自定義dplyr函數和多個參數的ggplot

Question

對於R plz的技術操作，我需要一些幫助。

我的問題：我有一些關於鳥類棲息地的觀察數據，它們是否存在於不同的棲息地類型中。 我想知道根據它們的表面范圍在這些不同生境中觀察的成功率：

data_observation <- data.frame(
  habitat_bush = c(
    0, 0, 0, 0, 10,
    10, 30, 30, 30, 45,
    65, 65, 65, 80, 80,
    80, 90, 95, 100
  ),
  obs = c(
    "yes", "no", "no", "no", "yes",
    "no", "no", "yes", "no", "yes",
    "yes", "no", "yes", "no", "yes",
    "yes", "yes", "yes", "yes"
  )
)

在這里，您只有'habitat_bush'的數據，但還有10個以上的時間棲息地。

在同事的幫助下，我們使此功能可以對“ habitat_bush”的不同面積大小下的觀察成功率進行ggplot繪制：

library(dplyr)
library(ggplot2)
library(scales)


plot_forest_test <- function(data = NULL, habitat_type = NULL, colour = NULL) {
  x <- enquo(habitat_type)
  fill <- enquo(colour)

  ggdata <- data %>%
    select(x = !!x, fill = !!fill) %>%
    mutate(
      group = case_when(
        x == 0 ~ "[0]",
        x > 0.0001 & x < 10.0001 ~ "]0-10]",
        x > 10.0001 & x < 25.0001 ~ "]10-25]",
        x > 25.0001 & x < 50.0001 ~ "]25-50]",
        x > 50.0001 & x < 75.0001 ~ "]50-75]",
        x > 75.0001 ~ "]75- 100]"
      )
    ) %>%
    select(-x) %>%
    group_by(group, fill) %>%
    count() %>%
    group_by(group) %>%
    group_modify(~ mutate(.data = .x, freq = n / sum(n)))

  ggplot(data = ggdata, mapping = aes(x = group, y = freq, fill = fill)) +
    geom_bar(stat = "identity") +
    scale_fill_brewer(palette = "Greens") +
    scale_y_continuous(labels = scales::percent) +
    theme_minimal() +
    labs(x = expr(!!x), fill = expr(!!fill))
}

plot_forest_test(data = data_observation, habitat_type = habitat_bush, colour = obs)

工作很好 但是觀察可以依靠技術人員為尋找鳥類的存在而付出的努力。 所以，我有這樣的數據：

data_observation_2 <- data.frame(
  superficie_essence = c(
    0, 0, 0, 0, 10,
    10, 30, 30, 30, 45,
    65, 65, 65, 80, 80,
    80, 90, 95, 100
  ),
  obs = c(
    "yes", "no", "no", "no", "yes",
    "no", "no", "yes", "no", "yes",
    "yes", "no", "yes", "no", "yes",
    "yes", "yes", "yes", "yes"
  ),
  effort = c(low, low, mid-low, mid-low, low, mid-low, mid-low,
            mid-high, mid-high, high, mid-low, mid-low, mid-high, mid-low, mid-high, high, high, mid-high, high)
)

我的R技能到此為止。 我想要具有相同的先前圖形，但按同一圖形（如多面板圖形）中的每種棲息地類型的方式按effort_type細分。 換句話說，我想通過努力方式將前一個圖的5個子圖與1個小圖一起繪制。 但是我有很多數據，所以我想將這個processu放到像這樣的函數中：

plot_forest_test_2(data = data_observation, habitat_type = habitat_bush, effort = Q_effort, colour = obs)

你能幫我嗎 ？ 謝謝你的幫助 ！

cdlt

Answer 1

不確定性不是我的專長，尤其是當它們可能會丟失但可以嘗試一下時。 我為facet_wrap()面項創建了一個新列，然后添加facet_wrap() 。 您也可以使用facet_grid() 。 希望能幫助到你。

plot_forest_test <- function(data = NULL, habitat_type = NULL, colour = NULL, facet = NULL) {
  x <- enquo(habitat_type)
  fill <- enquo(colour)

  # this is new ####################
  facet <- enquo(facet)
  has_facet <- quo_name(facet) != "NULL"

  df <- 
    data %>% 
    mutate(
      x = !!x, 
      fill = !!fill,
      facet = ""
    )

  if (has_facet) {
    df <- 
      df %>% 
      mutate(facet = !!facet)
  }
  ##################################

  ggdata <- 
    df %>%
    mutate(
      group = case_when(
        x == 0 ~ "[0]",
        x > 0.0001 & x < 10.0001 ~ "]0-10]",
        x > 10.0001 & x < 25.0001 ~ "]10-25]",
        x > 25.0001 & x < 50.0001 ~ "]25-50]",
        x > 50.0001 & x < 75.0001 ~ "]50-75]",
        x > 75.0001 ~ "]75- 100]"
      )
    ) %>%
    select(-x) %>%
    # adding facet here
    group_by(group, fill, facet) %>% 
    count() %>%
    group_by(group, facet) %>%
    arrange(desc(fill)) %>% 
    mutate(
      freq = n/sum(n),
      # these steps set up the label placement
      running_freq = cumsum(freq),
      prev_freq = lag(running_freq, default = 0),
      label_y = (prev_freq + running_freq)/2 ,
      label_n = paste0("n = ", sum(n))
    ) %>% 
    ungroup()

  # create plot w/o facet
  p <-
    ggplot(data = ggdata, mapping = aes(x = group, y = freq, fill = fill)) +
    geom_bar(stat = "identity") +
    geom_hline(yintercept = 0) +
    geom_text(aes(y = -0.05, label = label_n), size = 3.5) +
    #geom_text(aes(y = label_y, label = n)) +
    scale_fill_brewer(palette = "Greens") +
    scale_y_continuous(labels = scales::percent) +
    theme(
      panel.background = element_rect(fill = "white"),
      panel.border = element_rect(color = "grey90", fill = NA)
    ) +
    labs(x = expr(!!x), fill = expr(!!fill))

  # add in if facet was mentioned
  if (has_facet) {
    p <-
      p +
      facet_grid(~facet)
  }

  # return final plot
  p
}

我要對data_observation_2進行編輯，因為字符串不在引號中，並且某些值在連字符周圍有空格，而其他值則沒有。 我使它們全都沒有空間

data_observation_2 <- data.frame(
  superficie_essence = c(
    0, 0, 0, 0, 10,
    10, 30, 30, 30, 45,
    65, 65, 65, 80, 80,
    80, 90, 95, 100
  ),
  obs = c(
    "yes", "no", "no", "no", "yes",
    "no", "no", "yes", "no", "yes",
    "yes", "no", "yes", "no", "yes",
    "yes", "yes", "yes", "yes"
  ),
  effort = c(
    "low", "low", "mid-low", "mid-low", "low", "mid-low", "mid-low",
    "mid-high", "mid-high", "high", "mid-low", "mid-low", 
    "mid-high", "mid-low", "mid-high", "high", "high", "mid-high", "high"
  )
  )
)

最后的結果。 我使用fct_relevel()將它們按順序排列。

plot_forest_test(
  data = data_observation, 
  habitat_type = habitat_bush, 
  colour = obs
)

data_observation_2 %>% 
  mutate(effort = fct_relevel(effort, "low", "mid-low", "mid-high", "high")) %>% 
  plot_forest_test(
    habitat_type = superficie_essence, 
    colour = obs, 
    facet = effort
  )