R-跨数据集的所有行应用函数(combinevar)
我有一个数据集,其中每一行都包含combinevar函数所需的数据(package=fishmethods;combinevar将来自两个分布的信息结合起来,得出组合方差)R-跨数据集的所有行应用函数(combinevar),r,apply,variance,R,Apply,Variance,我有一个数据集,其中每一行都包含combinevar函数所需的数据(package=fishmethods;combinevar将来自两个分布的信息结合起来,得出组合方差) xbar1=c(2,2,1,4,3) xbar2=c(0,0,0,0,0) var1=c(0,1,3,2,1) var2=c(0,0,0,0,0) n1=c(50,10,30,40,50) n2=c(3,4,50,32,20) df我们可以按行嵌套数据,然后映射每行的函数 library(tidyverse) library
xbar1=c(2,2,1,4,3)
xbar2=c(0,0,0,0,0)
var1=c(0,1,3,2,1)
var2=c(0,0,0,0,0)
n1=c(50,10,30,40,50)
n2=c(3,4,50,32,20)
df我们可以按行嵌套数据,然后映射每行的函数
library(tidyverse)
library(fishmethods)
df %>%
rownames_to_column("row") %>%
nest(-row) %>%
mutate(combined_var = map(data, ~combinevar(xbar = c(.x$xbar1, .x$xbar2),
s_squared = c(.x$var1, .x$var2),
n = c(.x$n1, .x$n2))[2])) %>%
unnest()
#> row combined_var xbar1 xbar2 var1 var2 n1 n2
#> 1 1 0.2177068 2 0 0 0 50 3
#> 2 2 1.5714286 2 0 1 0 10 4
#> 3 3 1.3386076 1 0 3 0 30 50
#> 4 4 5.1048513 4 0 2 0 40 32
#> 5 5 2.5734990 3 0 1 0 50 20
或者我们可以按行应用函数
df %>%
rowwise() %>%
mutate(combined_var = combinevar(xbar = c(xbar1, xbar2),
s_squared = c(var1, var2),
n = c(n1, n2))[2])
#> Source: local data frame [5 x 7]
#> Groups: <by row>
#>
#> # A tibble: 5 x 7
#> xbar1 xbar2 var1 var2 n1 n2 combined_var
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2 0 0 0 50 3 0.218
#> 2 2 0 1 0 10 4 1.57
#> 3 1 0 3 0 30 50 1.34
#> 4 4 0 2 0 40 32 5.10
#> 5 3 0 1 0 50 20 2.57
df%>%
行()
突变(combined_var=combinevar(xbar=c(xbar1,xbar2),
s_平方=c(var1,var2),
n=c(n1,n2))[2])
#>来源:本地数据帧[5 x 7]
#>小组:
#>
#>#A tibble:5 x 7
#>xbar1 xbar2 var1 var2 n1 n2组合型
#>
#> 1 2 0 0 0 50 3 0.218
#> 2 2 0 1 0 10 4 1.57
#> 3 1 0 3 0 30 50 1.34
#> 4 4 0 2 0 40 32 5.10
#> 5 3 0 1 0 50 20 2.57
由(v0.2.0)于2018-08-19创建。我们可以按行嵌套数据,然后映射每行的函数
library(tidyverse)
library(fishmethods)
df %>%
rownames_to_column("row") %>%
nest(-row) %>%
mutate(combined_var = map(data, ~combinevar(xbar = c(.x$xbar1, .x$xbar2),
s_squared = c(.x$var1, .x$var2),
n = c(.x$n1, .x$n2))[2])) %>%
unnest()
#> row combined_var xbar1 xbar2 var1 var2 n1 n2
#> 1 1 0.2177068 2 0 0 0 50 3
#> 2 2 1.5714286 2 0 1 0 10 4
#> 3 3 1.3386076 1 0 3 0 30 50
#> 4 4 5.1048513 4 0 2 0 40 32
#> 5 5 2.5734990 3 0 1 0 50 20
或者我们可以按行应用函数
df %>%
rowwise() %>%
mutate(combined_var = combinevar(xbar = c(xbar1, xbar2),
s_squared = c(var1, var2),
n = c(n1, n2))[2])
#> Source: local data frame [5 x 7]
#> Groups: <by row>
#>
#> # A tibble: 5 x 7
#> xbar1 xbar2 var1 var2 n1 n2 combined_var
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2 0 0 0 50 3 0.218
#> 2 2 0 1 0 10 4 1.57
#> 3 1 0 3 0 30 50 1.34
#> 4 4 0 2 0 40 32 5.10
#> 5 3 0 1 0 50 20 2.57
df%>%
行()
突变(combined_var=combinevar(xbar=c(xbar1,xbar2),
s_平方=c(var1,var2),
n=c(n1,n2))[2])
#>来源:本地数据帧[5 x 7]
#>小组:
#>
#>#A tibble:5 x 7
#>xbar1 xbar2 var1 var2 n1 n2组合型
#>
#> 1 2 0 0 0 50 3 0.218
#> 2 2 0 1 0 10 4 1.57
#> 3 1 0 3 0 30 50 1.34
#> 4 4 0 2 0 40 32 5.10
#> 5 3 0 1 0 50 20 2.57
由(v0.2.0)于2018-08-19创建。您可以使用“将函数应用到行”并正确指定函数读取行:
library(fishmethods)
my_function<- function(vec){
combined_var <- combinevar(xbar = c(vec[1], vec[2]), s_squared = c(vec[3], vec[4]), n = c(vec[5], vec[6]))
}
apply(df, 1, my_function) [2, ]
库(fishmethods)
my_函数您可以对行使用apply函数,并正确指定函数读取行:
library(fishmethods)
my_function<- function(vec){
combined_var <- combinevar(xbar = c(vec[1], vec[2]), s_squared = c(vec[3], vec[4]), n = c(vec[5], vec[6]))
}
apply(df, 1, my_function) [2, ]
库(fishmethods)
my_函数