计算一个数据框中某一列中某个因子的出现次数并在另一个数据框中输出答案

【问题标题】：Count occurrences of a factor in a column in one dataframe and output in another计算一个数据框中某一列中某个因子的出现次数并在另一个数据框中输出
【发布时间】：2021-09-17 19:22:51
【问题描述】：

我是新来的，我绝对需要您的帮助：我想计算数据框中 4 个类别的因子出现次数（1 列，2 个级别）和行数（或观察值）并显示在另一个汇总数据框中输出。

我解释说：我做了一个实验，我测量了放在假贻贝床上的动物（帽贝）的壳温度。我想知道在每个时间点、侵染程度和复制情况下，我的动物有多少暴露或庇护（位置）。

这是我的第一个数据框（动物群）的样子：

> dput(infauna)
structure(list(date = c("14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021", 
"14/04/2021", "14/04/2021", "14/04/2021", "14/04/2021"), day.type = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "sunny", class = "factor"), 
    time = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("0", 
    "30", "60", "90"), class = "factor"), real.time = c("10:55", 
    "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", 
    "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", 
    "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", 
    "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", 
    "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", "10:55", 
    "10:55", "10:55", "10:55", "10:55", "11:25", "11:25", "11:25", 
    "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", 
    "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", 
    "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", "11:25", 
    "11:25", "11:25", "11:25", "11:25", "11:55", "11:55", "11:55", 
    "11:55", "11:55", "11:55", "11:55", "11:55", "11:55", "11:55", 
    "11:55", "11:55", "11:55", "11:55", "11:55", "11:55", "11:55", 
    "11:55", "11:55", "11:55", "11:55", "12:25", "12:25", "12:25", 
    "12:25", "12:25", "12:25", "12:25", "12:25", "12:25", "12:25", 
    "12:25", "12:25", "12:25", "12:25", "12:25", "12:25", "12:25", 
    "12:25", "12:25", "12:25", "12:25", "12:25", "12:25"), infauna = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L), .Label = "Scutellastra granularis", class = "factor"), 
    infestation = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
    2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
    2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
    2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
    2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("clean", 
    "infested"), class = "factor"), replicate = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L), .Label = c("1", "2", "3"), class = "factor"), 
    specimen = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 
    5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 
    7L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 
    2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 
    6L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 1L, 2L, 3L, 
    4L, 1L, 2L, 3L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 1L, 2L, 3L, 4L, 
    1L, 2L, 3L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 1L, 2L, 3L, 4L, 
    1L, 2L, 3L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L), shell.temp = c(23.5, 
    24.1, 24, 23.8, 23.9, 23.1, 22.7, 23.3, 24.3, 24.4, 23.6, 
    24.2, 23.2, 25, 26.5, 25, 25.4, 24.3, 25.9, 22.6, 25, 26.4, 
    25, 24.8, 25.7, 24.1, 24.6, 24.9, 24, 25, 23.4, 24.2, 24.5, 
    25.3, 26.2, 26.6, 25.8, 25.7, 25.8, 25.3, 32.3, 30.2, 31.4, 
    32.4, 29.8, 33.8, 36, 36.4, 35.2, 37.5, 33.9, 30.4, 29.7, 
    35.8, 32.9, 28.2, 27.7, 35.3, 36.1, 35.8, 34.8, 33.2, 32.7, 
    28.1, 31.4, 31, 37, 30.6, 36.3, 37.1, 35.7, 34.3, 38.6, 36.4, 
    38, 33, 29.7, 32.2, 36.2, 38.3, 39, 37.1, 33.7, 35.3, 36.5, 
    30.1, 38.2, 36.2, 33.7, 36.2, 37.6, 38.6, 39.4, 34.2, 42.4, 
    39, 40.2, 34.6, 33, 32.7, 32.5, 42, 40.8, 38.1, 35.1, 38.8, 
    31.5, 37.3, 37.4, 36.1, 37.5, 40.1), position = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 
    2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 2L, 1L, 1L), .Label = c("exposed", "sheltered"
    ), class = "factor"), no.software = c("M1", "M2", "M3", "M4", 
    "M5", "M6", "M7", "M1", "M2", "M3", "M4", "M5", "M6", "M1", 
    "M2", "M3", "M4", "M5", "M6", "M7", "M1", "M2", "M3", "M4", 
    "M5", "M6", "M7", "M1", "M2", "M3", "M4", "M5", "M6", "M1", 
    "M2", "M3", "M4", "M5", "M6", "M7", "M1", "M2", "M3", "M4", 
    "M5", "M6", "M1", "M2", "M3", "M4", "M5", "M1", "M2", "M3", 
    "M4", "M5", "M6", "M1", "M2", "M3", "M4", "M1", "M2", "M3", 
    "M4", "M1", "M2", "M3", "M1", "M2", "M3", "M4", "M1", "M2", 
    "M3", "M1", "M2", "M3", "M4", "M1", "M2", "M3", "M1", "M2", 
    "M3", "M4", "M1", "M2", "M3", "M1", "M2", "M3", "M4", "M5", 
    "M1", "M2", "M3", "M1", "M2", "M3", "M4", "M1", "M2", "M3", 
    "M1", "M2", "M3", "M4", "M5", "M1", "M2", "M3")), row.names = c(NA, 
-112L), class = "data.frame")

