dplyr中多列的平均值得到错误“必须解析为整数列位置，而不是列表”。 [英] Average of Multiple columns in dplyr getting error "must resolve to integer column positions, not a list"

问题描述

 gene   HSC_7256.bam HSC_6792.bam HSC_7653.bam   HSC_5852

我的数据框看起来像这样，我可以用正常的方式做到这一点，例如取出列使另一个数据帧平均化，但是我想在dplyr中做到这一点，我很难过，我不确定是什么问题

My data frame looks like this i can do that in a normal way such as take out the columns make another data frame average it ,but i want to do that in dplyr and im having a hard time I not sure what is the problem

我正在做类似的事情

HSC<- EPIGENETIC_FACTOR_SEQMONK %>%
    select(EPIGENETIC_FACTOR_SEQMONK,gene)

我收到此错误

错误： EPIGENETIC_FACTOR_SEQMONK 必须解析为整数列位置，而不是列表

Error: EPIGENETIC_FACTOR_SEQMONK must resolve to integer column positions, not a list

所以我必须这样做，取出所有HSC样本的平均值

So i have to do this take out all the HSC sample average them

有人建议我是什么

推荐答案

％>％函数将其左侧的所有内容拉到跟随功能。如果您的数据框是 EPIGENETIC_FACTOR_SEQMONK ，则这两个语句是等效的：

The %>% function pulls whatever is to the left of it into the first position of the following function. If your data frame is EPIGENETIC_FACTOR_SEQMONK, then these two statements are equivalent:

HSC <- EPIGENETIC_FACTOR_SEQMONK %>%
   select(gene)

HSC <- select(EPIGENETIC_FACTOR_SEQMONK, gene)

首先，我们将 EPIGENETIC_FACTOR_SEQMONK 传递到 select 使用％>％，通常在 dplyr 链中用作 dplyr 函数是一个数据框。

In the first, we are passing EPIGENETIC_FACTOR_SEQMONK into select using %>%, which is generally used in dplyr chains as the first argument in dplyr functions is a data frame.

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