geom_text和暂停动画的问题

时间：2019-03-01 13:41:48

标签： r ggplot2 gganimate

我正在尝试复制以下代码（thomasp85/gganimate）。我有两个问题：

  1. 我不想显示第一个geom_point的标签（变量：partidos）；
  2. 我希望动画结束后，显示最后geom_point的标签（变量：partidos）几秒钟。

    dput(polls_)
structure(list(week = structure(c(1551571200, 1551571200, 1551571200, 
1551571200, 1551571200, 1550966400, 1550966400, 1550966400, 1550966400, 
1550966400, 1550361600, 1550361600, 1550361600, 1550361600, 1550361600, 
1549756800, 1549756800, 1549756800, 1549756800, 1549756800, 1549152000, 
1549152000, 1549152000, 1549152000, 1549152000, 1548547200, 1548547200, 
1548547200, 1548547200, 1548547200, 1547942400, 1547942400, 1547942400, 
1547942400, 1547942400, 1547337600, 1547337600, 1547337600, 1547337600, 
1547337600, 1546732800, 1546732800, 1546732800, 1546732800, 1546732800, 
1546128000, 1546128000, 1546128000, 1546128000, 1546128000, 1545523200, 
1545523200, 1545523200, 1545523200, 1545523200, 1544918400, 1544918400, 
1544918400, 1544918400, 1544918400, 1544313600, 1544313600, 1544313600, 
1544313600, 1544313600, 1543708800, 1543708800, 1543708800, 1543708800, 
1543708800, 1541894400, 1541894400, 1541894400, 1541894400, 1541894400, 
1541289600, 1541289600, 1541289600, 1541289600, 1541289600, 1540684800, 
1540684800, 1540684800, 1540684800, 1540684800, 1540080000, 1540080000, 
1540080000, 1540080000, 1540080000, 1539475200, 1539475200, 1539475200, 
1539475200, 1539475200, 1538870400, 1538870400, 1538870400, 1538870400, 
1538870400), class = c("POSIXct", "POSIXt"), tzone = "UTC"), 
    partidos = c("PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX", "PPopular", "PSOE", "ahorapodemos", "CiudadanosCs", 
    "VOX"), resultados = c(16.7, 33.3, 14.5, 15.3, 5.9, 21, 27.3, 
    14.2, 16, 11.3, 21.75, 25.85, 14.4, 17.9, 10.9, 20.5, 25.4, 
    13.9, 17, 11.7, 21.3, 23.9, 13.5, 20.9, 11.2, 22.25, 23.65, 
    14.85, 19.15, 10.05, 21.5, 23.2, 14.4, 23, 8.9, 19.2, 23.75, 
    16.7, 18, 8.4, 18.3, 24.1, 16.1, 18.5, 11.5, 20.6, 22.6, 
    15.5, 19.65, 10.75, 21.8, 23.5, 15.2, 22.7, 7.8, 21.4, 24.15, 
    16.15, 20.1, 8.6, 22.8, 24.4, 17.2, 19.8, 5.9, 19.7, 23.2, 
    17.65, 18.2, 10.7, 23.35, 26.4, 17.2, 20.15, 1.8, 22.3, 26.6, 
    16.6, 21.9, 3.4, 22.65, 24.95, 17.15, 21.55, 2.55, 22.6, 
    25.2, 17.7, 19.2, 5.1, 26.7, 26.8, 16.8, 19.5, 1.9, 23, 26.2, 
    18, 20.7, 0)), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -100L), vars = "week", indices = list(95:99, 
    90:94, 85:89, 80:84, 75:79, 70:74, 65:69, 60:64, 55:59, 50:54, 
    45:49, 40:44, 35:39, 30:34, 25:29, 20:24, 15:19, 10:14, 5:9, 
    0:4), drop = TRUE, group_sizes = c(5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), biggest_group_size = 5L, labels = structure(list(
    week = structure(c(1538870400, 1539475200, 1540080000, 1540684800, 
    1541289600, 1541894400, 1543708800, 1544313600, 1544918400, 
    1545523200, 1546128000, 1546732800, 1547337600, 1547942400, 
    1548547200, 1549152000, 1549756800, 1550361600, 1550966400, 
    1551571200), class = c("POSIXct", "POSIXt"), tzone = "UTC")), class = "data.frame", row.names = c(NA, 
-20L), vars = "week", indices = list(315:319, 310:314, 305:309, 
    275:304, 270:274, 240:269, 230:239, 195:229, 155:194, 150:154, 
    140:149, 125:139, 95:124, 90:94, 70:89, 65:69, 50:64, 30:49, 
    5:29, 0:4), drop = TRUE, group_sizes = c(5L, 5L, 5L, 30L, 
5L, 30L, 10L, 35L, 40L, 5L, 10L, 15L, 30L, 5L, 20L, 5L, 15L, 
20L, 25L, 5L), biggest_group_size = 40L, labels = structure(list(
    week = structure(c(1538870400, 1539475200, 1540080000, 1540684800, 
    1541289600, 1541894400, 1543708800, 1544313600, 1544918400, 
    1545523200, 1546128000, 1546732800, 1547337600, 1547942400, 
    1548547200, 1549152000, 1549756800, 1550361600, 1550966400, 
    1551571200), tzone = "UTC", class = c("POSIXct", "POSIXt"
    ))), class = "data.frame", row.names = c(NA, -20L), vars = "week", indices = list(
    c(63L, 127L, 191L, 255L, 319L), c(62L, 126L, 190L, 254L, 
    318L), c(61L, 125L, 189L, 253L, 317L), c(55L, 56L, 57L, 58L, 
    59L, 60L, 119L, 120L, 121L, 122L, 123L, 124L, 183L, 184L, 
    185L, 186L, 187L, 188L, 247L, 248L, 249L, 250L, 251L, 252L, 
    311L, 312L, 313L, 314L, 315L, 316L), c(54L, 118L, 182L, 246L, 
    310L), c(48L, 49L, 50L, 51L, 52L, 53L, 112L, 113L, 114L, 
    115L, 116L, 117L, 176L, 177L, 178L, 179L, 180L, 181L, 240L, 
    241L, 242L, 243L, 244L, 245L, 304L, 305L, 306L, 307L, 308L, 
    309L), c(46L, 47L, 110L, 111L, 174L, 175L, 238L, 239L, 302L, 
    303L), c(39L, 40L, 41L, 42L, 43L, 44L, 45L, 103L, 104L, 105L, 
    106L, 107L, 108L, 109L, 167L, 168L, 169L, 170L, 171L, 172L, 
    173L, 231L, 232L, 233L, 234L, 235L, 236L, 237L, 295L, 296L, 
    297L, 298L, 299L, 300L, 301L), c(31L, 32L, 33L, 34L, 35L, 
    36L, 37L, 38L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 
    159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 223L, 224L, 
    225L, 226L, 227L, 228L, 229L, 230L, 287L, 288L, 289L, 290L, 
    291L, 292L, 293L, 294L), c(30L, 94L, 158L, 222L, 286L), c(28L, 
    29L, 92L, 93L, 156L, 157L, 220L, 221L, 284L, 285L), c(25L, 
    26L, 27L, 89L, 90L, 91L, 153L, 154L, 155L, 217L, 218L, 219L, 
    281L, 282L, 283L), c(19L, 20L, 21L, 22L, 23L, 24L, 83L, 84L, 
    85L, 86L, 87L, 88L, 147L, 148L, 149L, 150L, 151L, 152L, 211L, 
    212L, 213L, 214L, 215L, 216L, 275L, 276L, 277L, 278L, 279L, 
    280L), c(18L, 82L, 146L, 210L, 274L), c(14L, 15L, 16L, 17L, 
    78L, 79L, 80L, 81L, 142L, 143L, 144L, 145L, 206L, 207L, 208L, 
    209L, 270L, 271L, 272L, 273L), c(13L, 77L, 141L, 205L, 269L
    ), c(10L, 11L, 12L, 74L, 75L, 76L, 138L, 139L, 140L, 202L, 
    203L, 204L, 266L, 267L, 268L), c(6L, 7L, 8L, 9L, 70L, 71L, 
    72L, 73L, 134L, 135L, 136L, 137L, 198L, 199L, 200L, 201L, 
    262L, 263L, 264L, 265L), c(1L, 2L, 3L, 4L, 5L, 65L, 66L, 
    67L, 68L, 69L, 129L, 130L, 131L, 132L, 133L, 193L, 194L, 
    195L, 196L, 197L, 257L, 258L, 259L, 260L, 261L), c(0L, 64L, 
    128L, 192L, 256L)), drop = TRUE, group_sizes = c(5L, 5L, 
5L, 30L, 5L, 30L, 10L, 35L, 40L, 5L, 10L, 15L, 30L, 5L, 20L, 
5L, 15L, 20L, 25L, 5L), biggest_group_size = 40L)))

