Time series, how to eliminate gaps between missing periods in ggplot2?

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I need to present climate data during an evaluation period, but the time lapses, as observed in Figure 1, using the data (exe2) and the script (1). Naturally the ggplot plot the x-axis as continuous data, precise be created (cuts) to approximate periods (Figure 2), and or eliminate even these spaces.

Figure 1: Normal example inserir a descrição da imagem aqui

Figure 2: Example of possible model

inserir a descrição da imagem aqui

sample data:

exe2<-structure(list(V1 = structure(c(18601, 18601, 18601, 18601, 18601, 
18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 
18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 
18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 
18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 18601, 
18601, 18601, 18601, 18601, 18601, 18601, 18601, 18602, 18602, 
18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 
18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 
18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 
18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 
18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 18602, 
18602, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 
18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 
18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 
18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 
18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 18603, 
18603, 18603, 18603, 18603, 18604, 18604, 18604, 18604, 18604, 
18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 
18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 
18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 
18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 18604, 
18604, 18604, 18604, 18604, 18604, 18604, 18604, 18605, 18605, 
18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 
18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 
18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 
18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 
18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 18605, 
18605, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 
18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 
18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 
18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 
18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 18637, 
18637, 18637, 18637, 18637, 18638, 18638, 18638, 18638, 18638, 
18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 
18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 
18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 
18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 18638, 
18638, 18638, 18638, 18638, 18638, 18638, 18638, 18639, 18639, 
18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 
18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 
18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 
18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 
18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 18639, 
18639, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 
18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 
18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 
18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 
18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 18640, 
18640, 18640, 18640, 18640, 18641, 18641, 18641, 18641, 18641, 
18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 
18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 
18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 
18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 18641, 
18641, 18641, 18641, 18641, 18641, 18641, 18641, 18675, 18675, 
18675, 18675, 18675, 18675, 18675, 18675, 18675, 18675, 18675, 
18675, 18675, 18675, 18675, 18675, 18675, 18675, 18675, 18675, 
18675, 18675, 18675, 18675, 18675, 18675, 18675, 18676, 18676, 
18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 
18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 
18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 
18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 
18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 18676, 
18676, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 
18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 
18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 
18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 
18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 18677, 
18677, 18677, 18677, 18677, 18678, 18678, 18678, 18678, 18678, 
18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 
18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 
18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 
18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 18678, 
18678, 18678, 18678, 18678, 18678, 18678, 18678, 18679, 18679, 
18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 
18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 
18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 
18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 
18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 18679, 
18679), class = "Date"), Time = structure(c(1607126400, 1607162400, 
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1613899800), class = c("POSIXct", "POSIXt"), tzone = "GMT"), 
    UR = c(89.7, 53.2, 46.9, 45.6, 45.3, 36.4, 36.4, 39.2, 40.4, 
    42.2, 43.8, 45.5, 51.7, 59.8, 65.3, 74.5, 80.7, 85.2, 87.1, 
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    84, 72.1, 70.4, 58.2, 56.4, 42.6, 44.4, 45.1, 92.1, 38.5, 
    42.4, 53.3, 77.9, 80, 75.3, 68.4, 57.6, 49.9, 58.7, 69.5, 
    70.4, 72.9, 72.8, 81, 84.9, 89.7, 91.5, 92.5, 92.5, 93.2, 
    93.3, 92.8, 93.6, 94.1, 94.3, 94, 94, 93.4, 92.2, 93.5, 93.5, 
    92.7, 93.7, 93.8, 93.9, 93.7, 92.1, 87.9, 83.8, 61.2, 41.8, 
    34.3, 39, 34.3, 33.1, 40.7, 92.3, 36.3, 38, 36.4, 40.9, 49, 
    39.7, 44.4, 42, 41.3, 50.4, 54.4, 62.7, 68.3, 72.7, 75.3, 
    79.9, 83.1, 85.1, 85, 85.7, 93.4, 93.7, 85.3, 86.6, 88.8, 
    88.6, 88.5, 88.7, 89.6, 90.4, 93.4, 93.4, 93, 93.7, 93.4, 
    94.2, 94.3, 92.6, 86.8, 82.6, 66.1, 48.9, 44.4, 40.3, 40.6, 
    37.5, 35.6, 91.3, 53.9, 39.1, 38.1, 36.2, 42.3, 43.6, 52.5, 
    66, 79.2, 79.4, 75.3, 78.6, 79.7, 84.3, 84.6, 87.3, 90.3, 
    91.5, 92, 92.8, 91.2, 90.5, 92.5, 92.7, 92.4, 92.6, 92.9, 
    93.3, 93.1, 93.4, 89.1, 88, 91.5, 87.7, 88.2, 89, 90, 88.8, 
    86.5, 83.3, 76.9, 66.3, 61.8, 69, 71.3, 53.9, 54.5, 93.9, 
    71.4, 66.6, 58.1, 58.3, 52.1, 52.2, 54.2, 54.8, 67.8, 69.4, 
    77.1, 82.7, 84, 84.4, 89.1, 92.2, 93.5, 93.6, 94.5, 94.1, 
    94.1, 94.4, 94.3, 94.8, 95, 95.4, 95.3, 94.8, 95.3, 95.3, 
    94.5, 94.5, 93.8, 94.7, 95, 95.1, 95.1, 95, 93.1, 91.8, 90.8, 
    87.7, 81, 74.1, 72.5, 65.5, 71.5, 91.7, 31.2, 29.1, 32.6, 
    33.5, 34.1, 32.9, 32.8, 33.1, 34.4, 34.5, 38.6, 43.7, 51.6, 
    62.4, 71, 78, 80.9, 82.6, 85.3, 86.7, 91.1, 91.5, 87.6, 87.1, 
    88.4, 89.7, 90.6, 91.3, 90.9, 91.7, 92.6, 93.1, 91.2, 93.2, 
    93.5, 93.9, 94.4, 94.4, 92.4, 88.8, 80.7, 62.5, 48.6, 44.2, 
    49.7, 35.7, 30.9, 92.4, 35.3, 34.7, 29.8, 30.7, 30.9, 31.1, 
    30.8, 32, 31.6, 32.1, 35, 40.2, 46.5, 51.8, 64.4, 74.6, 81.6, 
    85.1, 86.9, 87.9, 91.6, 91.1, 89.3, 89.8, 90.2, 89.3, 89.8, 
    90.8, 91.4, 92, 91.6, 90.8, 92.2, 91.8, 92.4, 92, 92.6, 91.8, 
    86.5, 82.4, 78.1, 62.3, 57.1, 48.6, 37.8, 34.2, 32.1, 91.4, 
    29.1, 30.1, 28.5, 29.1, 30.4, 30.9, 31.4, 33.1, 33.8, 34, 
    35.5, 42.5, 47.8, 57.1, 60.5, 67.4, 74.9, 80.5, 83.1, 85.2, 
    91.9, 92.3, 87.3, 87.5, 87.7, 87.3, 87.8, 88.5, 89.2, 90, 
    92.3, 92.6, 91.6, 91.8, 91.4, 91.3, 91.4, 91.6, 89.8, 87.4, 
    81.9, 56.8, 38.8, 34.4, 30.3, 29.4, 29.7, 90.7, 30.9, 28.4, 
    29.1, 30.4, 31.4, 31.7, 32.8, 33.3, 31.8, 34.4, 36.7, 39.7, 
    45.8, 51.9, 59.4, 70.5, 78.2, 82.5, 85.8, 87.6, 91.2, 91.4, 
    87.4, 87.4, 87.4, 88, 88.7, 89.2, 89.8, 90.5, 91.3, 91, 91.1, 
    91.3, 91.6, 91.9, 92.3, 91.6, 89, 85.8, 82.9, 53.2, 41.7, 
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data for breaks:

