合并r dataframes

我有A R数据框df_big合并r dataframes

Candidate Status 
A   1 
B   10 
C   12 
D   15 
E   25

等

我有第二个数据帧df_small

Candidate_1 Candidate_2 
A    C 
B    E  
C    D

我要合并df_small和df_big到得到df_final看起来像

Candidate_1 Candidate_2  Status_1  Status_2 
A    C     1   12 
B    E     10   25 
C    D     12   15

我试过的东西效果

df_small_1 = merge(x=df_small,y = df_big,by.x = "Candidate_1",by.y="Candidate") 

df_small_2 = merge(x=df_small,y = df_big,by.x = "Candidate_2",by.y="Candidate")

，但我不知道如何结合df_small_1和df_small_2到df_small

来源

2017-03-17 Ssank

像'df_final =合并（X =合并（X = df_small，Y = df_big，by.x = “Candidate_2”，by.y = “候选人” ），y = df_big，by.x =“Candidate_1”，by.y =“Candidate”）' – HubertL

刚刚重塑为long形式比较容易：'library（tidyverse）; df_small％>％gather（var，Candidate）％>％left_join（df_big）' – alistaire

您需要为每个两位候选人的身份参加两次，一次：

df_result <- merge(x=df_small, y=df_big, by.x="Candidate_1", by.y="Candidate") 
df_result <- merge(x=df_result, y=df_big, by.x="Candidate_2", by.y="Candidate")

来源

2017-03-17 01:13:26

合并是一项昂贵的操作。您可以更好地执行此操作，而无需使用其组合和索引的合并操作。我已经对合并和非合并解决方案进行了基准测试。答案也根据需要给出列的顺序。

doit <- function(df_small, df_big) 
{ 

    # Which elements do we need to copy 
    indx1 <- df_big[["Candidate"]] %in% df_small[["Candidate_1"]] 

    indx2 <- df_big[["Candidate"]] %in% df_small[["Candidate_2"]] 

    # Copy them 
    df_needed <- data.frame(Candiate_1 = df_big[indx1, "Candidate"], Candiate_2 = df_big[indx2, "Candidate"], 
          Status_1 = df_big[indx1, "Status"], Status_2 = df_big[indx2, "Status"]) 

} 

#merge two times 
doit_merge <- function(df_small, df_big) 
{ 
    df_result <- merge(x=df_small, y=df_big, by.x="Candidate_1", by.y="Candidate") 
    df_result <- merge(x=df_result, y=df_big, by.x="Candidate_2", by.y="Candidate") 
} 

library(microbenchmark) 

# benchmark results 
microbenchmark(
    doit(df_small, df_big) , 
    doit_merge(df_small, df_big) 
)

成绩

Unit: microseconds 
expr        min  lq  mean median  uq  max neval cld 
doit(df_small, df_big)  676.570 758.472 1077.203 834.0115 978.9315 4591.473 100 a 
doit_merge(df_small, df_big) 1329.327 1449.205 1986.995 1612.3940 2021.9070 5966.780 100 b

来源

2017-03-17 01:52:16 discipulus

合并r dataframes

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