如何加入具有共同列的兩個數據框？

Question

我想添加一個新的列，這取決於另一個列的行組合。

例如可以說我有一個數據幀象下面這樣：

library(dplyr) 
library(minpack.lm) 
library(broom) 
No = c(replicate(1,rep(letters[1:6],each=10))) 
ACME <- as.character(rep(rep(c(78,110),each=10),times=3)) 
ARGON <- as.character(rep(rep(c(256,320,384),each=20),times=1)) 
V <- rep(c(seq(2,40,length.out=5),seq(-2,-40,length.out=5)),times=1) 
DQ0 = c(replicate(2, sort(runif(10,0.001,1)))) 
direc <- rep(rep(c("North","South"),each=5),times=6) 

df <- data.frame(No,ACME,ARGON,V,DQ0,direc) 


>df 
    No ACME ARGON  V  DQ0 direc 
1 a 78 256 2.0 0.07532351 North 
2 a 78 256 11.5 0.13785481 North 
3 a 78 256 21.0 0.27397961 North 
4 a 78 256 30.5 0.44296243 North 
5 a 78 256 40.0 0.45721902 North 
6 a 78 256 -2.0 0.68077463 North 
7 a 78 256 -11.5 0.68764283 North 
8 a 78 256 -21.0 0.76284209 North 
9 a 78 256 -30.5 0.81040056 North 
10 a 78 256 -40.0 0.95336230 North 
11 b 110 256 2.0 0.04190305 South 
12 b 110 256 11.5 0.17484353 South 
13 b 110 256 21.0 0.22409319 South 
---------------- 

我適合這個df使用nlsLM溫控功能從minpack.lm包

- >配合部

nls_fit=nlsLM(DQ0~ifelse(df$direc=="North"&V<J1, exp((-t_pw)/f0*exp(-del1*(1-V/J1)^2)),1)*ifelse(df$direc=="South"&V>J2, exp((-t_pw)/f0*exp(-del2*(1-V/J2)^2)),1) 
      ,data=df,start=c(del1=1,J1=15,del2=1,J2=-15),trace=T) 

後擬合我想創建一個新的數據框df_new與新列名爲address

df_new<- df%>% 
    group_by(No)%>% 
    do(data.frame(model=tidy(nls_fit)))%>% # **this part is related fit fitting result. After this process I got "model.term" and "model.estimate"** columns and in the next step I renamed them. 
    select_("delta"="model.term","value"= "model.estimate")%>% 
    filter(delta%in%c("del1","del2"))%>% #**I filter some fitting parameters** 
    mutate(adress=interaction(ACME,ARGON))%>% #this part is not working 
    ungroup 

我收到錯誤，說

錯誤：不兼容的大小（％d），預計％d（組大小）或1

最後我有一個這樣的輸出沒有mutatate部分

df_new

No delta value 
1 a del1 1.479056 
2 a del2 1.016404 
3 b del1 1.479056 
4 b del2 1.016404 
5 c del1 1.479056 
6 c del2 1.016404 
7 d del1 1.479056 
8 d del2 1.016404 
9 e del1 1.479056 
10 e del2 1.016404 
11 f del1 1.479056 
12 f del2 1.016404 

我希望得到像這樣的東西;

No delta value adress 
1 a del1 1.479056 78.256 
2 a del2 1.016404 78.256 
3 b del1 1.479056 110.256 
4 b del2 1.016404 110.256 
5 c del1 1.479056 78.320 
6 c del2 1.016404 78.320 
7 d del1 1.479056 110.320 
8 d del2 1.016404 110.320 
9 e del1 1.479056 78.384 
10 e del2 1.141958 78.384 
11 f del1 1.019201 110.384 
12 f del2 1.141958 110.384 

Answer 1

你真正想要的是df_new和df之間的連接。你可以做到這一點，例如data.table：

library(data.table) #v1.9.5+ 
setDT(df_new)[df, adr:=adress, on="No"] 

如果你想從CRAN的最新版本做，你可以這樣做：

setDT(df_new, key="No")[setDT(df, key="No"), adr:=adress] 

均可以得到以下結果：

> dt_new 
    No delta value  adr 
1: a del1 1.479056 78.256 
2: a del2 1.016404 78.256 
3: b del1 1.479056 110.256 
4: b del2 1.016404 110.256 
5: c del1 1.479056 78.320 
6: c del2 1.016404 78.320 
7: d del1 1.479056 110.320 
8: d del2 1.016404 110.320 
9: e del1 1.479056 78.384 
10: e del2 1.016404 78.384 
11: f del1 1.479056 110.384 
12: f del2 1.016404 110.384 

使用dplyr的方法：

df_new2 <- df %>% select(No, adress) %>% group_by(No) %>% 
    summarise(adr = unique(adress)) %>% 
    left_join(df_new, ., by="No") 

可以得到相同的結果：

> identical(df_new2, setDF(df_new)) 
[1] TRUE 

---

注：我使用的development version of data.table