问题

我有一个数据集，其中包含关于出现在我进行评估的地方的物种的一些指标。同一物种可能在同一地方多次出现，因为每个地方都有不同的坐标位置。

这是数据集的样本：

我想要按地点从唯一物种中总结列 score 的值（均值、中位数、偏差和方差）。我尝试使用 dplyr 如下所示：

library(dplyr)
dataSpp %>% group_by(PLACE) %>% summarise_each(funs(n_distinct(.)))

但这并没有起作用。我应该做什么呢？

library(dplyr)
dataSpp %>% group_by(PLACE) %>% summarise_each(funs(n_distinct(.)))

答案1

得分: 0

library(tidyverse)

df <- tibble::tribble(
  ~PLACE,                     ~species,   ~score,
  348L,  "Cercopithecus mitis mitis", 4.950851,
  597L,           "Acinonyx jubatus", 6.332438,
  597L,           "Acinonyx jubatus", 6.332438,
  597L, "Acomys johannis cineraceus", 4.655138,
  597L,         "Aepyceros melampus", 5.646404,
  873L,         "Aepyceros melampus", 5.668386,
  873L,         "Aepyceros melampus", 5.668386,
  873L,      "Alcelaphus buselaphus", 5.075547
)

df %>%
  distinct() %>%
  summarize(
    mean = mean(score),
    median = median(score),
    sd = sd(score),
    .by = c(PLACE)
  )
#> # A tibble: 3 × 4
#>   PLACE  mean median     sd
#>   <int> <dbl>  <dbl>  <dbl>
#> 1   348  4.95   4.95 NA    
#> 2   597  5.54   5.65  0.843
#> 3   873  5.37   5.37  0.419

^{Created on 2023-03-21 with reprex v2.0.2}

<details>
<summary>英文:</summary>

``` r
library(tidyverse)

df &lt;- tibble::tribble(
  ~PLACE,                     ~species,   ~score,
  348L,  &quot;Cercopithecus mitis mitis&quot;, 4.950851,
  597L,           &quot;Acinonyx jubatus&quot;, 6.332438,
  597L,           &quot;Acinonyx jubatus&quot;, 6.332438,
  597L, &quot;Acomys johannis cineraceus&quot;, 4.655138,
  597L,         &quot;Aepyceros melampus&quot;, 5.646404,
  873L,         &quot;Aepyceros melampus&quot;, 5.668386,
  873L,         &quot;Aepyceros melampus&quot;, 5.668386,
  873L,      &quot;Alcelaphus buselaphus&quot;, 5.075547
)

df |&gt;
  distinct() |&gt;
  summarize(
    mean = mean(score),
    median = median(score),
    sd = sd(score),
    .by = c(PLACE)
  )
#&gt; # A tibble: 3 &#215; 4
#&gt;   PLACE  mean median     sd
#&gt;   &lt;int&gt; &lt;dbl&gt;  &lt;dbl&gt;  &lt;dbl&gt;
#&gt; 1   348  4.95   4.95 NA    
#&gt; 2   597  5.54   5.65  0.843
#&gt; 3   873  5.37   5.37  0.419

^{Created on 2023-03-21 with reprex v2.0.2}