Manipulating Rows | Data Frames

Course Content

# R Introduction: Part II

R Introduction: Part II

## Manipulating Rows

Now let's learn how to add/delete rows. Let's consider two methods. The first is more applicable for adding a single row.

The method is to assign a new row to the last plus one index of an existing data frame (to get the number of rows, use the `nrow()` function). Remember that you can not store data of different types using vectors. So, you need to assign either a data frame or a list with new values. Do not worry if you do not know lists. In simple words, this is like a vector that allows us to store data of different types. Let's represent that. The initial data frame is shown below.

Note

By default, when changing a data frame, any new string values in a list are automatically converted to factors. To prevent this automatic conversion, the parameter `stringsAsFactors = FALSE` should be specified during the creation of the data frame. This approach should be applied whenever you are modifying rows in the data frame.

You could do this by using a new data frame and the `merge` function. This method requires the same column names and setting of necessary parameters (`all = T`).

As you can see, the outputs are identical. To remove rows out of the data frame, use square quotes and put a minus sign to the left of the row index. For example, `test[-1,]` will remove the first row (the same as for matrices)

Let's continue working with the `store` data frame.

1. Remove the `'Dining chair'` row (index 4) out of the `store` data frame. Reassign the result to the `store` variable.
2. Add a new row to the data frame `store` using the `list` approach with the data below.
 Item Price Sold Kitchen Cabinet 70 67

Output modified data frame.

Everything was clear?

Section 2. Chapter 6

Course Content

# R Introduction: Part II

R Introduction: Part II

## Manipulating Rows

Now let's learn how to add/delete rows. Let's consider two methods. The first is more applicable for adding a single row.

The method is to assign a new row to the last plus one index of an existing data frame (to get the number of rows, use the `nrow()` function). Remember that you can not store data of different types using vectors. So, you need to assign either a data frame or a list with new values. Do not worry if you do not know lists. In simple words, this is like a vector that allows us to store data of different types. Let's represent that. The initial data frame is shown below.

Note

By default, when changing a data frame, any new string values in a list are automatically converted to factors. To prevent this automatic conversion, the parameter `stringsAsFactors = FALSE` should be specified during the creation of the data frame. This approach should be applied whenever you are modifying rows in the data frame.

You could do this by using a new data frame and the `merge` function. This method requires the same column names and setting of necessary parameters (`all = T`).

As you can see, the outputs are identical. To remove rows out of the data frame, use square quotes and put a minus sign to the left of the row index. For example, `test[-1,]` will remove the first row (the same as for matrices)

Let's continue working with the `store` data frame.
1. Remove the `'Dining chair'` row (index 4) out of the `store` data frame. Reassign the result to the `store` variable.
2. Add a new row to the data frame `store` using the `list` approach with the data below.