在 R 中，如何将一个数据框中选定行的值与另一个数据框中选定的列匹配？

Question

I have two separate dataframes. A few of the columns from one dataframe have the same name as some rows in the other. How can I match values corresponding to a few rows in one df to values corresponding to a few columns (with the same names as the rows) in another df?

In this example, I want to know if for each row in the first df, the values (A/B/C/D) under each question (E4Q_) matches the value at row E4Q_ and column 'Answer' in df2. After this, I want to either print TRUE/FALSE or 1/0 in a third data frame which is set up like the first.

df1:
Name E4Q1 E4Q2 E4Q3 E4Q4 E4Q5 
XYZ  B    B    A    A    B
DEF  D    D    D    C    B
GHJ  -    -    B    A    C

    df2:
Question Answer
E4Q1     B
E4Q2     D
E4Q3     C
E4Q4     A
E4Q5     C

df3:
Name E4Q1 E4Q2 E4Q3 E4Q4 E4Q5 
XYZ  1    0    0    1    0
DEF  0    1    0    0    0
GHJ  0    0    0    1    1

Answer 1

If you are using the current version of R you have stringsAsFactos=FALSE as the default. This task is an excellent example of why that change was made. Factos would complicate this process completely. If you are like me you need to do the data entry with that explicitly set:

 df1 <- read.table(text= "Name E4Q1 E4Q2 E4Q3 E4Q4 E4Q5 
 XYZ  B    B    A    A    B
 DEF  D    D    D    C    B
 GHJ  -    -    B    A    C", head=TRUE,stringsAsFactors=FALSE)
 
 df2 <- read.table(text=" Question Answer
 E4Q1     B
 E4Q2     D
 E4Q3     C
 E4Q4     A
 E4Q5     C", head=TRUE,stringsAsFactors=FALSE)

df3 <- df1 # same structure but Question columns will be changed to 1/0

First try : loop through col names and compare results to correct values in df2:

 for( i in names(df1[-1]) ){ df3[[i]] <- df1[[i]] == df2[df2$Question==i, 2] }
 df3
  Name  E4Q1  E4Q2  E4Q3  E4Q4  E4Q5
1  XYZ  TRUE FALSE FALSE  TRUE FALSE
2  DEF FALSE  TRUE FALSE FALSE FALSE
3  GHJ FALSE FALSE FALSE  TRUE  TRUE

So need to coerce to numeric, either with as.numeric or by adding 0.

 for( i in names(df1[-1]) ){ df3[[i]] <- ( df1[[i]] == df2[df2$Question==i, 2])+0 }
 df3
  Name E4Q1 E4Q2 E4Q3 E4Q4 E4Q5
1  XYZ    1    0    0    1    0
2  DEF    0    1    0    0    0
3  GHJ    0    0    0    1    1