Question

我面临着计算长格式数据均值的问题。

我使用的数据集很长很复杂，所以我将重现4个案例。

dta = structure(list(idno = c(12501, 12501, 12501, 12501, 12501, 12502, 
12502, 12502, 12502, 12502, 12502, 12502, 12502, 12502, 12502, 
12502, 12502, 12591, 12591, 12591, 12591, 12591, 12591, 12591, 
12591, 12591, 12591, 12591, 12591, 12591, 12591, 12591, 12592, 
12592, 12592, 12592, 12592), isex = structure(c(1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L), .Label = c("FEMALE", "MALE"), class = "factor"), children = c(0, 
   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 
   1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), variable = structure(c(1L, 
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
144L, 1L, 2L, 3L, 4L, 5L, 135L, 136L, 137L, 138L, 139L, 140L, 
141L, 142L, 143L, 144L, 1L, 2L, 3L, 4L, 5L), .Label = c("act1.001", 
"act1.002", "act1.003", "act1.004", "act1.005", "act1.006", "act1.007", 
"act1.008", "act1.009", "act1.010", "act1.011", "act1.012", "act1.013", 
"act1.014", "act1.015", "act1.016", "act1.017", "act1.018", "act1.019", 
"act1.020", "act1.021", "act1.022", "act1.023", "act1.024", "act1.025", 
"act1.026", "act1.027", "act1.028", "act1.029", "act1.030", "act1.031", 
"act1.032", "act1.033", "act1.034", "act1.035", "act1.036", "act1.037", 
"act1.038", "act1.039", "act1.040", "act1.041", "act1.042", "act1.043", 
"act1.044", "act1.045", "act1.046", "act1.047", "act1.048", "act1.049", 
"act1.050", "act1.051", "act1.052", "act1.053", "act1.054", "act1.055", 
"act1.056", "act1.057", "act1.058", "act1.059", "act1.060", "act1.061", 
"act1.062", "act1.063", "act1.064", "act1.065", "act1.066", "act1.067", 
"act1.068", "act1.069", "act1.070", "act1.071", "act1.072", "act1.073", 
"act1.074", "act1.075", "act1.076", "act1.077", "act1.078", "act1.079", 
"act1.080", "act1.081", "act1.082", "act1.083", "act1.084", "act1.085", 
"act1.086", "act1.087", "act1.088", "act1.089", "act1.090", "act1.091", 
"act1.092", "act1.093", "act1.094", "act1.095", "act1.096", "act1.097", 
"act1.098", "act1.099", "act1.100", "act1.101", "act1.102", "act1.103", 
"act1.104", "act1.105", "act1.106", "act1.107", "act1.108", "act1.109", 
"act1.110", "act1.111", "act1.112", "act1.113", "act1.114", "act1.115", 
"act1.116", "act1.117", "act1.118", "act1.119", "act1.120", "act1.121", 
"act1.122", "act1.123", "act1.124", "act1.125", "act1.126", "act1.127", 
"act1.128", "act1.129", "act1.130", "act1.131", "act1.132", "act1.133", 
"act1.134", "act1.135", "act1.136", "act1.137", "act1.138", "act1.139", 
"act1.140", "act1.141", "act1.142", "act1.143", "act1.144"), class = "factor"), 
   value = structure(c(8L, 9L, 9L, 9L, 9L, 8L, 8L, 8L, 8L, 8L, 
   8L, 8L, 8L, 8L, 8L, 8L, 8L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
   1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("a Sleep", 
   "c Work", "e Travel/Commute", "f Cooking", "g Housework", 
   "h Odd jobs", "i Eating", "j Child care", "k Care for others", 
   "m Leisure", "u TV/Radio", "v Others", "t Visiting/Socialising", 
   "p Telephone/Online Communication", "b Personal care", "d Studies/library", 
   "s Religious", "l Shopping", "q Computing/Internet", "n Highbrow", 
   "o Sport", "r Civic"), class = "factor"), sleep = c(0, 0, 
   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 
   10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 
   10, 10)), .Names = c("idno", "isex", "children", "variable", 
"value", "sleep"), row.names = c(1L, 2L, 3L, 4L, 5L, 145L, 146L, 
 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 155L, 288L, 289L, 
 290L, 291L, 292L, 293L, 423L, 424L, 425L, 426L, 427L, 428L, 429L, 
 430L, 431L, 432L, 433L, 434L, 435L, 436L, 437L), class = "data.frame")

前5行看起来像这样。

     idno   isex children variable             value sleep
1   12501 FEMALE        0 act1.001      j Child care     0
2   12501 FEMALE        0 act1.002 k Care for others     0
3   12501 FEMALE        0 act1.003 k Care for others     0
4   12501 FEMALE        0 act1.004 k Care for others     0
5   12501 FEMALE        0 act1.005 k Care for others     0

idno是个人识别符，然后是性别，孩子，时间戳，活动以及我为睡眠创建假人的最后一行。

如果我使用聚合

aggregate(sleep ~ isex, data = dta, FUN = sum)
150 / 2 # 2 women in my dataset
50 / 2 # 2 men in my dataset

我得到mean女性睡眠时间为75分钟，男性为25分钟。

使用summarise，我可以按性别计算此类所有活动的sum。我们可以看到睡眠的总和是正确的。

dta %>% 
 group_by(isex, value, add = T) %>% 
 summarise(smn = n()*10) 

    isex             value smn
1 FEMALE           a Sleep 150
2 FEMALE      j Child care  10
3 FEMALE k Care for others  40
4   MALE           a Sleep  50
5   MALE      j Child care 120

我的问题是，我现在需要将此smn和除以正确的n组（因此，在此最小示例2和2中）。

所以简单地使用mean无效

dta %>% 
 group_by(isex, value, add = T) %>% 
 summarise(smn = n()*10, mean(smn) )

使用distinct并未向我提供活动

的正确总和

dta %>% 
  distinct(idno) %>%  
  group_by(isex, value, add = T) %>% 
  summarise(smn = n()*10)

所以我需要使用distinct来获得正确的总和来将我的活动总数除以计算这一活动总和。因此distinct应该在第一个summarise 之后使用。我不知道该怎么做。

有任何线索吗？

所需的输出

isex value smn mean 1 FEMALE a Sleep 150 75 2 FEMALE j Child care 10 5 3 FEMALE k Care for others 40 20 4 MALE a Sleep 50 25 5 MALE j Child care 120 60

有一件事：我的问题是，在我的原始数据集中，男性/女性（或其他群体）的数量不均匀，因此我想避免手动划分。

Answer 1

嗯，我想将group_by重新用于add=TRUE是一种方式：

dta %>% 
  group_by(isex) %>% 
  mutate( ng = n_distinct(idno) ) %>% 
  group_by(value,add=TRUE) %>%
  summarise( smn = 10*n(), mean = 10*n()/ng[1] )
#     isex             value smn mean
# 1 FEMALE           a Sleep 150   75
# 2 FEMALE      j Child care  10    5
# 3 FEMALE k Care for others  40   20
# 4   MALE           a Sleep  50   25
# 5   MALE      j Child care 120   60

也可能有一些方法可以使用其中一个dplyr连接函数。

计算长格式的平均值 - n_distinct问题和group_by问题

1 个答案: