本文介绍了基于整行,在R中使用dplyr / magrittr过滤行的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
一个可以使用 filter 使用dplyr过滤行,但条件通常基于每行的特定列,例如
One is able to filter rows with dplyr with filter, but the condition is usually based on specific columns per row such as
d <- data.frame(x=c(1,2,NA),y=c(3,NA,NA),z=c(NA,4,5)) d %>% filter(!is.na(y))我想通过NA的数量是否大于50%来过滤这个行,例如
I want to filter the row by whether the number of NA is greater than 50%, such as
d %>% filter(mean(is.na(EACHROW)) < 0.5 )推荐答案
您可以使用 rowSums 为了那个原因。提供的数据的示例:
You could use rowSums for that. An example with the provided data:
> d x y z 1 1 3 NA 2 2 NA 4 3 NA NA 5 d %>% filter(rowSums(is.na(.))/ncol(.) < 0.5) # or: d %>% filter(rowMeans(is.na(.)) < 0.5)其中:
x y z 1 1 3 NA 2 2 NA 4正如你可以看到第3行从数据中删除。
As you can see row 3 is removed from the data.
在基数R中,您可以执行以下操作:
In base R, you could just do:
d[rowMeans(is.na(d)) < 0.5,]获得相同的结果。
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基于整行,在R中使用dplyr / magrittr过滤行
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