To merge two dataframes in R, you can use merge() function or *_join() function from dplyr package.

The following methods show how you can do it with syntax.

Method 1: Use merge() Function

merge(df1,df2,by="common_column")

Method 2: Use join() Function

library(dplyr)

*_join(df1, df2, by = "common_column")

Using join() function you can perform inner_join, right_join, left_join and outer_join operations on dataframe.

The following examples show how to merge two dataframes using merge and join function in R.

Using merge() Function

Let’s see how we can use merge() function in R:

# Create dataframe
df1 <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2001-01-19","2003-04-27","2004-11-26","2008-11-25")),
                 Machine_name = c("Machine1","Machine2","Machine3","Machine4","Machine5","Machine6"),
                 Value = c(108,120,135,95,98,105),Reading= c(110,97,91,89,80,85))

df2 <- data.frame( Machine_name = c("Machine1","Machine3","Machine4","Machine6"),
                 Value = c(120,121,107,105))

# Merge dataframe by inner join
df <- merge(df1,df2,by="Machine_name")

# Print dataframe 
print(df)

Output:

 Machine_name Start_date Value.x Reading Value.y
1     Machine1 2000-05-21     108     110     120
2     Machine3 2001-01-19     135      91     121
3     Machine4 2003-04-27      95      89     107
4     Machine6 2008-11-25     105      85     105

Here the output shows two dataframes are merge using merge() function based on common Machine_name column between them.

Using join() Function

Let’s see how we can use join() function in R.

Using inner_join() Function

Suppose we want to merge only those rows which are common between both dataframes then use inner_join() function:

library(dplyr)

# Create dataframe
df1 <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2003-04-27","2004-11-26","2008-11-25")),
                  Machine_name = c("Machine1","Machine2","Machine4","Machine5","Machine6"),
                  Value = c(108,135,95,98,105),Reading= c(110,91,89,80,85))

df2 <- data.frame( Machine_name = c("Machine1","Machine3","Machine4","Machine6"),
                   Value = c(120,121,107,105))

# Merge dataframe by inner join 
inner_df <- inner_join(df1, df2, by = "Machine_name")   

# Show merge dataframe
print(inner_df)

Output:

  Start_date Machine_name Value.x Reading Value.y
1 2000-05-21     Machine1     108     110     120
2 2003-04-27     Machine4      95      89     107
3 2008-11-25     Machine6     105      85     105

Here the output shows common rows between both dataframes.

Using left_join() Function

Let’s see how we can merge dataframe using left_join() function:

library(dplyr)

# Create dataframe
df1 <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2003-04-27","2004-11-26","2008-11-25")),
                  Machine_name = c("Machine1","Machine2","Machine4","Machine5","Machine6"),
                  Value = c(108,135,95,98,105),Reading= c(110,91,89,80,85))

df2 <- data.frame( Machine_name = c("Machine1","Machine3","Machine4","Machine6"),
                   Value = c(120,121,107,105))

# Merge dataframe by left join
df <- left_join(df1,df2,by="Machine_name")

# Print dataframe 
print(df)

Output:

  Start_date Machine_name Value.x Reading Value.y
1 2000-05-21     Machine1     108     110     120
2 1998-03-28     Machine2     135      91      NA
3 2003-04-27     Machine4      95      89     107
4 2004-11-26     Machine5      98      80      NA
5 2008-11-25     Machine6     105      85     105

Here the output shows all rows from left dataframe and common rows from right dataframe.

Using right_join() Function

Let’s see how we can merge dataframe using right_join() function:

library(dplyr)

# Create dataframe
df1 <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2003-04-27","2004-11-26","2008-11-25")),
                  Machine_name = c("Machine1","Machine2","Machine4","Machine5","Machine6"),
                  Value = c(108,135,95,98,105),Reading= c(110,91,89,80,85))

df2 <- data.frame( Machine_name = c("Machine1","Machine3","Machine4","Machine6"),
                   Value = c(120,121,107,105))

# Merge dataframe by right join
df <- right_join(df1,df2,by="Machine_name")

# Print dataframe 
print(df)

Output:

  Start_date Machine_name Value.x Reading Value.y
1 2000-05-21     Machine1     108     110     120
2 2003-04-27     Machine4      95      89     107
3 2008-11-25     Machine6     105      85     105
4       <NA>     Machine3      NA      NA     121

Here the output shows all rows from right dataframe and common rows from left dataframe based on Machine_name column.

Using full_join() Function

Let’s see how to common all rows of both dataframes:

library(dplyr)

# Create dataframe
df1 <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2003-04-27","2004-11-26","2008-11-25")),
                  Machine_name = c("Machine1","Machine2","Machine4","Machine5","Machine6"),
                  Value = c(108,135,95,98,105),Reading= c(110,91,89,80,85))

df2 <- data.frame( Machine_name = c("Machine1","Machine3","Machine4","Machine6"),
                   Value = c(120,121,107,105))

# Merge dataframe by full join
df <- full_join(df1,df2,by="Machine_name")

# Print dataframe 
print(df)

Output:

  Start_date Machine_name Value.x Reading Value.y
1 2000-05-21     Machine1     108     110     120
2 1998-03-28     Machine2     135      91      NA
3 2003-04-27     Machine4      95      89     107
4 2004-11-26     Machine5      98      80      NA
5 2008-11-25     Machine6     105      85     105
6       <NA>     Machine3      NA      NA     121

Here the output shows all rows from both dataframes.