should be kept. Finally, we apply this to the df for use in ggplot.

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