You can use the following syntax to remove specific row numbers in R:

#remove 4th row
new_df <- df[-c(4), ]

#remove 2nd through 4th row
new_df <- df[-c(2:4), ]

#remove 1st, 2nd, and 4th row
new_df <- df[-c(1, 2, 4), ]

You can use the following syntax to remove rows that don’t meet specific conditions:

#only keep rows where col1 value is less than 10 and col2 value is less than 6
new_df <- subset(df, col1<10 & col2<6)

And you can use the following syntax to remove rows with an NA value in any column:

#remove rows with NA value in any column
new_df <- na.omit(df)

The following examples show how to use each of these functions in practice.

Example 1: Remove Rows by Number

The following code shows how to remove rows by specific row numbers in R:

#create data frame
df <- data.frame(player=c('A', 'B', 'C', 'D', 'E'),
                 pts=c(17, 12, 8, 9, 25),
                 rebs=c(3, 3, 6, 5, 8),
                 blocks=c(1, 1, 2, 4, NA))

#view data frame
df
  player pts rebs blocks
1      A  17    3      1
2      B  12    3      1
3      C   8    6      2
4      D   9    5      4
5      E  25    8     NA

#remove 4th row
df[-c(4), ]

  player pts rebs blocks
1      A  17    3      1
2      B  12    3      1
3      C   8    6      2
5      E  25    8     NA

#remove 2nd through 4th row
df[-c(2:4), ]

  player pts rebs blocks
1      A  17    3      1
5      E  25    8     NA

#remove 1st, 2nd, and 4th row
df[-c(1, 2, 4), ]

  player pts rebs blocks
3      C   8    6      2
5      E  25    8     NA

Example 2: Remove Rows by Condition

The following code shows how to remove rows that don’t meet a specific condition:

#create data frame
df <- data.frame(player=c('A', 'B', 'C', 'D', 'E'),
                 pts=c(17, 12, 8, 9, 25),
                 rebs=c(3, 3, 6, 5, 8),
                 blocks=c(1, 1, 2, 4, NA))

#view data frame
df
  player pts rebs blocks
1      A  17    3      1
2      B  12    3      1
3      C   8    6      2
4      D   9    5      4
5      E  25    8     NA

#only keep rows where pts is less than 10 and rebs is less than 6
subset(df, pts<10 & rebs<6)

  player pts rebs blocks
4      D   9    5      4

Example 3: Remove Rows with NA Values

The following code shows how to remove rows with a NA value in any row:

#create data frame
df <- data.frame(player=c('A', 'B', 'C', 'D', 'E'),
                 pts=c(17, 12, 8, 9, 25),
                 rebs=c(3, 3, 6, 5, 8),
                 blocks=c(1, 1, 2, 4, NA))

#view data frame
df
  player pts rebs blocks
1      A  17    3      1
2      B  12    3      1
3      C   8    6      2
4      D   9    5      4
5      E  25    8     NA

#remove rows with NA value in any row:
na.omit(df)

  player pts rebs blocks
1      A  17    3      1
2      B  12    3      1
3      C   8    6      2
4      D   9    5      4