这是一项正在进行的科学研究，因此请不要过于广泛地分享此数据集 :)

我开始创建一个数据框来总结平均壳温、标准偏差和每个时间点的动物数量、侵染程度、复制和位置，使用以下代码（感谢 cmets）：

library(dplyr)
infauna.mean <- infauna %>%
  group_by(time, infestation, replicate, position, .drop = FALSE) %>%
  summarise(shell.mean = mean(shell.temp, na.rm=TRUE), 
            shell.sd = sd(shell.temp, na.rm=TRUE))

这在新数据框 (infauna.mean) 中为我提供了以下输出：

> dput(infauna.mean)
structure(list(time = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 60L, 
60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 90L, 90L, 90L, 
90L, 90L, 90L, 90L, 90L, 90L, 90L), infestation = c("clean", 
"clean", "clean", "clean", "clean", "infested", "infested", "infested", 
"infested", "infested", "infested", "clean", "clean", "clean", 
"clean", "clean", "infested", "infested", "infested", "infested", 
"infested", "infested", "clean", "clean", "clean", "clean", "clean", 
"infested", "infested", "infested", "infested", "infested", "infested", 
"clean", "clean", "clean", "clean", "infested", "infested", "infested", 
"infested", "infested", "infested"), replicate = c(1L, 2L, 2L, 
3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 3L, 3L, 1L, 1L, 2L, 
2L, 3L, 3L, 1L, 1L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 2L, 
3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L), position = c("exposed", "exposed", 
"sheltered", "exposed", "sheltered", "exposed", "sheltered", 
"exposed", "sheltered", "exposed", "sheltered", "exposed", "sheltered", 
"exposed", "exposed", "sheltered", "exposed", "sheltered", "exposed", 
"sheltered", "exposed", "sheltered", "exposed", "sheltered", 
"exposed", "exposed", "sheltered", "exposed", "sheltered", "exposed", 
"sheltered", "exposed", "sheltered", "exposed", "exposed", "exposed", 
"sheltered", "exposed", "sheltered", "exposed", "sheltered", 
"exposed", "sheltered"), shell.mean = c(23.8333333333333, 25.38, 
24.35, 25.9, 25.3, 23.7333333333333, 22.7, 25.35, 22.6, 24.36, 
24.2, 36.275, 33.9, 35.5, 37, 30.8, 31.85, 31.55, 34.35, 29, 
32.4333333333333, 28.1, 38.3, 36.4, 38.1333333333333, 37.2, 33.7, 
36.7, 35, 34.6, 30.95, 35.9, 31.9, 40.5333333333333, 40.3, 38.8, 
36.1, 37.95, 34.2, 34.6, 32.7333333333333, 37.8333333333333, 
33.3), shell.sd = c(0.53166405433005, 0.664830805543786, 0.353553390593274, 
0.447213595499958, NA, 0.372379734500505, NA, 0.771362431027075, 
NA, 0.66558245169175, NA, 0.956991814663705, NA, 0.57154760664941, 
NA, 0.282842712474618, 0.636396103067892, 1.88591268797542, 2.05060966544099, 
1.26227308191743, 0.929157324317759, NA, 0.42426406871193, NA, 
0.960902353693304, 1.4142135623731, NA, 0.565685424949241, 0.989949493661171, 
2.26274169979695, 1.76776695296637, 0.848528137423859, 2.54558441227157, 
1.72433562085034, 1.99749843554382, 1.83847763108502, NA, 1.37961347243832, 
NA, NA, 0.251661147842358, 0.838649708360608, 2.54558441227157
)), row.names = c(NA, -43L), groups = structure(list(time = c(0L, 
0L, 0L, 0L, 0L, 0L, 30L, 30L, 30L, 30L, 30L, 30L, 60L, 60L, 60L, 
60L, 60L, 60L, 90L, 90L, 90L, 90L, 90L, 90L), infestation = c("clean", 
"clean", "clean", "infested", "infested", "infested", "clean", 
"clean", "clean", "infested", "infested", "infested", "clean", 
"clean", "clean", "infested", "infested", "infested", "clean", 
"clean", "clean", "infested", "infested", "infested"), replicate = c(1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L), .rows = structure(list(1L, 2:3, 
    4:5, 6:7, 8:9, 10:11, 12:13, 14L, 15:16, 17:18, 19:20, 21:22, 
    23:24, 25L, 26:27, 28:29, 30:31, 32:33, 34L, 35L, 36:37, 
    38:39, 40:41, 42:43), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -24L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = FALSE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

