How to group rows with duplicate name in R? - r

Question

I am quite new to R and struggling with subsetting datasets.
This is where the dataset came from and how I clean it.
board_game_original<- read.csv("https://raw.githubusercontent.com/bryandmartin/STAT302/master/docs/Projects/project1_bgdataviz/board_game_raw.csv")
#tidy up the column of mechanic and category with cSplit function
library(splitstackshape)
mechanic <- board_game$mechanic
board_game_tidy <- cSplit(board_game,splitCols=c("mechanic","category"), sep = ",", direction = "long")
here's my code trying to extract two columns: category, and average complexities.
summary_category <- summary(board_game_tidy$category)
top_5_category <- summary_category[1:5]
complexity_top_5_category <- board_game_tidy %>%
group_by(category) %>%
select(average_complexity) %>%
filter(category == c("Abstract Strategy Action / Dexterity", "Adventure", "Age of Reason","American Civil War "))
complexity_top_5_category
My final intent: create a data frame with only 2 columns: category and average complexities, and take a mean of the average complexities under the same category name.
What I encountered: I have 5 rows of category, but 30 rows of average complexities. What can I do to take a mean value of all the average complexities under the same category names? All help will be appreciated! Thank you!

Answer 1

filter the values for top 5 category, then group_by category and take mean of average_complexity.
library(dplyr)
board_game_tidy %>%
filter(category %in% names(top_5_category)) %>%
group_by(category) %>%
summarise(average_complexity = mean(average_complexity))
# category average_complexity
# <fct> <dbl>
#1 Abstract Strategy 0.844
#2 Action / Dexterity 0.469
#3 Adventure 1.25
#4 Age of Reason 1.95
#5 American Civil War 1.68

Answer 2

You are very close. You need dplyr::summarise()
complexity_top_5_category <- board_game_tidy %>%
group_by(category) %>%
dplyr::summarise(mean_average_complexity = mean(average_complexity, na.rm=TRUE)) %>%
top_n(5, mean_average_complexity)
#select(average_complexity) %>% # you don't need this
#filter(category == c("Abstract Strategy Action / Dexterity", "Adventure", "Age of Reason","American Civil War "))
complexity_top_5_category
You don't have to include dplyr:: before summarise(). However, some other common packages have their versions of summarise() so it's safer to be specific.
You can use top_n() to automatically select the top n categories, instead of using filter().