I want to use count with group_by but it's not giving me the right answer

I have this dataset: chocolate_bars_dataset
I want to know how many bars were reviewd for each country(bean_origin).
I tried this code:

bars_reviewd <- chocolate_bars %>%


But it's not giving me the right answer. Could someone please help me ? I would really appreciate it.

Can you show us some of the data in chocolate_bars.

A handy way to supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need.

df <- read.delim("C:/Users/Jerry/Desktop/R_files/chocolate.txt", header = TRUE, sep = "\t")
bars_reviewed <- df %>%
group_by(Country.of.Bean.Origin) %>%

1 Australia 2
2 Bali 1
3 Belize 56
4 Blend 92
5 Bolivia 47
6 Brazil 60

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Try only using count()

bars_reviewd <- chocolate_bars %>%
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Agreed. Omit the argument to count.

Or when you look at the man page you see you can omit the group_by and name the grouping column in the count() the way OP did

I had been treating count() as a shorthand for summarise(n = n()) with optional sort.
Have only just realised its advertised function includes the group_by and none of the examples include a group_by beforehand. Count observations by group — count • dplyr

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Here's two solutions using data.table and dplyr.


# data.table

dt_1 <- fread("~/R/20220729_chocolate.csv", header = TRUE)

dt_2 <- dt_1[, .(count = .N), .(`Country of Bean Origin`)] |>

   Country of Bean Origin count
1:              Venezuela   254
2:                   Peru   248
3:     Dominican Republic   234
4:                Ecuador   223
5:             Madagascar   184
6:                  Blend   156


# dplyr

df_1 <- read.csv("~/R/20220729_chocolate.csv", header = TRUE)

df_2 <- df_1 |>
  group_by(Country.of.Bean.Origin) |>
  summarise(count = n()) |>

# A tibble: 6 x 2
  Country.of.Bean.Origin count
  <chr>                  <int>
1 Venezuela                254
2 Peru                     248
3 Dominican Republic       234
4 Ecuador                  223
5 Madagascar               184
6 Blend                    156
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This answer should be the best answer. It shows the simplest way of getting the result.
And this is the documentation of count: "count() lets you quickly count the unique values of one or more variables: df %>% count(a, b) is roughly equivalent to df %>% group_by(a, b) %>% summarise(n = n())". I wonder why the author of the question didn't even take a look on it (?)

How to download this data from this website - first post ?

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