从R中的数据框中获取具有多个单独观察的组级观察计数

Question

我如何得到这样的数据帧:

soccer_player country position
"sam"         USA     left defender
"jon"         USA     right defender
"sam"         USA     left midfielder
"jon"         USA     offender
"bob"         England goalie
"julie"       England central midfielder
"jane"        England goalie

看起来像这样(每个国家/地区拥有独特玩家数量的国家/地区):

country player_count
USA     2
England 3

显而易见的复杂因素是每个玩家有多个观察,所以我不能简单table(df$country)地获得每个国家的观察数量.

我一直在玩table()和merge()功能,但没有运气.

Answer 1

dplyr v 3.0的新功能提供了一个紧凑的解决方案:

数据:

dd <- read.csv(text='
soccer_player,country,position
"sam",USA,left defender
"jon",USA,right defender
"sam",USA,left midfielder
"jon",USA,offender
"bob",England,goalie
"julie",England,central midfielder
"jane",England,goalie')

码:

library(dplyr)

dd %>% distinct(soccer_player,country) %>% 
       count(country)

Answer 2

这是一种方式:

as.data.frame(table(unique(d[-3])$country))
#      Var1 Freq
# 1 England    3
# 2     USA    2

删除第三列,删除任何重复的国家/地区名称对,然后计算每个国家/地区的出现次数.

Answer 3

不使用任何包,你可以做:

List = by(df, df$country, function(x) length(unique(x$soccer_player)))
DataFrame = do.call(rbind, lapply(names(List), function(x) 
  data.frame(country=x, player_count=List[[x]])))
#  country player_count
#1 England            2
#2     USA            2

通过以下方式更容易data.table:

dt = data.table(df)
dt[,list(player_count = length(unique(soccer_player))),by=country]