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[英]Add values to other values in another dataframe based on matching pair names in two columns of two dataframes in R
[英]How do I add another column to a dataframe in R that shows the difference between the columns of two other dataframes?
我有的:
我有两个数据框可以使用。 那些是:
> print(myDF_2003)
A_score country B_score
1 200 Germany 11
2 150 Italy 9
3 0 Sweden 0
和:
> print(myDF_2005)
A_score country B_score
1 -300 France 16
2 100 Germany 12
3 200 Italy 15
4 40 Spain 17
它们是由以下代码生成的,我不想更改它们:
#_________2003______________
myDF_2003=data.frame(c(200,150,0),c("Germany", "Italy", "Sweden"), c(11,9,0))
colnames(myDF_2003)=c("A_score","country", "B_score")
myDF_2003$country=as.character(myDF_2003$country)
myDF_2003$country=factor(myDF_2003$country, levels=unique(myDF_2003$country))
myDF_2003$A_score=as.numeric(as.character(myDF_2003$A_score))
myDF_2003$B_score=as.numeric(as.character(myDF_2003$B_score))
#_________2005______________
myDF_2005=data.frame(c(-300,100,200,40),c("France","Germany", "Italy", "Spain"), c(16,12,15,17))
colnames(myDF_2005)=c("A_score","country", "B_score")
myDF_2005$country=as.character(myDF_2005$country)
myDF_2005$country=factor(myDF_2005$country, levels=unique(myDF_2005$country))
myDF_2005$A_score=as.numeric(as.character(myDF_2005$A_score))
myDF_2005$B_score=as.numeric(as.character(myDF_2005$B_score))
我想要的是:我想将另一列粘贴到myDF_2005
,该列具有两个先前数据框中都存在的国家/地区的B_Scores差异。 换句话说:我想产生以下输出:
> print(myDF_2005_2003_Diff)
A_score country B_score B_score_Diff
1 -300 France 16
2 100 Germany 12 1
3 200 Italy 15 6
4 40 Spain 17
问题:执行此操作的最优雅的代码是什么?
# join in a temporary dataframe
temp <- merge(myDF_2005, myDF_2003, by = "country", all.x = T)
# calculate the difference and assign a new column
myDF_2005$B_score_Diff <- temp$B_score.x - temp$B_score.y
使用dplyr的解决方案。 想法是合并两个数据框,然后计算差异。
library(dplyr)
myDF_2005_2 <- myDF_2005 %>%
left_join(myDF_2003 %>% select(-A_score), by = "country") %>%
mutate(B_score_Diff = B_score.x - B_score.y) %>%
select(-B_score.y) %>%
rename(B_score = B_score.x)
myDF_2005_2
# A_score country B_score B_score_Diff
# 1 -300 France 16 NA
# 2 100 Germany 12 1
# 3 200 Italy 15 6
# 4 40 Spain 17 NA
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