why my code is wrong summarise () and mean()

Your bar chart reveals the locations that produce the highest rated chocolate bars. To get a better idea of the specific rating for each location, you’d like to highlight each bar.

Assume that you are working with the code chunk:

ggplot(data = best_trimmed_flavors_df) +

geom_bar(mapping = aes(x = Company.Location))

Add a code chunk to the second line of code to map the aesthetic color to the variable Rating**.**

NOTE: the three dots (...) indicate where to add the code chunk.

my code :-geom_bar(mapping = aes(x = Company.Location, color = Company.Location))

According to your bar chart, which two company locations produce the highest rated chocolate bars?

Scotland and France

Amsterdam and U.S.A.

Canada and France

Canada and U.S.A.


Umm.. Are you sure these are the instructions? I find it weird that your professor asked you to map color, rather than fill. and I would suspect that the y axis should be mapped to the mean rating for each location, not the color..

Does this make sense to you?

best_trimmed_flavors_df <- tibble(
  Company.Location = sample(state.abb[1:5],20,TRUE),
  rating = sample(1:5,20,TRUE)

best_trimmed_flavors_df %>% 
  summarise(rating = mean(rating), .by = Company.Location) %>% 
ggplot()+geom_bar(aes(x = fct_reorder(Company.Location,-rating),
                      y = rating,
                      fill = Company.Location),
                  stat = "identity")

I changed a little bit the code your professor asked.

The fct_reorder() simply makes sure that the X axis categories are sorted by their value in y, you can remove it and see what happens.
stat = 'identity' is instead of using geom_col which i actualy prefer.
.by = in summarise is a new thing R guys are experimenting and I think its great. Usualy you would have to have a group_by before, and then you'd have grouped data. this is explicit and simple

1 Like

Thank you so much for the detailed explanation.

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