Error in object[seq_len(ile)] : object of type 'symbol' is not subsettable

Question

I am trying to convert an rmd file to pdf using render statement.

render("MiningReport.Rmd", "pdf_document",output_dir = "C:/ProjectSocial/Reports/Twitter/Maybelline")

I am getting an error as below

Quitting from lines 109-113 (MiningReport.Rmd) 
Error in object[seq_len(ile)] : 
  object of type 'symbol' is not subsettable

This looks very strange to me because when I knit the Rmd file then is no such error and the pdf report is generated successfully and when I try to do the same using render statement it gives error. Can anyone please explain what's going on ? Below is the code chunk where the error creeps in

```{r assoc ,echo=F,message=FALSE}
library(tm)
findAssocs(myTdm,df$term[1:10],0.5)
```

When I remove the above chunk then the same error occurs for the next chunk of code. Below is my Rmd file. I am reading in tweets stored in files present in the directory specified.

```{r computedate,echo = FALSE}
date1 <-format(Sys.Date() - 7,"%B %d")
date2 <-format(Sys.Date() - 1,"%B %d, %Y")

```

# This report has been created on twitter data from `r date1` to `r date2`.
# Analysis of Tweets
## Below we can see the most frequent words.

```{r frequent,echo=FALSE,message=FALSE,warning=FALSE,cache=TRUE}

setwd("C:/ProjectSocial/Data/TwitterData/Maybelline")

library(devtools)
library(twitteR)
library(tm)
library(ggplot2)
library(graph)
library(Rgraphviz)
library(wordcloud)
library(topicmodels)
library(data.table)
library(fpc)
library(igraph)
library(xlsx)
library(stringr)

tweets.df<-data.frame(text=character(),favorited=character(),favoriteCount=numeric(),replyToSN=character(),
                created=as.POSIXct(character()),truncated=character(),replyToSID=character(),id=character(),replyToUID=character(),statusSource=character(),screenName=character(),retweetCount=numeric(),
isRetweet=character(),retweeted=character(),longitude=character(),latitude=character(),stringsAsFactors =F)
i<-1
while(i<=7){
  since<-Sys.Date()-i
  file<-read.xlsx2(file=paste("Maybelline",since,".xlsx",sep=""), 1,colClasses = c(rep("character",2),
  "numeric","character","POSIXct",rep("character",6),"numeric",rep("character",4)),   stringsAsFactors=F)

  tweets.df<-rbind(tweets.df,file)
  i<-i+1
}

j<-1
HashTagsList<-c()
HashTags<-str_extract_all(tweets.df$text,"#\\S+")
HashTags<-HashTags[!HashTags %in% c("character(0)")]

while (j<=length(HashTags)){

  HashTagsList<-c(HashTagsList,HashTags[[j]])
  j<-j+1
}
HashTagsList<- gsub("#", "", HashTagsList) 
HashTagsList<-unique(HashTagsList)
HashTagsList<-gsub("[^[:alnum:] ]", "", HashTagsList)

k<-1
HandleTagsList<-c()
HandleTags<-str_extract_all(tweets.df$text,"@\\S+")
HandleTags<-HandleTags[!HandleTags %in% c("character(0)")]
while (k<=length(HandleTags)){

  HandleTagsList<-c(HandleTagsList,HandleTags[[k]])
  k<-k+1
}

HandleTagsList<- gsub("@", "", HandleTagsList) 
HandleTagsList<-unique(HandleTagsList)
HandleTagsList<-gsub("[^[:alnum:] ]", "", HandleTagsList)

tweets.df$text<-gsub("#\\S+", "", tweets.df$text)
tweets.df$text<-gsub("@\\S+", "", tweets.df$text)

Tweets.df<-subset(tweets.df,isRetweet=="FALSE")
Tweets.df$text<-gsub("[^[:alpha:] ]", " ", Tweets.df$text)
Tweets.df$text<-tolower(Tweets.df$text)

myCorpus <-Corpus(VectorSource(Tweets.df$text))
myStopwords<-c(stopwords("english"),"maybelline","https","like","bring","make","thought","please","maybe",
               "know","just","want","wearing","really","last","better","best","first")
myCorpus<-tm_map(myCorpus,removeWords,myStopwords)
myCorpus<-tm_map(myCorpus,removeWords,HashTagsList)
myCorpus<-tm_map(myCorpus,removeWords,HandleTagsList)

myCorpus <- tm_map(myCorpus, PlainTextDocument)
myTdm<-TermDocumentMatrix(myCorpus,control=list(wordLengths=c(4,13)))
freq.Terms<- findFreqTerms(myTdm,lowfreq=20)
termFrequency <- rowSums(as.matrix(myTdm))
termFrequency <- subset(termFrequency, termFrequency>=20)
df <- data.frame(term=names(termFrequency), freq=termFrequency,stringsAsFactors = F)
df <- df[order(-df$freq),] 
rownames(df) <- NULL
print(head(df,50), row.names = FALSE)
df<-head(df,40)
ggplot(df,aes(x=term,y=freq)) + geom_bar(stat="identity") + xlab("Terms") +ylab("Count") +coord_flip()

```

## Below we can find all the words which are associated with the top 10 most frequent words and having correlation > 0.5.

```{r assoc ,echo=F,message=FALSE}

library(tm)
findAssocs(myTdm,df$term[1:10],0.5)

```

Any help appreciated Thanks

Answer 1

The error was coming because I used echo=F instead of echo=FALSE. F or T are considered as symbols and hence it creates issue. Here is why F (or T) is a symbol (see ?is.symbol to know what a symbol is):

> str(alist(warning = F)) 
List of 1 $ warning: symbol F > str(alist(warning = FALSE)) List of 1 $ warning: logi FALSE