Reference code and image below: 
I have a dataframe that is grouped by company name that looks like so:
Company | tweet AMZN @115827 Thanks for your patience. AMZN @115826 I'm sorry for the wait. You'll receive an email as soon as possible. APPL @115818 Glad to check. APPL @115853 Happy to assist any way I can. DASH @116109 We have followed up via DM. DASH @116269 We've been in touch via DM! After subsetting the tweet field based on each word using the code below - I ended up creating a row for each word found per tweet. Example of new table.
CODE Supp_cleaned_tweets <- Customer_df %>% mutate(Cleaned_Tweet = str_remove_all(tweet, "\\s*@\\S+")) %>% select(Company, Cleaned_Tweet) %>% mutate(line = row_number()) %>% unnest_tokens(word, Cleaned_Tweet) %>% anti_join(stop_words) Company | word AMZN Thanks AMZN for AMZN your AMZN patience APPL Glad APPL to APPL check What I am having trouble is to create a graph that shows each company and their respective top 10 most common words found - in descending order - as each company will have different words. What I would like to do is a facet_wrap so it's all on one image but the y-axis is messing up.
Supp_cleaned_tweets %>% group_by(Company) %>% count(word, sort = TRUE) %>% top_n(10) %>% mutate(word = reorder(word, n)) %>% ggplot(aes(x = word, y = n, fill = Company)) + geom_col() + facet_wrap(~ Company) + xlab(NULL) + coord_flip() + labs(y = "Count", x = "Unique words", title = "Most frequent words found in the tweets", subtitle = "Stop words removed from the list") 1 Answer
UPDATE
Solved based on this code below - referenced from the help in comments link shared
Supp_cleaned_tweets %>% group_by(Company) %>% count(word, sort = TRUE) %>% top_n(10) %>% ungroup %>% mutate(word = reorder_within(word, n, Company)) %>% ggplot(aes(x = word, y = n, fill = author_id)) + geom_col(show.legend = FALSE) + facet_wrap(~ author_id, scales = "free_y") + coord_flip() + scale_x_reordered() + scale_y_continuous(expand = c(0,0)) + labs(y = "Count", x = "Unique words", title = "Most frequent words found in the tweets", subtitle = "Stop words removed from the list") 