我想在此数据框中再添加两列，其中包含以下信息：

nb.position ：每组暴露或庇护的动物数量 - 转换为给定组的“位置”列中“暴露”或“庇护”的出现次数（例如 t=0，infestation=clean，replicate=1，position=exposed，nb.position = 6）
nb.visible ：每组可见的动物总数 - 转换为给定组的行数（观察）（例如 t=0，infestation=clean，复制=1，位置=暴露/遮蔽，nb.visible = 6)

我尝试了几个在这里和那里清除的代码，但没有成功。这是我在 Excel 上手动完成的预期输出的虚拟版本：

> dput(infauna.mean)
structure(list(time = c(0L, 30L, 60L, 90L, 0L, 30L, 60L, 90L, 
0L, 30L, 60L, 90L, 0L, 30L, 60L, 90L, 0L, 30L, 60L, 90L, 0L, 
30L, 60L, 90L), infestation = c("clean", "clean", "clean", "clean", 
"infested", "infested", "infested", "infested", "clean", "clean", 
"clean", "clean", "infested", "infested", "infested", "infested", 
"clean", "clean", "clean", "clean", "infested", "infested", "infested", 
"infested"), replicate = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), 
    position = c("exposed", "exposed", "exposed", "exposed", 
    "exposed", "exposed", "exposed", "exposed", "exposed", "exposed", 
    "exposed", "exposed", "exposed", "exposed", "exposed", "exposed", 
    "exposed", "exposed", "exposed", "exposed", "exposed", "exposed", 
    "exposed", "exposed"), shell.mean = c(23.8333, 36.275, 38.3, 
    40.5333, 23.7333, 31.85, 36.7, 37.95, 25.38, 35.5, 38.1333, 
    40.3, 25.35, 34.35, 34.6, 34.6, 25.9, 37, 37.2, 38.8, 24.36, 
    32.4333, 35.9, 37.8333), shell.sd = c("0,5317", "0,9570", 
    "0,4243", "1,7243", "0,3724", "0,6364", "0,5657", "1,3796", 
    "0,6648", "0,5715", "0,9609", "1,9975", "0,7714", "2,0506", 
    "2,2627", "na", "0,4472", "na", "1,4142", "1,8385", "0,6656", 
    "0,9292", "0,8485", "0,8386"), nb.position = c(6L, 4L, 2L, 
    3L, 6L, 2L, 2L, 4L, 5L, 4L, 3L, 3L, 6L, 2L, 2L, 1L, 6L, 1L, 
    2L, 2L, 5L, 3L, 2L, 3L), x.position = c(0.75, 0.5, 0.25, 
    0.38, 0.75, 0.25, 0.25, 0.5, 0.63, 0.5, 0.38, 0.38, 0.75, 
    0.25, 0.25, 0.13, 0.75, 0.13, 0.25, 0.25, 0.63, 0.38, 0.25, 
    0.38), nb.visible = c(6L, 5L, 3L, 3L, 7L, 6L, 4L, 5L, 7L, 
    4L, 3L, 3L, 7L, 6L, 4L, 4L, 7L, 3L, 3L, 3L, 6L, 4L, 4L, 5L
    ), x.visible = c(0.75, 0.63, 0.38, 0.38, 0.88, 0.75, 0.5, 
    0.63, 0.88, 0.5, 0.38, 0.38, 0.88, 0.75, 0.5, 0.5, 0.88, 
    0.38, 0.38, 0.38, 0.75, 0.5, 0.5, 0.63)), class = "data.frame", row.names = c(NA, 
-24L))

