# How to Use rowMeans() Function in R

The rowMeans() function in R can be used to calculate the mean of several rows of a matrix or data frame in R.

This function uses the following basic syntax:

```#calculate row means of every column
rowMeans(df)

#calculate row means and exclude NA values
rowMeans(df, na.rm=T)

#calculate row means of specific rows
rowMeans(df[1:3, ])```

The following examples show how to use this syntax in practice.

### Example 1: Calculate Mean of Every Row

The following code shows how to calculate the mean of every row in a data frame:

```#create data frame
df <- data.frame(points=c(99, 91, 86, 88, 95),
assists=c(33, 28, 31, 39, 34),
rebounds=c(30, 28, 24, 24, 28),
blocks=c(1, 4, 11, 0, 2))

#view data frame
df

points assists rebounds blocks
1     99      33       30      1
2     91      28       28      4
3     86      31       24     11
4     88      39       24      0
5     95      34       28      2

#calculate row means
rowMeans(df)

[1] 40.75 37.75 38.00 37.75 39.75```

Here’s how to interpret the output:

• The mean of values in the first row is 40.75.
• The mean of values in the second row is 37.75.

And so on.

### Example 2: Calculate Mean of Every Row & Exclude NA’s

The following code shows how to calculate the mean of every row and exclude NA values:

```#create data frame with some NA values
df <- data.frame(points=c(99, 91, 86, 88, 95),
assists=c(33, NA, 31, 39, 34),
rebounds=c(30, 28, NA, NA, 28),
blocks=c(1, 4, 11, 0, 2))

#view data frame
df

points assists rebounds blocks
1     99      33       30      1
2     91      NA       28      4
3     86      31       NA     11
4     88      39       NA      0
5     95      34       28      2

#calculate row means
rowMeans(df, na.rm=T)

[1] 40.75000 41.00000 42.66667 42.33333 39.75000
```

### Example 3: Calculate Mean of Specific Rows

The following code shows how to calculate the mean values of specific rows in the data frame:

```#create data frame
df <- data.frame(points=c(99, 91, 86, 88, 95),
assists=c(33, 28, 31, 39, 34),
rebounds=c(30, 28, 24, 24, 28),
blocks=c(1, 4, 11, 0, 2))

#calculate row means for first three rows only
rowMeans(df[1:3, ])

1     2     3
40.75 37.75 38.00  ```

We can also use the c() syntax to select specific rows:

```#calculate row means for rows 1, 4, and 5
rowMeans(df[c(1, 4, 5), ])

1     4     5
40.75 37.75 39.75  ```