如果我们的数据集中有多个数值变量具有分组变量的NA，则需要多次使用na.rm = FALSE来查找具有均值函数的每个变量的均值或任何其他统计量。但是我们可以使用dplyr软件包的summarise_all函数来完成此操作，这将导致仅两行代码即可得出所有数值变量的均值。
加载dplyr软件包-
> library(dplyr)
考虑基数R中的ToothGrowth数据集-
> str(ToothGrowth) 'data.frame': 60 obs. of 3 variables: $ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ... $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ... $ dose: num 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ... > grouping_by_supp <- ToothGrowth %>% group_by(supp) > grouping_by_supp %>% summarise_each(funs(mean(., na.rm = TRUE))) # A tibble: 2 x 3 supp len dose <fct> <dbl> <dbl> 1 OJ 20.7 1.17 2 VC 17.0 1.17
考虑基数R中的mtcars数据集-
> str(mtcars) 'data.frame': 32 obs. of 11 variables: $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ... $ cyl : Factor w/ 3 levels "four","six","eight": 2 2 1 2 3 2 3 1 1 2 ... $ disp: num 160 160 108 258 360 ... $ hp : num 110 110 93 110 175 105 245 62 95 123 ... $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ... $ wt : num 2.62 2.88 2.32 3.21 3.44 ... $ qsec: num 16.5 17 18.6 19.4 17 ... $ vs : num 0 0 1 1 0 1 0 1 1 1 ... $ am : num 1 1 1 0 0 0 0 0 0 0 ... $ gear: num 4 4 4 3 3 3 3 4 4 4 ... $ carb: num 4 4 1 1 2 1 4 2 2 4 ... > grouping_by_cyl <- mtcars %>% group_by(cyl) > grouping_by_cyl %>% summarise_each(funs(mean(., na.rm = TRUE))) # A tibble: 3 x 11 cyl mpg disp hp drat wt qsec vs am gear carb <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 four 26.7 105. 82.6 4.07 2.29 19.1 0.909 0.727 4.09 1.55 2 six 19.7 183. 122. 3.59 3.12 18.0 0.571 0.429 3.86 3.43 3 eight 15.1 353. 209. 3.23 4.00 16.8 0 0.143 3.29 3.5
考虑以R为基础的CO2数据集-
> str(CO2) Classes ‘nfnGroupedData’, ‘nfGroupedData’, ‘groupedData’ and 'data.frame': 84 obs. of 5 variables: $ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ... $ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ... $ Treatment: Factor w/ 2 levels "nonchilled","chilled": 1 1 1 1 1 1 1 1 1 1 ... $ conc : num 95 175 250 350 500 675 1000 95 175 250 ... $ uptake : num 16 30.4 34.8 37.2 35.3 39.2 39.7 13.6 27.3 37.1 ... - attr(*, "formula")=Class 'formula' language uptake ~ conc | Plant .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv> - attr(*, "outer")=Class 'formula' language ~Treatment * Type .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv> - attr(*, "labels")=List of 2 ..$ x: chr "Ambient carbon dioxide concentration" ..$ y: chr "CO2 uptake rate" - attr(*, "units")=List of 2 ..$ x: chr "(uL/L)" ..$ y: chr "(umol/m^2 s)" > grouping_by_Type <- CO2 %>% group_by(Type) > grouping_by_Type %>% summarise_all(funs(mean(., na.rm = TRUE))) # A tibble: 2 x 5 Type Plant Treatment conc uptake <fct> <dbl> <dbl> <dbl> <dbl> 1 Quebec NA NA 435 33.5 2 Mississippi NA NA 435 20.9
在mean.default（Plant，na.rm = TRUE）中-参数不是数字或逻辑-返回NA
在mean.default（Plant，na.rm = TRUE）中-参数不是数字或逻辑-返回NA
在mean.default（Treatment，na.rm = TRUE）中-参数不是数字或逻辑-返回NA
在mean.default（Treatment，na.rm = TRUE）中-参数不是数字或逻辑-返回NA
在这里，由于变量Plant和Treatment不是数字，我们收到一些警告消息。