编写R函数，该函数仅在声明时进行子集设置
编写R函数，该函数仅在声明时进行子集设置
提问于 2021-12-13 21:38:57
我正在尝试编写一个函数，从特定列(深度)的数据帧中提取方法和min和max，它可以被两个分类变量分类，因此在函数中，一个是按类型变量分组的。另一个分类变量是在2020年或2021年收集的数据。我希望默认函数提取所有年份的数据，除非在参数中说明，然后按年对数据进行子集。如果我能改变变量(比如长度而不是深度)，那也是很好的。这是我的密码
analysis <- function(data=measurements, yearX=2020){
data %>%
subset(year == yearX) %>% ## Subsets the dataset by specific year
group_by(type) %>% ## groups the data by type
summarise(mBD=mean(depth), sdBD=sd(depth), minBD=min(depth),
maxBD=max(depth), median=median(depth),
range=(max(depth) - min(depth)))
}回答 2
Stack Overflow用户
发布于 2021-12-13 22:01:34
实现您期望的结果的一个选项可能如下所示：
set.seed(123)
measurements <- data.frame(
year = rep(2020:2021, each = 10),
type = rep(c("A", "B")),
length = runif(20),
depth = runif(20)
)
library(dplyr)
analysis <- function(data = measurements, x, yearX = NULL) {
# Subset by year if given
if (!is.null(yearX)) data <- filter(data, year %in% yearX)
data %>%
group_by(type) %>%
summarise(across({{x}}, .fns = list(
mBD = mean,
sdBD = sd,
minBD = min,
maxBD = max,
median = median,
range = ~ diff(range(.x))), .names = "{.fn}"
))
}
analysis(x = depth)
#> # A tibble: 2 × 7
#> type mBD sdBD minBD maxBD median range
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 A 0.577 0.290 0.0246 0.963 0.648 0.938
#> 2 B 0.576 0.299 0.147 0.994 0.643 0.847
analysis(measurements, depth, 2020)
#> # A tibble: 2 × 7
#> type mBD sdBD minBD maxBD median range
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 A 0.604 0.217 0.289 0.890 0.641 0.600
#> 2 B 0.627 0.307 0.147 0.994 0.693 0.847
analysis(measurements, length, 2021)
#> # A tibble: 2 × 7
#> type mBD sdBD minBD maxBD median range
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 A 0.462 0.348 0.103 0.957 0.328 0.854
#> 2 B 0.584 0.370 0.0421 0.955 0.573 0.912Stack Overflow用户
发布于 2021-12-14 06:49:22
为了从函数中使用subset()的方便性，我们可以使用match.call()和match与formalArgs of subset.default一起创建一个subset调用，我们可以使用evaluate。如果没有指定子集，则行类似于省略。
对于剩下的部分，我们定义了一个汇总函数，在这里我们应该定义当有NA's时会发生什么，并在aggregate()中使用它，并使用一个很容易用reformulate()创建的公式。
有了案例处理，我们也可以省略分组。
FUN <- function(..., col, group=NA, na.rm=FALSE) {
cll <- match.call()
m <- match(formalArgs(subset.default), names(cll), 0L)
m <- cll[c(1L, m)]
m[[1L]] <- quote(subset)
dat <- eval(m)
mysum <- function(x) c(mBD=mean(x, na.rm=na.rm), sdBD=sd(x, na.rm=na.rm),
minBD=min(x, na.rm=na.rm), maxBD=max(x, na.rm=na.rm),
median=median(x, na.rm=na.rm),
range=max(x, na.rm=na.rm) - min(x, na.rm=na.rm))
if (!is.na(group)) {
res <- aggregate(reformulate(group, col), dat, mysum)
} else {
res <- mysum(dat[, col])
}
return(res)
}用法
FUN(x=measurements, col='depth', group='type')
# type depth.mBD depth.sdBD depth.minBD depth.maxBD depth.median depth.range
# 1 A 0.57739614 0.29037002 0.02461368 0.96302423 0.64810631 0.93841055
# 2 B 0.57604555 0.29862847 0.14711365 0.99426978 0.64347271 0.84715613
FUN(x=measurements, col='depth', group='type', subset=year == 2020)
# type depth.mBD depth.sdBD depth.minBD depth.maxBD depth.median depth.range
# 1 A 0.6037955 0.2169419 0.2891597 0.8895393 0.6405068 0.6003796
# 2 B 0.6273719 0.3070970 0.1471136 0.9942698 0.6928034 0.8471561
FUN(x=measurements, col='length', group='type', subset=year == 2020)
# type length.mBD length.sdBD length.minBD length.maxBD length.median length.range
# 1 A 0.5433124 0.2457008 0.2875775 0.9404673 0.5281055 0.6528898
# 2 B 0.6131826 0.3633747 0.0455565 0.8924190 0.7883051 0.8468625
FUN(x=measurements, col='depth', group=NA)
# mBD sdBD minBD maxBD median range
# 0.57672085 0.28667353 0.02461368 0.99426978 0.64810631 0.96965609 数据(从斯特凡借用)：
measurements <- structure(list(year = c(2020L, 2020L, 2020L, 2020L, 2020L, 2020L,
2020L, 2020L, 2020L, 2020L, 2021L, 2021L, 2021L, 2021L, 2021L,
2021L, 2021L, 2021L, 2021L, 2021L), type = c("A", "B", "A", "B",
"A", "B", "A", "B", "A", "B", "A", "B", "A", "B", "A", "B", "A",
"B", "A", "B"), length = c(0.287577520124614, 0.788305135443807,
0.4089769218117, 0.883017404004931, 0.940467284293845, 0.0455564993899316,
0.528105488047004, 0.892419044394046, 0.551435014465824, 0.456614735303447,
0.956833345349878, 0.453334156190977, 0.677570635452867, 0.572633401956409,
0.102924682665616, 0.899824970401824, 0.24608773435466, 0.0420595335308462,
0.327920719282702, 0.954503649147227), depth = c(0.889539316063747,
0.6928034061566, 0.640506813768297, 0.994269776623696, 0.655705799115822,
0.708530468167737, 0.544066024711356, 0.59414202044718, 0.28915973729454,
0.147113647311926, 0.963024232536554, 0.902299045119435, 0.690705278422683,
0.795467417687178, 0.0246136845089495, 0.477795971091837, 0.758459537522867,
0.216407935833558, 0.318181007634848, 0.231625785352662)), class = "data.frame", row.names = c(NA,
-20L))页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/70341256
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