基于多列的NA过滤数据帧 [英] filtering data frame based on NA on multiple columns

问题描述

我有以下数据框，将其称为 df ，并具有以下观察结果：

I have the following data frame lets call it df, with the following observations:

id   type   company
1    NA      NA
2    NA      ADM
3    North   Alex
4    South   NA
NA   North   BDA
6    NA      CA

我只想保留类型和公司列中不包含NA的记录。

I want to retain only the records which do not have NA in column "type" and "company".

id   type   company
3    North   Alex
NA   North   BDA

我尝试过：

 df_non_na <- df[!is.na(df$company) || !is.na(df$type), ]

但这是行不通的。

预先感谢

推荐答案

我们可以获取以下内容的逻辑索引这两个列都使用& 并对行进行子集。

We can get the logical index for both columns, use & and subset the rows.

df1[!is.na(df1$type) & !is.na(df1$company),]
# id  type company
#3  3 North    Alex
#5 NA North     BDA

或在逻辑矩阵上使用 rowSums （ is.na（df1 [- 1]））子集。

Or use rowSums on the logical matrix (is.na(df1[-1])) to subset.

df1[!rowSums(is.na(df1[-1])),]

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