R:按列的最常用值对数据进行排序

统计555

我在这里关注这个stackoverflow帖子:基于R中的频率排序

我正在尝试按“ Node_A”列的最常用值对数据进行排序。

library(dplyr)

Data_I_Have <- data.frame(
   
    "Node_A" = c("John", "John", "John", "John, "John", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"),
    "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude"),
    " Place_Where_They_Met" = c("Chicago", "Boston", "Seattle", "Boston", "Paris", "Paris", "Chicago", "London", "Chicago", "London", "Paris"),
  "Years_They_Have_Known_Each_Other" = c("10", "10", "1", "5", "2", "8", "7", "10", "3", "3", "5"),
  "What_They_Have_In_Common" = c("Sports", "Movies", "Computers", "Computers", "Video Games", "Sports", "Movies", "Computers", "Sports", "Sports", "Video Games")
)

sort = Data_I_Have %>% arrange(Node_A, desc(Freq))

有人可以告诉我我在做什么错吗?谢谢

休伯特

作为该帖子的最后答案,您提到:

Data_I_Have %>% 
  group_by(Node_A) %>%
  arrange( desc(n()))

# Node_A Node_B X.Place_Where_They_Met Years_They_Have_Known_Each_Other What_They_Have_In_Common
# <chr>  <chr>  <chr>                  <chr>                            <chr>                   
# 1  John   Claude Chicago                10                               Sports                  
# 2  John   Peter  Boston                 10                               Movies                  
# 3  John   Tim    Seattle                1                                Computers               
# 4  John   Tim    Boston                 5                                Computers               
# 5  John   Claude Paris                  2                                Video Games             
# 6  Peter  Henry  Paris                  8                                Sports                  
# 7  Tim    Kevin  Chicago                7                                Movies                  
# 8  Kevin  Claude London                 10                               Computers               
# 9  Adam   Tim    Chicago                3                                Sports                  
# 10 Adam   Henry  London                 3                                Sports                  
# 11 Xavier Claude Paris                  5                                Video Games             

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