“x.position”和“x.visible”列只是我为图形目的所做的百分比。

请注意，我实际上是一名博士生，很遗憾我没有对 R 的支持。我的主管和同事使用 Excel 和 Statistica，但我还有 8 个像这样的数据集，我不想这样做所有的计数都是手工计算的（我不想成为穴居人 TT）。

如果您需要更多详细信息，请不要犹豫，非常感谢您抽出宝贵时间！社区的任何帮助都将在我的论文和我未来发表的论文中得到承认；）

【问题讨论】：

请通过写dput(infauna) 分享您的数据并将结果包含在代码块中。此外，如果您更简洁地说明您想要的输出，它将帮助您获得好的答案。
@AndyEggers 感谢您的建议！

标签： r dataframe counting

【解决方案1】：

我们也可以使用

library(dplyr)
result <- infauna %>%
            group_by(across(c(time:position, -shell.temp, -specimen)))%>%
            summarise(across(shell.temp, list(mean = ~ mean(., na.rm = TRUE),
                        sd = ~ sd(., na.rm = TRUE))), .groups = 'drop')

【讨论】：

您的代码给了我以下错误消息：Error: Problem with 'summarise()' input '..1'. x Can't subset columns that don't exist. x Column 'shell.temp' doesn't exist. i Input '..1' is '(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...'. i The error occurred in group 1: time = 0, real.time = "10:55", infauna = "Scutellastra granularis", infestation = "clean", replicate = 1, specimen = 1, shell.temp = 23.3, position = "exposed".@Ronak Shah 在下面的评论中的代码运行良好！
@AlexiaDIEVART 我假设您的数据中有shell.temp 列。可能你有一个旧版本的dplyr。你能查一下packageVersion('dplyr')
我检查了dput 的infauna.mean。没有'shell.temp'。由于infauna dput 没有显示，虽然不清楚
我确实在发布问题后添加了infauna 的dput，对不起！ infauna.mean 不包含 shell.temp 列（指单个观察值），因为操作的目的是为此数据框中的每个类别获取 shell.mean 和 shell.sd 列。我的dplyr 版本是1.0.5，是旧的吗？我觉得你的代码中的问题可能是函数across()的使用，下面是list()，但我不是编码专家。你怎么看？
@AlexiaDIEVART 真正的问题是time:position 还包括范围内的“shell.temp”。我们必须删除带有-shell.temp 的那些。请查看更新。

【解决方案2】：

对于这样的计算，我建议使用dplyr，因为它可以很方便地进行多次计算。如果您的列是因子，请使用.drop = FALSE 来保留所有值。

library(dplyr)

result <- infauna %>%
  group_by(time, infestation, replicate, position, .drop = FALSE) %>%
  summarise(shell.mean = mean(shell.temp, na.rm=TRUE), 
            shell.sd = sd(shell.temp, na.rm=TRUE))

【讨论】：