# rbind in R | 3 Examples (Vector, Data Frame & rbind.fill for Missing Columns)

**Basic R Syntax:**

rbind(my_data, new_row) |

rbind(my_data, new_row)

The name of the *rbind* R function stands for *row-bind*. The rbind function can be used to combine several vectors, matrices and/or data frames by rows. Above, you can find the basic code for rbind in R.

In the following article, I’m going to provide you with 3 examples for the **application of the rbind function** in R. Let’s start right away…

## Example 1: rbind Vector to Data Frame

The easiest way of using rbind in R is the combination of a vector and a data frame. First, let’s create some example data frame…

x1 <- c(7, 4, 4, 9) # Column 1 of data frame x2 <- c(5, 2, 8, 9) # Column 2 of data frame x3 <- c(1, 2, 3, 4) # Column 3 of data frame data_1 <- data.frame(x1, x2, x3) # Create example data frame |

x1 <- c(7, 4, 4, 9) # Column 1 of data frame x2 <- c(5, 2, 8, 9) # Column 2 of data frame x3 <- c(1, 2, 3, 4) # Column 3 of data frame data_1 <- data.frame(x1, x2, x3) # Create example data frame

…and an example vector:

vector_1 <- c(9, 8, 7) # Create example vector |

vector_1 <- c(9, 8, 7) # Create example vector

Now, let’s rbind this vector to the data frame:

rbind(data_1, vector_1) # rbind vector to data frame |

rbind(data_1, vector_1) # rbind vector to data frame

**Table 1: Output Data Table after Applying rbind to Vector and Data Frame.**

Table 1 illustrates the output of the rbind function: The first four rows are identical to our original data frame data_1; the fifth row is identical to our vector vector_1.

## Example 2: rbind Two Data Frames in R

The rbind command can also be applied to two data frames. Let’s create a second data frame and row bind it to data_1 (the data frame that we created above):

x1 <- c(7, 1) # Column 1 of data frame 2 x2 <- c(4, 1) # Column 2 of data frame 2 x3 <- c(4, 3) # Column 3 of data frame 2 data_2 <- data.frame(x1, x2, x3) # Create second data frame |

x1 <- c(7, 1) # Column 1 of data frame 2 x2 <- c(4, 1) # Column 2 of data frame 2 x3 <- c(4, 3) # Column 3 of data frame 2 data_2 <- data.frame(x1, x2, x3) # Create second data frame

We can rbind these two data frames with the same R code as before:

rbind(data_1, data_2) # rbind two data frames in R |

rbind(data_1, data_2) # rbind two data frames in R

**Table 2: Output after row-binding Two Data Frames in R.**

As in Example 1, the upper part of the rbind output consists of data_1 and the lower part of the rbind output consists of data_2.

**Note:** Both data frames have the same column names. When the columns of the two data frames differ, it gets a bit more complicated. In the next example, I’m going to show you how to rbind data frames with different column names.

## Example 3: *rbind fill* – Row Bind with Missing Columns

The binding of data frames with different columns / column names is a bit more complicated with the rbind function. R usually returns the error *“Error in match.names(clabs, names(xi))”*, if you try to use the rbind function for data frames with different columns.

For that reason, the plyr package (be careful: it’s called *plyr*; not *dplyr*) provides the rbind.fill R function as add-on to the rbind base function. In the following example, I’ll show you how to use the plyr rbind.fill function in R.

Consider the following two example data frames:

col1 <- c(5, 1, 1, 8) # Column 1 of data frame 1 plyr example col2 <- c(9, 7, 5, 1) # Column 2 of data frame 1 plyr example col3 <- c(1, 1, 2, 2) # Column 3 of data frame 1 plyr example data_plyr1 <- data.frame(col1, col2, col3) # Create plyr data frame 1 # col1 col2 col3 # 5 9 1 # 1 7 1 # 1 5 2 # 8 1 2 |

col1 <- c(5, 1, 1, 8) # Column 1 of data frame 1 plyr example col2 <- c(9, 7, 5, 1) # Column 2 of data frame 1 plyr example col3 <- c(1, 1, 2, 2) # Column 3 of data frame 1 plyr example data_plyr1 <- data.frame(col1, col2, col3) # Create plyr data frame 1 # col1 col2 col3 # 5 9 1 # 1 7 1 # 1 5 2 # 8 1 2

col3 <- c(5, 1, 1, 8) # Column 1 of data frame 2 plyr example col4 <- c(9, 7, 5, 1) # Column 2 of data frame 2 plyr example data_plyr2 <- data.frame(col3, col4) # Create plyr data frame 2 # col3 col4 # 5 9 # 1 7 # 1 5 # 8 1 |

col3 <- c(5, 1, 1, 8) # Column 1 of data frame 2 plyr example col4 <- c(9, 7, 5, 1) # Column 2 of data frame 2 plyr example data_plyr2 <- data.frame(col3, col4) # Create plyr data frame 2 # col3 col4 # 5 9 # 1 7 # 1 5 # 8 1

To apply rbind.fill in R, we need to load the plyr package first:

library("plyr") # Load plyr package |

library("plyr") # Load plyr package

Now, we can apply the rbind.fill R command to our two example data frames:

rbind.fill(data_plyr1, data_plyr2) # Apply the rbind.fill plyr function |

rbind.fill(data_plyr1, data_plyr2) # Apply the rbind.fill plyr function

**Table 3: Output after row-binding Two Data Frames with the rbind.fill R Function.**

Table 3 makes it clear how rbind fill works: The function creates a column for each column name that appears either in the first or in the second data matrix. If a column exists in both data frames, it is row binded as usual. However, if a column is missing in one of the two data frames, the empty cells are replaced by NA.

## Video: Further Examples of rbind & rbind.fill

Have a look at the following video of my Statistical Programming YouTube channel. In the video, I’m showing two examples for rbind() and rbind.fill() based on a real data set.

## Further Reading

- The cbind Function in R
- bind_rows & bind_cols functions of dplyr Package
- The merge Function in R
- Convert List to Data Frame
- Subsetting Data Frame in R
- NA Values in R
- The R Programming Language

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