dias<-saldo%>%subset(V2=="00:00:00")%>%select(Time,UNIX)

graph script (Figure 1):

ggplot(exe2,aes(x=Time,y=UR,group=V1))+geom_line()+
  scale_x_datetime(date_labels ="%y-%m-%d %H",breaks=dias$Time)+theme_bw()+theme(axis.text.x=element_text(angle=90, hjust=1))
r ggplot2

1 answer

2

One possible way to solve the problem is with facet_*. The graph is divided into three, one for each group. For this, a variable is created faceta. The breaks are omitted since dias$Time is not in the question.

library(dplyr)
library(ggplot2)

exe2 %>%
  mutate(faceta = cumsum(c(TRUE, diff(exe2$V1) > 1)),
         faceta = paste("Grupo", faceta)) %>%
  ggplot(aes(Time, UR, group = V1)) +
  geom_line() +
  scale_x_datetime(
    date_labels = "%y-%m-%d %H"
    #,
    #breaks = dias$Time
  ) +
  facet_wrap(~ faceta, scales = "free_x") +
  theme_bw() +
  theme(axis.text.x = element_text(angle = 90, hjust = 1))

inserir a descrição da imagem aqui

  • Yes, I thought, and I still omit the strip, but as this is just an example in the real data, would be group 1 with 30 days, 2 with 10, and 3 with 3, days, at plotting time, the part of group 1 would be "squeezed" in relation to the others, I would like something with better fluidity. Anyway, thanks for the effort.

  • 1

    Replace the facet_wrap... for facet_grid(~ faceta, scales = "free_x", space = "free_x"). Thus each facet will have width proportional to the length of the X-axis.

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