错误：必须使用有效的下标向量重命名列答案

【问题标题】：Error: must rename columns with a valid subscript vector错误：必须使用有效的下标向量重命名列
【发布时间】：2021-08-02 19:09:00
【问题描述】：

我只是想导入一个 kaggle 数据集来研究 R，这简直是一场噩梦。

我正在尝试重命名数据框中的列，但我不断收到错误。

library(tidyverse)
library(dplyr)
library(ggplot2)
library(tibble)
library(janitor)
food_advs<- read.csv("CAERS_ASCII_2004_2017Q2.csv")
food_df <- data.frame(food_advs)
food_df %>% rename(food_df, Product = PRI_Reported.Brand.Product.Name, Industry = PRI_FDA.Industry.Name, Person_age = CI_Age.at.Adverse.Event, Gender = CI_Gender, Outcomes = AEC_One.Row.Outcomes, Symptoms = SYM_One.Row.Coded.Symptoms)



> food_df %>% rename(food_df, "Product" = "PRI_Reported.Brand.Product.Name", "Industry" = "PRI_FDA.Industry.Name", "Person_age" = "CI_Age.at.Adverse.Event", "Gender" = "CI_Gender", "Outcomes" = "AEC_One.Row.Outcomes", "Symptoms" = "SYM_One.Row.Coded.Symptoms")
Error: Must rename columns with a valid subscript vector.
x Subscript has the wrong type `data.frame<
  RA_Report..                    : integer
  RA_CAERS.Created.Date          : character
  AEC_Event.Start.Date           : character
  PRI_Product.Role               : character
  PRI_Reported.Brand.Product.Name: character
  PRI_FDA.Industry.Code          : integer
  PRI_FDA.Industry.Name          : character
  CI_Age.at.Adverse.Event        : integer
  CI_Age.Unit                    : character
  CI_Gender                      : character
  AEC_One.Row.Outcomes           : character
  SYM_One.Row.Coded.Symptoms     : character
>`.
i It must be numeric or character.
Run `rlang::last_error()` to see where the error occurred.

【问题讨论】：

%>% 的 lhs 中已经有了数据，即food_df %>% rename(Product = ...

标签： r dplyr

【解决方案1】：

试试下面的，

food_df %>% 
    rename(Product = PRI_Reported.Brand.Product.Name,
           Industry = PRI_FDA.Industry.Name, 
           Person_age = CI_Age.at.Adverse.Event,
           Gender = CI_Gender,
           Outcomes = AEC_One.Row.Outcomes,
           Symptoms = SYM_One.Row.Coded.Symptoms
    )

你的错误在于你使用了%>%；当您在调用之前已经拥有data %>% 时，使用rename(data, ...) 非常丰富。

【讨论】：