anim <- ggplot(polls_, aes(semana, resultados, group = partidos)) + 
  geom_line() + 
  geom_segment(aes(xend = as.POSIXct("2019-03-08 00:00:00", tz="UTC"), yend = resultados), 
               linetype = 2, colour = 'grey') + 
  geom_point(size = 2) + 
  geom_text(aes(x = as.POSIXct("2019-03-15 00:00:00", tz="UTC"), label = partidos),
            hjust = 0) + 
  transition_reveal(semana) + 
  coord_cartesian(clip = 'off') + 
  labs(title = 'Opinion polling for the 2019 Spanish general election', 
       y = 'Estimated results', x = 'week') + 
  theme_minimal() + 
  theme(plot.margin = margin(5.5, 40, 5.5, 5.5))

animate(anim, width = 900, height = 600, fps = 10, rewind = FALSE, duration = 15)

在这里我包括动画：

animation

1 个答案:

答案 0 :(得分：2)

这里有两个步骤可以解决您的两个问题：

  1. 在将数据帧传递到ggplot()之前先对其进行排序：
polls_ <- arrange(polls_, week)
  1. 在end_pause = <some positive integer>中包含animate(anim, ...)。

注意：示例数据框中的列名称为week，而代码使用semana。我要和前者一起去。

说明：

您的数据框的顶部是最新的week值，而最早的是下面的值。这不适用于transition_reveal的默认参数。

来自?transition_reveal：

transition_reveal(along, range = NULL, keep_last = TRUE, id)

其中keep_last是TRUE / FALSE值，用于确定是否应为后续帧保留数据的最后一行。

最早的week行位于此位置时，由于其week的值，它们被安排排在最前面，而由于keep_last = TRUE的原因，它们一直可见到最后。

另一方面，当我们按week对行进行排序时，最新的week值将被排序到最下面的行。现在keep_last = TRUE对我们有利，因为我们希望将这些值保留给所有后续帧-最重要的是，最后一个帧 {1}}变得有用。

演示：

end_pause

result

相关问题
最新问题