使用线性模型捕获NAs [英] catch NAs using linear model with dplyr

问题描述

这里是一个例外的数据框架

here's an exmaple data frame

library(dplyr)
df <- data.frame(id=c(1,1,1,2,2,2),
   v2=factor(c("a","c","c","a","b","d")),
   v3=c(1,NA,NA,6,7,9),
   v4=c(5:10))

请注意， v3 包含NAs，所以当我尝试为每个 id ，我收到一个错误：

Note that v3 contains NAs, so when I try to fit a linear model for each id, I get an error:

slope <- df %>% filter(v2=="c") %>% 
  group_by(id) %>% 
  do(fit = lm(v3 ~ v4, .)) %>%
  summarise(slope = coef(fit)[2])

Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...)   : 
  0 (non-NA) cases

如果只有NAs，我如何捕获此错误并将其替换为默认值

How can I catch this error and replace it with a default value if only NAs exist.

请注意，也可能发生 v4 有NAs，如果v3 = c（1，NA ）和
v4 = c（NA，2）它也不能构建线性模型。

Note that it could also happen that v4 has NAs, and if v3=c(1,NA) and v4=c(NA,2) it could not build a linear model as well.

例如，如果 df 不包含任何c然后我可以轻松地这样做

For example, if df does not contain any "c" then I can do this easily with

if(nrow(slope) == 0) slope <- 0

因为这个斜率是一个空数据框。

because then slope is an empty data frame.

推荐答案

我们可以在 do 中使用 if / else 检查 NA 元素。如果全部元素在'v3'或（ | NA $ c>）'v4'，它应该返回斜率为NA或 else 执行 lm 并获得斜率价值。

We could use an if/else condition within do to check the NA elements. If all the elements are NA in either 'v3' or (|) 'v4', it should return the slope as NA or else do the lm and get the slope value.

df %>% 
  filter(v2=='c') %>%
  group_by(id) %>%
  do({if(all(is.na(.$v3))|all(is.na(.$v4))) 
              data.frame(slope=NA) 
             else data.frame(slope=coef(lm(v3~v4, .))[2])}) %>%
  slice(1L) %>% 
  ungroup() %>%
  select(-id)

data

data

df <- data.frame(id=c(1,1,1,2,2,2, 3, 3, 3,3, 3, 4, 4),
 v2=factor(c("a","c","c","a","b","d", "c", "c", "a", "c", "c", "c", "c")),
 v3=c(1,NA,NA,6,7,9, NA, 1, NA, 5,8, NA, 5 ),
 v4=c(5:17))

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