根据条件 R 删除行

Question

I have a data as like this

Name  Group  Heath  BP  PM
QW    DE23    20    60  10
We    Fw34    0.5   42  2.5
Sd    Kl78    0.4   0.1 0.5
Op    Ss14    43    45  96

I need to remove all the rows if that values are less than 1.8

I used following command

 data[colSums(data)>=1.8]
 data[,colSums(data)>=1.8, drop=FALSE]
subset(data, select=colSums(data) >=1.8)

But I got error as like this "Error in colSums(data): 'x' must be numeric"

Expected out put

Name  Group  Heath  BP  PM
QW    DE23    20    60  10
We    Fw34    0.5   42  2.5
Op    Ss14    43    45  96

Answer 1

You can use to select rows where their sum is >=1.8 :

data[rowSums(data[-1:-2])>=1.8,]
#  Name Group Heath BP   PM
#1   QW  DE23  20.0 60 10.0
#2   We  Fw34   0.5 42  2.5
#4   Op  Ss14  43.0 45 96.0

or where any element in the row is >=1.8 :

data[rowSums(data[-1:-2]>=1.8)>0,]
#  Name Group Heath BP   PM
#1   QW  DE23  20.0 60 10.0
#2   We  Fw34   0.5 42  2.5
#4   Op  Ss14  43.0 45 96.0

data[-1:-2] select the numeric columns.

Answer 2

Here is a tidyverse solution:

library(tidyverse)


df <- tibble::tribble(
    ~Name,~Group,~Heath,~BP,~PM,
   "QW",    "DE23",20,60,10,
  "We",    "Fw34",0.5,42,2.5,
  "Sd",    "Kl78",0.4,0.1,0.5,
   "Op",    "Ss14",43,45,96
  )


df %>% 
  filter_if(is.numeric,any_vars(.>=1.8))
#> # A tibble: 3 x 5
#>   Name  Group Heath    BP    PM
#>   <chr> <chr> <dbl> <dbl> <dbl>
#> 1 QW    DE23   20      60  10  
#> 2 We    Fw34    0.5    42   2.5
#> 3 Op    Ss14   43      45  96

^{Created on 2020-12-07 by the reprex package (v0.3.0)}

Answer 3

The easiest way is to use the filter() function from dplyr package in combination with select to automatically detect numeric columns:

library(dplyr)

df <- data.frame(Name = c("QW", "We", "Sd", "Op"),
                 Group = c("DE23", "Fw34", "Kl78", "Ss14"),
                 Heath = c(20, 0.5, 0.4, 43),
                 BP = c(60, 42, 0.1, 45),
                 PM = c(10, 2.5, 0.5, 96))

df %>% filter(rowSums(select_if(., is.numeric)) >= 1.8)

  Name Group Heath BP   PM
1   QW  DE23  20.0 60 10.0
2   We  Fw34   0.5 42  2.5
3   Op  Ss14  43.0 45 96.0

Answer 4

An option with Reduce from base R

df[Reduce(`|`, lapply(df[-(1:2)], `>=`, 1.8)),]
#   Name Group Heath BP   PM
#1   QW  DE23  20.0 60 10.0
#2   We  Fw34   0.5 42  2.5
#4   Op  Ss14  43.0 45 96.0