如何使用 dplyr 过滤带有条件语句的分组数据框？

Question

我想使用条件过滤使用 dplyr 的数据框。我要测试的条件是国家-年份组合是否有两个版本。

df <- data.frame(country = c("country1", "country2", "country1", "country2", "country3"), year = rep(2011,5), version = c("versionA", "versionA", "versionB", "versionB", "versionB"))

这是我在查看here后尝试的：

df %>%
     group_by(country, year) %>%
     {if unique(version)==1 . else filter(version == "versionA")}

我希望得到的是一个如下所示的数据框：

country     year     version

country1    2011     versionA
country2    2011     versionA
country3    2011     versionB

Answer 1

要计算唯一值的数量，我们可以使用n_distinct 并根据它过滤行。

library(dplyr)

df %>%
  group_by(country, year) %>%
  filter(if(n_distinct(version) == 2) version == 'versionA' else TRUE)


#  country   year version 
#  <fct>    <dbl> <fct>   
#1 country1  2011 versionA
#2 country2  2011 versionA
#3 country3  2011 versionB

Answer 2

按“国家”、“年份”、filter 分组后，如果不同元素的数量大于 1，则返回“版本A”，否则返回第一个元素

library(dplyr)
df %>%
  group_by(country, year)  %>% 
  filter((n_distinct(version)  > 1 & version == 'versionA')|row_number() == 1)
# A tibble: 3 x 3
# Groups:   country, year [3]
#  country   year version 
#  <fct>    <dbl> <fct>   
#1 country1  2011 versionA
#2 country2  2011 versionA
#3 country3  2011 versionB

---

或者这可以添加到if/else

df %>%
    group_by(country, year) %>%
    filter(if(n_distinct(version) > 1) version == 'versionA'
       else row_number() ==1)
# A tibble: 3 x 3
# Groups:   country, year [3]
#  country   year version 
#  <fct>    <dbl> <fct>   
#1 country1  2011 versionA
#2 country2  2011 versionA
#3 country3  2011 versionB

---

或者另一个选项是arrange

df %>% 
    arrange(country, year, version != 'versionA') %>% 
    group_by(country, year) %>% 
    slice(1)

---

或summarize

df %>%
    group_by(country, year) %>%
    summarise(version = if(n_distinct(version) > 1) 'versionA' else first(version))

---

或使用data.table

library(data.table)
setDT(df)[, .SD[if(n_distinct(version) > 1) version == 'versionA' 
          else 1], .(country, year)]

Answer 3

Base R 单线感谢 (@akrun)：

df[!(duplicated(df[1:2])),]

Base R 单线：

df[!(duplicated(df$country, df$year)),]

Tidyverse 解决方案：

library(tidyverse)
df %>%
  filter(!(duplicated(country, year)))

更通用的基础 R 解决方案：

# Create a counter of versions for each year and country: 

df$tmp <- with(lapply(df, function(x){if(is.factor(x)){as.character(x)}else{x}}),
               ave(version, paste0(country, year), FUN = seq.int))

# Subset the dataframe to hold only the first record for each year/country: 

df[which(df$tmp == 1), ]

更通用的 tidyverse 解决方案：

df %>%
  arrange(version) %>% 
  filter(!(duplicated(country, year)))