使用dplyr获取方差为零的列名 [英] Get column names with zero variance using dplyr
问题描述
我正在尝试找到数据中方差为零的任何变量（即恒定连续变量）。我想出了如何使用lapply来做到这一点，但由于要遵循整洁的数据原理，因此我想使用dplyr。我可以使用dplyr创建一个仅包含方差的向量，但最后一步是找到不等于零的值并返回使我感到困惑的变量名。
I'm trying to find any variables in my data that have zero variance (i.e. constant continuous variables). I figured out how to do it with lapply but I would like to use dplyr as I'm trying to follow tidy data principles. I can create a vector of just the variances using dplyr but its the last step where I find the values not equal to zero and return the variable names that confusing me.
代码
Here's the code
library(PReMiuM)
library(tidyverse)
#> ── Attaching packages ───────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
#> ✔ ggplot2 2.2.1 ✔ purrr 0.2.4
#> ✔ tibble 1.4.2 ✔ dplyr 0.7.4
#> ✔ tidyr 0.7.2 ✔ stringr 1.2.0
#> ✔ readr 1.2.0 ✔ forcats 0.2.0
#> ── Conflicts ──────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag() masks stats::lag()
setwd("~/Stapleton_Lab/Projects/Premium/hybridAnalysis/")
# read in data from analysis script
df <- read_csv("./hybrid.csv")
#> Parsed with column specification:
#> cols(
#> .default = col_double(),
#> Exp = col_character(),
#> Pedi = col_character(),
#> Harvest = col_character()
#> )
#> See spec(...) for full column specifications.
# checking for missing variable
# df %>%
# select_if(function(x) any(is.na(x))) %>%
# summarise_all(funs(sum(is.na(.))))
# grab month for analysis
may <- df %>%
filter(Month==5)
june <- df %>%
filter(Month==6)
july <- df %>%
filter(Month==7)
aug <- df %>%
filter(Month==8)
sept <- df %>%
filter(Month==9)
oct <- df %>%
filter(Month==10)
# check for zero variance in continuous covariates
numericVars <- grep("Min|Max",names(june))
zero <- which(lapply(june[numericVars],var)==0,useNames = TRUE)
noVar <- june %>%
select(numericVars) %>%
summarise_all(var) %>%
filter_if(all, all_vars(. != 0))
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
#> Warning in .p(.tbl[[vars[[i]]]], ...): coercing argument of type 'double'
#> to logical
推荐答案
举一个可重复的例子，我想你是目标是在下面。请注意，正如Colin所指出的，我没有处理您选择带有字符变量的变量的问题。
With a reproducible example, I think what you are aiming for is below. Please note that as pointed out by Colin, I have not dealt with the issue of you selecting variables with a character variable. See his answer for details on that.
# reproducible data
mtcars2 <- mtcars
mtcars2$mpg <- mtcars2$qsec <- 7
library(dplyr)
mtcars2 %>%
summarise_all(var) %>%
select_if(function(.) . == 0) %>%
names()
# [1] "mpg" "qsec"
我个人认为这模糊了您在做什么。以下是使用 purrr 程序包（如果您希望保留在tidyverse中）的下列选项之一，我希望它带有良好的书面注释。
Personally, I think that obfuscates what you are doing. One of the following using the purrr package (if you wish to remain in the tidyverse) would be my preference, with a well written comment.
library(purrr)
# Return a character vector of variable names which have 0 variance
names(mtcars2)[which(map_dbl(mtcars2, var) == 0)]
names(mtcars2)[map_lgl(mtcars2, function(x) var(x) == 0)]
如果您想对其速度进行优化，请坚持使用基本R
If you'd like to optimize it for speed, stick with base R
# Return a character vector of variable names which have 0 variance
names(mtcars2)[vapply(mtcars2, function(x) var(x) == 0, logical(1))]
这篇关于使用dplyr获取方差为零的列名的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
