r - ggplot 将平均线添加到特定月份的方面

Question

我正在尝试为我拥有的每一年的时间序列 ggplot 图添加“3”月的“平均”线。

我想通过 facets 的平均值画一条水平线- 我试过group_by , mutate等，但不能让它工作。

预期输出将只是基于每个方面的水平线，基于该方面的月“3”平均值。

代码:

dat %>% 
  ggplot(aes(x = day, y = NO2)) +
  geom_line() +
  facet_grid(~year)

数据:

dat <- structure(list(station_location = c("Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen", "Pza del Carmen", "Pza del Carmen", "Pza del Carmen", 
"Pza del Carmen"), date = structure(c(16495, 16496, 16497, 16498, 
16499, 16500, 16501, 16502, 16503, 16504, 16505, 16506, 16507, 
16508, 16509, 16510, 16511, 16512, 16513, 16514, 16515, 16516, 
16517, 16518, 16519, 16520, 16521, 16522, 16523, 16524, 16525, 
16861, 16862, 16863, 16864, 16865, 16866, 16867, 16868, 16869, 
16870, 16871, 16872, 16873, 16874, 16875, 16876, 16877, 16878, 
16879, 16880, 16881, 16882, 16883, 16884, 16885, 16886, 16887, 
16888, 16889, 16890, 16891, 17226, 17227, 17228, 17229, 17230, 
17231, 17232, 17233, 17234, 17235, 17236, 17237, 17238, 17239, 
17240, 17241, 17242, 17243, 17244, 17245, 17246, 17247, 17248, 
17249, 17250, 17251, 17252, 17253, 17254, 17255, 17256, 17591, 
17592, 17593, 17594, 17595, 17596, 17597, 17598, 17599, 17600, 
17601, 17602, 17603, 17604, 17605, 17606, 17607, 17608, 17609, 
17610, 17611, 17612, 17613, 17614, 17615, 17616, 17617, 17618, 
17619, 17620, 17621, 17956, 17957, 17958, 17959, 17960, 17961, 
17962, 17963, 17964, 17965, 17966, 17967, 17968, 17969, 17970, 
17971, 17972, 17973, 17974, 17975, 17976, 17977, 17978, 17979, 
17980, 17981, 17982, 17983, 17984, 17985, 17986), class = "Date"), 
    yvar = c(31, 35, 51, 55, 50, 62, 83, 62, 74, 80, 82, 77, 
    54, 38, 39, 48, 54, 49, 36, 36, 36, 37, 58, 41, 32, 38, 44, 
    57, 40, 54, 69, 70, 57, 48, 45, 35, 33, 39, 46, 46, 43, 50, 
    50, 49, 51, 54, 72, 64, 47, 35, 41, 53, 46, 55, 44, 48, 35, 
    21, 23, 34, 53, 34, 42, 53, 48, 26, 25, 34, 45, 71, 79, 80, 
    59, 31, 30, 43, 44, 45, 58, 65, 59, 43, 33, 29, 37, 50, 48, 
    30, 32, 47, 59, 57, 44, 39, 60, 33, 34, 37, 39, 41, 57, 55, 
    42, 21, 28, 48, 47, 28, 35, 33, 38, 44, 44, 51, 59, 60, 31, 
    39, 55, 47, 47, 28, 20, 30, 56, 49, 34, 13, 22, 16, 18, 34, 
    38, 38, 41, 37, 29, 39, 58, NA, NA, NA, 29, 30, 42, 44, 33, 
    29, 32, 24, 44, 48, 34, 27, 26), year = c(2015L, 2015L, 2015L, 
    2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 
    2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 
    2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 
    2015L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 
    2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 
    2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 
    2016L, 2016L, 2016L, 2016L, 2016L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2019L, 2019L, 2019L, 2019L, 2019L, 
    2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 
    2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 
    2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L), 
    month = c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), day = c(1L, 2L, 3L, 4L, 
    5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
    18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 
    30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
    13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 
    25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 
    7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
    19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
    31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 
    14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 
    26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
    8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
    20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L
    )), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-155L))

Answer 1

您可以使用 geom_smooth，并适合仅拦截线:

dat %>% 
ggplot(aes(x = day, y = yvar)) +
geom_line() +
geom_smooth(method="lm",formula=y~1,se=FALSE)+
facet_grid(~year)

这是有效的，因为如果你拟合一个线性模型，例如 lm(y~1)，这是一个仅截距模型，截距将是平均值。