Figure Error in if (grepl("docx", opts_knit$get("rmarkdown.pandoc.to"))) {: argument is of length zero

[ahbon123]

Hello, I get an error: Figure Error in if (grepl("docx", opts_knit$get("rmarkdown.pandoc.to"))) {: argument is of length zero, while running analysis part, could you help?

[KWigg4]

I did too - did you figure it out, abhon123?

[KWigg4]

UPDATE: I got the error when I ran the code in rmd, but when I knitted it, it worked fine! Who knows?!

[pvsundar]

I too get this message:


Figure Error in if (grepl("docx", opts_knit$get("rmarkdown.pandoc.to"))) { :
argument is of length zero

`# Analysis

# this chunk will programmatically generates Markdown code (results='asis')
# split the data by specie to simulate different attributes to analyze, it is here 3 here but it could be any number.
data <- split(iris, iris$Species)
uniqueSpecies <- levels(iris$Species)
# for loop
for(i in 1:length(uniqueSpecies)){
  
  dataSubset <- data[[uniqueSpecies[i]]]
    
  # print the heading
  cat("\n##", uniqueSpecies[i], "\n")
  
  # print an empty line
  cat("\n  <br>  \n")
  
  # print some text
  cat("Figure ")
  # reference the figure below (note the use of knit_print_run function in 'asis' chunks)
  knit_print_run(run_reference(paste0("pData", uniqueSpecies[i])))
  cat(" shows the relation between Sepal width and length.")
  
  # plot the data 
  pData <- ggplot(aes(x=Sepal.Length, y=Sepal.Width), data=dataSubset) + 
    geom_point() + geom_smooth(method='lm', se=F) + labs(title=uniqueSpecies[i])
  
  # output the plot (note the use of the print function in 'asis' chunks)
  print(pData)
  
  cat("\n") # sometimes you need to add this to make things work
  
  # Add the figure numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  fig_num <- run_autonum(seq_id = "Figure", pre_label = "Figure ", bkm = paste0("pData", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Scatter plot of Sepal Width vs Sepal Length for ", uniqueSpecies[i], ". Blue line is a linear regression."),
              style = "caption", autonum = fig_num))
  
  
  # print some text
  cat("A linear regression was performed using Sepal.Length as the response and Sepal.Width as the explanatory variable. Table ")
  knit_print_run(run_reference(paste0("tabRegression", uniqueSpecies[i])))
  cat(" shows the parameters estimates and 95% Confidence intervals.")
  
  cat("\n") # sometimes you need to add this to make things work
  
  # do a regression generate the fit summary table
  regression <- lm(Sepal.Length ~ Sepal.Width, data=dataSubset, digits = 4)
  tabRegression <- tidy(regression)
  tabRegression <- cbind(tabRegression, confint(regression, level=0.95))
  
  # Add the table numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  tab_num <- run_autonum(seq_id = "Table", pre_label = "Table ", bkm = paste0("tabRegression", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Parameters estimates of the fit for ", uniqueSpecies[i]),
              style = "caption", autonum = tab_num))
  
  
  
  # output the summary table (note the use of knit_print and cat functions in 'asis' chunks)
  tabRegression %>% flextable() %>% 
     colformat_double(digits = 4)%>% knit_print() %>% cat()
  
  cat('\n')
}
# Add a page break
run_pagebreak()

[pvsundar]

I too get this message: Figure Error in if (grepl("docx", opts_knit$get("rmarkdown.pandoc.to"))) { : argument is of length zero

`# Analysis

# this chunk will programmatically generates Markdown code (results='asis')
# split the data by specie to simulate different attributes to analyze, it is here 3 here but it could be any number.
data <- split(iris, iris$Species)
uniqueSpecies <- levels(iris$Species)
# for loop
for(i in 1:length(uniqueSpecies)){
  
  dataSubset <- data[[uniqueSpecies[i]]]
    
  # print the heading
  cat("\n##", uniqueSpecies[i], "\n")
  
  # print an empty line
  cat("\n  <br>  \n")
  
  # print some text
  cat("Figure ")
  # reference the figure below (note the use of knit_print_run function in 'asis' chunks)
  knit_print_run(run_reference(paste0("pData", uniqueSpecies[i])))
  cat(" shows the relation between Sepal width and length.")
  
