Introduction to the R language merge function

Authors <-Data.frame (
surname = I (C ("Tukey", "Venables", "Tierney", "Ripley", "McNeil"),
Nationality = C ("Us", "Australia", "Us", "UK", "Australia"),
deceased = C ("Yes", Rep ("No", 4)))
Books <-Data.frame (
Name = I (C ("Tukey", "Venables", "Tierney",
"Ripley", "Ripley", "McNeil", "R Core"),
title = C ("Exploratory Data analysis",
"Modern applied Statistics ...",
"Lisp-stat",
"Spatial Statistics", "Stochastic Simulation",
"Interactive Data Analysis",
"An Introduction to R"),
Other.author = C (Na, "Ripley", Na, na, na, na,
"Venables & Smith"))

If you want to implement a INNER join function similar to SQL, use the code
M1 <-Merge (authors, books, by.x = "surname", by.y = "name")
If you want to implement the LEFT JOIN function, use the code
M1 <-Merge (authors, books, by.x = "surname", by.y = "name", All.x=true)
Right Join function code
M1 <-Merge (authors, books, by.x = "surname", by.y = "name", All.y=true)
All Join function code
M1 <-Merge (authors, books, by.x = "surname", by.y = "name", All=true)

The summary of univariate matching is these, but for multivariable matching, such as the following two tables, it is necessary to match the case of K1,K2 two variables equal
x <-data.frame (k1 = C (na,na,3,4,5), K2 = C (1,na,na,4,5), data = 1:5)
Y <-data.frame (k1 = C (na,2,na,4,5), K2 = C (na,na,3,4,5), data = 1:5)

The matching code is the following merge (X, y, by = C ("K1", "K2")) #inner Join





> id<-c (1,2,3,4)
> name<-c ("Jim", "Tony", "Lisa", "Tom")
> score<-c (89,22,78,78)
> Student1<-data.frame (id,name)
> Student2<-data.frame (Id,score)
> Student1
ID Name
1 1 Jim
2 2 Tony
3 3 Lisa
4 4 Tom
> Student2
ID Score
1 1 89
2 2 22
3 3 78
4 4 78
> Total_student<-merge (student1,student2,by= "ID")
> total_student
ID Name Score
1 1 Jim 89
2 2 Tony 22
3 3 Lisa 78
4 4 Tom 78
> (ID&LT;-C)
> name<-c ("Jame", "Kevin", "Sunny")
> Student1<-data.frame (id,name)
> id<-c (4,5,6)
> name<-c ("Sun", "Frame", "Eric")
> Student2<-data.frame (id,name)
> Student1
ID Name
1 1 Jame
2 2 Kevin
3 3 Sunny
> Student2
ID Name
1 4 Sun
2 5 Frame
3 6 Eric
> Total<-rbind (STUDENT1,STUDENT2)
> Total
ID Name
1 1 Jame
2 2 Kevin
3 3 Sunny
4 4 Sun
5 5 Frame
6 6 Eric
> Authors <-Data.frame (
+ surname = I (C ("Tukey", "Venables", "Tierney", "Ripley", "McNeil")),
+ nationality = C ("Us", "Australia", "Us", "UK", "Australia"),
+ deceased = C ("Yes", Rep ("No", 4)))
> Authors
Surname Nationality deceased
1 Tukey US Yes
2 Venables Australia No
3 Tierney US No
4 Ripley UK No
5 McNeil Australia No
> Books <-data.frame (
+ name = I (C ("Tukey", "Venables", "Tierney",
+ "Ripley", "Ripley", "McNeil", "R Core"),
+ title = C ("Exploratory Data analysis",
+ "Modern applied Statistics ...",
+ "Lisp-stat",
+ "Spatial Statistics", "Stochastic Simulation",
+ "Interactive Data analysis",
+ "An Introduction to R"),
+ Other.author = C (Na, "Ripley", Na, na, na, na,
+ "Venables & Smith"))
>
> Books
Name Title Other.author
1 Tukey Exploratory Data analysis <NA>
2 Venables modern applied Statistics ... Ripley
3 Tierney Lisp-stat <NA>
4 Ripley Spatial Statistics <NA>
5 Ripley Stochastic Simulation <NA>
6 McNeil Interactive Data Analysis <NA>
7 R Core an Introduction to R Venables & Smith
> Authors
Surname Nationality deceased
1 Tukey US Yes
2 Venables Australia No
3 Tierney US No
4 Ripley UK No
5 McNeil Australia No
> M1 <-Merge (authors, books, by.x = "surname", by.y = "name")
> M1
Surname Nationality deceased title Other.author
1 McNeil Australia no Interactive Data analysis <NA>
2 Ripley UK no Spatial Statistics <NA>
3 Ripley UK no Stochastic Simulation <NA>
4 Tierney US No Lisp-stat <NA>
5 Tukey US Yes exploratory Data analysis <NA>
6 Venables Australia No modern applied Statistics ... Ripley
> M1 <-Merge (authors, books, by.x = "surname", by.y = "name", All.x=true)
> M1
Surname Nationality deceased title Other.author
1 McNeil Australia no Interactive Data analysis <NA>
2 Ripley UK no Spatial Statistics <NA>
3 Ripley UK no Stochastic Simulation <NA>
4 Tierney US No Lisp-stat <NA>
5 Tukey US Yes exploratory Data analysis <NA>
6 Venables Australia No modern applied Statistics ... Ripley
> M1 <-Merge (authors, books, by.x = "surname", by.y = "name", All.y=true)
> M1
Surname Nationality deceased Title
1 McNeil Australia no Interactive Data analysis
2 R Core <NA> <NA> an Introduction to R
3 Ripley UK No Spatial Statistics
4 Ripley UK No Stochastic Simulation
5 Tierney US No Lisp-stat
6 Tukey US Yes exploratory Data analysis
7 Venables Australia No modern applied Statistics ...
Other.author
1 <NA>
2 Venables & Smith
3 <NA>
4 <NA>
5 <NA>
6 <NA>
7 Ripley
> x <-data.frame (k1 = C (na,na,3,4,5), K2 = C (1,na,na,4,5), data = 1:5)
> y <-data.frame (k1 = C (na,2,na,4,5), K2 = C (na,na,3,4,5), data = 1:5)
> x
K1 K2 Data
1 NA 1 1
2 Na Na 2
3 3 NA 3
4 4 4 4
5 5 5 5
> y
K1 K2 Data
1 Na Na 1
2 2 NA 2
3 NA 3 3
4 4 4 4
5 5 5 5
> Merge (x, y, by = C ("K1", "K2"))
K1 K2 data.x Data.y
1 4 4) 4 4
2 5 5) 5 5
3 Na Na 2 1
>