Why does my code chunk render my plot correctly when run by itself but I get an 'object not found' error when I try to knit in R Markdown?

I am relatively new at R Markdown and am having trouble when trying to knit to create a report. The error I am getting is:

Error in ggplot(data = bio1530_sci1420_summary_stats.xlsx) :
object 'bio1530_sci1420_summary_stats.xlsx' not found
Calls: <Anonymous> ... withVisible -> eval_with_user_handlers -> eval -> eval -> ggplot
Execution halted

Here is my code thus far:

title: "NGRMarkdown"
author: "Rob McCandless"
date: "r Sys.Date()"
output: word_document

knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(ggrepel)
library(tidyverse)
library(here)
read_csv("bio1530_sci1420_summary_stats.xlsx")

#ScatterPlot of mean course grade v. mean normalized gain on 1420 and 1530 data with regression lines and error bars
ggplot(data=bio1530_sci1420_summary_stats.xlsx)+
  geom_errorbar(aes(x=Course_grade, y=Norm_gain, ymin=Norm_gain-CI, ymax=Norm_gain+CI), color="black", width=0.2, position=position_dodge2(10.0))+
  geom_point(mapping=aes(x=Course_grade, y=Norm_gain, shape=Course, color=Course),size=3)+
  geom_smooth(method=lm, se=FALSE, col='black', size=1, mapping=aes(x=Course_grade, y=Norm_gain, linetype=Course))+
  geom_label_repel(aes(Course_grade, y=Norm_gain, label = Alpha), box.padding = 0.3, point.padding = 0.7, segment.color = 'grey50')+  #added point labels A-J 
  ylab('Mean Normalized Gain (all instructor sections)')+
  xlab('Mean Course Grade (all instructor sections)')+
  scale_fill_discrete(labels=c("Bio 1530", "Sci 1420"))+
  labs(title="Normalized Gain v. Course Grade by Course & Instructor", subtitle="Mean and 95% CI of all sections per instructor (A-J)")+
  theme(plot.title=element_text(hjust=0.5))+
  theme(plot.subtitle=element_text(hjust=0.5))+
  annotate("text", x=73.0, y=0.09, label="R2 = 0.68, p = 0.044")+
  annotate("text", x=78.5, y=0.22, label="R2 = 0.46, p = 0.095")




And this is the plot that renders when I tell R to run this chunk only:

[Course grade v. normalized gain](https://i.stack.imgur.com/WO9S7.png)

So the code works and the dataframe the code refers to is valid, but it won't render when I try to knit in R Markdown.


I suspect it may have to do with the current and working directories not being the same, but I'm not certain of this and am not sure how to check this.  I have confirmed that my my working directory is:

getwd()
[1] "/Users/robmccandless/Library/Mobile Documents/com~apple~CloudDocs/R Projects/Normalized_Gain_Data"

and this is where the dataframe and RMD file are both located.  Can anyone give me some idea of what I am doing wrong?  Any assistance will be greatly appreciated.

</details>


# 答案1
**得分**: 0

错误提示表示您的数据集对象（即.xlsx文件）在您的本地环境中未找到。从上面的代码片段来看，数据集似乎只是读取而没有保存。一种选择是在您的Markdown中尝试：

```R
df <- read_csv("bio1530_sci1420_summary_stats.xlsx")

ggplot(data=df)+
  geom_errorbar(aes(x=Course_grade, y=Norm_gain, ymin=Norm_gain-CI, ymax=Norm_gain+CI), color="black", width=0.2, position=position_dodge2(10.0))+
  geom_point(mapping=aes(x=Course_grade, y=Norm_gain, shape=Course, color=Course),size=3)+
  geom_smooth(method=lm, se=FALSE, col='black', size=1, mapping=aes(x=Course_grade, y=Norm_gain, linetype=Course))+
  geom_label_repel(aes(Course_grade, y=Norm_gain, label = Alpha), box.padding = 0.3, point.padding = 0.7, segment.color = 'grey50')+  #added point labels A-J 
  ylab('Mean Normalized Gain (all instructor sections)')+
  xlab('Mean Course Grade (all instructor sections)')+
  scale_fill_discrete(labels=c("Bio 1530", "Sci 1420"))+
  labs(title="Normalized Gain v. Course Grade by Course & Instructor", subtitle="Mean and 95% CI of all sections per instructor (A-J)")+
  theme(plot.title=element_text(hjust=0.5))+
  theme(plot.subtitle=element_text(hjust=0.5)+
  annotate("text", x=73.0, y=0.09, label="R2 = 0.68, p = 0.044")+
  annotate("text", x=78.5, y=0.22, label="R2 = 0.46, p = 0.095")

请确保您的工作目录中包含名为"bio1530_sci1420_summary_stats.xlsx"的文件，或者根据文件的实际路径进行相应的更改。

df <- read_csv("bio1530_sci1420_summary_stats.xlsx")

ggplot(data=df)+
  geom_errorbar(aes(x=Course_grade, y=Norm_gain, ymin=Norm_gain-CI, ymax=Norm_gain+CI), color="black", width=0.2, position=position_dodge2(10.0))+
  geom_point(mapping=aes(x=Course_grade, y=Norm_gain, shape=Course, color=Course),size=3)+
  geom_smooth(method=lm, se=FALSE, col='black', size=1, mapping=aes(x=Course_grade, y=Norm_gain, linetype=Course))+
  geom_label_repel(aes(Course_grade, y=Norm_gain, label = Alpha), box.padding = 0.3, point.padding = 0.7, segment.color = 'grey50')+  #added point labels A-J 
  ylab('Mean Normalized Gain (all instructor sections)')+
  xlab('Mean Course Grade (all instructor sections)')+
  scale_fill_discrete(labels=c("Bio 1530", "Sci 1420"))+
  labs(title="Normalized Gain v. Course Grade by Course & Instructor", subtitle="Mean and 95% CI of all sections per instructor (A-J)")+
  theme(plot.title=element_text(hjust=0.5))+
  theme(plot.subtitle=element_text(hjust=0.5))+
  annotate("text", x=73.0, y=0.09, label="R2 = 0.68, p = 0.044")+
  annotate("text", x=78.5, y=0.22, label="R2 = 0.46, p = 0.095")