  # plot the data 
  pData <- ggplot(aes(x=Sepal.Length, y=Sepal.Width), data=dataSubset) + 
    geom_point() + geom_smooth(method='lm', se=F) + labs(title=uniqueSpecies[i])
  
  # output the plot (note the use of the print function in 'asis' chunks)
  print(pData)
  
  cat("\n") # sometimes you need to add this to make things work
  
  # Add the figure numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  fig_num <- run_autonum(seq_id = "Figure", pre_label = "Figure ", bkm = paste0("pData", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Scatter plot of Sepal Width vs Sepal Length for ", uniqueSpecies[i], ". Blue line is a linear regression."),
              style = "caption", autonum = fig_num))
  
  
  # print some text
  cat("A linear regression was performed using Sepal.Length as the response and Sepal.Width as the explanatory variable. Table ")
  knit_print_run(run_reference(paste0("tabRegression", uniqueSpecies[i])))
  cat(" shows the parameters estimates and 95% Confidence intervals.")
  
  cat("\n") # sometimes you need to add this to make things work
  
  # do a regression generate the fit summary table
  regression <- lm(Sepal.Length ~ Sepal.Width, data=dataSubset, digits = 4)
  tabRegression <- tidy(regression)
  tabRegression <- cbind(tabRegression, confint(regression, level=0.95))
  
  # Add the table numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  tab_num <- run_autonum(seq_id = "Table", pre_label = "Table ", bkm = paste0("tabRegression", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Parameters estimates of the fit for ", uniqueSpecies[i]),
              style = "caption", autonum = tab_num))
  
  
  
  # output the summary table (note the use of knit_print and cat functions in 'asis' chunks)
  tabRegression %>% flextable() %>% 
     colformat_double(digits = 4)%>% knit_print() %>% cat()
  
  cat('\n')
}
# Add a page break
run_pagebreak()

This is test of an excellent example by : Thomas de Marchin - Awesome Rmarkdown Word report with programmatically inserted headings, outputs and cross-references

Very Intriguingly, I can get it to work in a local drive where I installed all the libraries earlier today.
When I copy the .RMD file to another location and try to get it to run there i got the above error.
So, I opened the .Rmd file in the same PROJECT and I could get it to work only if I copied one of the outputs: grateful-refs.
Anyway, it may be a useful template to have for others that also uses the GRATEFUL package to cite sources used.

CODE:
--- title: "Thomas de Marchin - Awesome Rmarkdown Word report with programmatically inserted headings, outputs and cross-references" author: "P.V. (SUNDAR) Balakrishnan" date: "r Sys.time()`"
output:
html_document:
toc: yes
toc_depth: 2
fig_caption: yes
number_sections: yes
officedown::rdocx_document:
mapstyles:
Normal: First Paragraph
bibliography: grateful-refs.bib

# Let's setup a few things.
rm(list=ls())
library(knitr)
library(officedown)
library(officer)
library(ggplot2)
library(tidyverse)
library(broom)
library(flextable)

# set chunks defaults
# set flextable defaults

knitr::opts_chunk$set(
	echo = TRUE,
	message = FALSE,
	warning = FALSE
)
  set_flextable_defaults(
  font.family = "Calibri", font.size = 9, 
  theme_fun = "theme_vanilla",
  big.mark="", table.layout="autofit")
  
# formatting properties for specific paragraphs
centeredP <- fp_par(text.align = "center")

ft <- fp_text(shading.color='#EFEFEF', bold = TRUE)
fp <- fp_par(
  text.align = "center", 
  padding.bottom = 20, padding.top = 120, 
  border.bottom = fp_border())

This document presents most of the features of the package r ftext("officedown", ft). r fp

\newpage

Introduction

The aim of this document is to introduce a way to generate word reports from R using Rmarkdown with programmatically inserted headings, outputs and Word cross-references.

See https://towardsdatascience.com/awesome-r-markdown-word-report-with-programmatically-inserted-headings-outputs-and-19ad0de29a22 to understand the context of this example.

