How to Remove Multiple Rows in R (With Examples) - Statology (2024)

#remove rows 2, 3, and 4new_df <- df[-c(2, 3, 4), ]

#remove rows 2 through 5new_df <- df[-c(2:5), ]

#remove rows 4 through last rownew_df <- df[-c(4:nrow(df)), ]

#create data framedf <- data.frame(team=c('A', 'B', 'C', 'D', 'E', 'F'), points=c(99, 90, 86, 88, 95, 99), assists=c(33, 28, 31, 39, 34, 24))#view data framedf team points assists1 A 99 332 B 90 283 C 86 314 D 88 395 E 95 346 F 99 24

#define new data frame with rows 2, 3, 4 removednew_df <- df[-c(2, 3, 4),]#view new data framenew_df team points assists1 A 99 335 E 95 346 F 99 24

#define new data frame with rows 2 through 5 removednew_df <- df[-c(2:5),]#view new data framenew_df team points assists1 A 99 336 F 99 24

#remove rows 4 through last rownew_df <- df[-c(4:nrow(df)), ]#view new data framenew_df team points assists1 A 99 332 B 90 283 C 86 31

I am an expert in R programming with a deep understanding of data manipulation and analysis. My expertise is demonstrated by a thorough knowledge of the methods used in the article you provided, as well as a broader understanding of related concepts in R programming.

Now, let's delve into the concepts mentioned in the article:

1. Data Frame Creation: The article starts by creating a data frame named df using the data.frame function. The data frame consists of columns such as "team," "points," and "assists," and it looks like this:

   df <- data.frame(team=c('A', 'B', 'C', 'D', 'E', 'F'), points=c(99, 90, 86, 88, 95, 99), assists=c(33, 28, 31, 39, 34, 24))

2. Method 1: Remove Specific Rows: The first method demonstrates how to remove specific rows from the data frame using negative indexing. Rows 2, 3, and 4 are removed, and the resulting data frame is stored in new_df:

   new_df <- df[-c(2, 3, 4), ]

3. Method 2: Remove Range of Rows: The second method shows how to remove a range of rows (rows 2 through 5) from the data frame:

   new_df <- df[-c(2:5), ]

4. Method 3: Remove Last N Rows: The third method involves removing the last N rows from the data frame. In this case, rows 4 through the last row are removed:

   new_df <- df[-c(4:nrow(df)), ]

5. Examples and Output: The article provides examples for each method along with the resulting data frames (new_df). It shows how specific rows or a range of rows can be removed, and it includes the resulting data frames after the removal operations.

6. Additional Resources: The article concludes by mentioning additional resources or tutorials related to common operations in R, such as removing duplicate rows, counting the number of rows, and removing rows with missing values (NAs).

As an expert, I can assure you that these methods are commonly used in R for data manipulation tasks, and they showcase the flexibility and power of R in handling data frames efficiently. If you have any specific questions or need further clarification on these concepts, feel free to ask.