# this chunk is a normal chunk compared to the next one
# create the bookmark for the summary table
tab_num <- run_autonum(seq_id = "Table", pre_label = "Table ", bkm = "summaryTable")
# add the caption
block_caption(label= "Summary table for the iris dataset",
              style = "caption", autonum = tab_num)
# create the summary table and output it with flextable()
summaryData <- iris %>% gather(value="value", key="Attribute", -Species) %>% group_by(Attribute, Species) %>% summarise(n=n(), mean=mean(value), sd=sd(value), min=min(value), max=max(value)) 
summaryData %>% flextable() %>% merge_v(j = "Attribute") %>% colformat_double(j=c("mean", "sd"), digits = 2)

\newpage

Analysis

# this chunk will programmatically generates Markdown code (results='asis')
# split the data by specie to simulate different attributes to analyze, it is here 3 here but it could be any number.
data <- split(iris, iris$Species)
uniqueSpecies <- levels(iris$Species)
# for loop
for(i in 1:length(uniqueSpecies)){
  
  dataSubset <- data[[uniqueSpecies[i]]]
    
  # print the heading
  cat("\n##", uniqueSpecies[i], "\n")
  
  # print an empty line
  cat("\n  <br>  \n")
  
  # print some text
  cat("Figure ")
  # reference the figure below (note the use of knit_print_run function in 'asis' chunks)
  knit_print_run(run_reference(paste0("pData", uniqueSpecies[i])))
  cat(" shows the relation between Sepal width and length.")
  
  # plot the data 
  pData <- ggplot(aes(x=Sepal.Length, y=Sepal.Width), data=dataSubset) + 
    geom_point() + geom_smooth(method='lm', se=F) + labs(title=uniqueSpecies[i])
  
  # output the plot (note the use of the print function in 'asis' chunks)
  print(pData)
  
  cat("\n") # sometimes you need to add this to make things work
  
  # Add the figure numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  fig_num <- run_autonum(seq_id = "Figure", pre_label = "Figure ", bkm = paste0("pData", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Scatter plot of Sepal Width vs Sepal Length for ", uniqueSpecies[i], ". Blue line is a linear regression."),
              style = "caption", autonum = fig_num))
  
  
  # print some text
  cat("A linear regression was performed using Sepal.Length as the response and Sepal.Width as the explanatory variable. Table ")
  knit_print_run(run_reference(paste0("tabRegression", uniqueSpecies[i])))
  cat(" shows the parameters estimates and 95% Confidence intervals.")
  
  cat("\n") # sometimes you need to add this to make things work
  
  # do a regression generate the fit summary table
  regression <- lm(Sepal.Length ~ Sepal.Width, data=dataSubset, digits = 4)
  tabRegression <- tidy(regression)
  tabRegression <- cbind(tabRegression, confint(regression, level=0.95))
  
  # Add the table numbering and caption (note the use of the knit_print_block function in 'asis' chunks)
  tab_num <- run_autonum(seq_id = "Table", pre_label = "Table ", bkm = paste0("tabRegression", uniqueSpecies[i]))
  knit_print_block(block_caption(paste0("Parameters estimates of the fit for ", uniqueSpecies[i]),
              style = "caption", autonum = tab_num))
  
  
  
  # output the summary table (note the use of knit_print and cat functions in 'asis' chunks)
  tabRegression %>% flextable() %>% 
     colformat_double(digits = 4)%>% knit_print() %>% cat()
  
  cat('\n')
}
# Add a page break
run_pagebreak()

Conclusion

\newpage

REFERENCES

library(report)
renv::snapshot()

r <- report_text(sessionInfo())
summary(r)  
     # # Add a page break
     run_pagebreak()

             ###citations
library(grateful)
#nocite_references(cite_packages(output = "citekeys", out.dir = "."))
# cite_packages(output = "file",
#               cite.tidyverse = TRUE,
#               include.RStudio = TRUE,
#               out.file = "grateful-references", 
#               out.dir = ".")
# # Add a page break
# run_pagebreak()

pkgs <- cite_packages(output = "table", out.dir = ".")

knitr::kable(pkgs)

`