# R - NA (Not Available)

NA (Not Available|Missing Values) is a logical constant.

See

````?NA`
```
``````> str(NA)
logi NA```
```

NA values have a class. There are integer NA, character NA, etc.

NA means “Not Available”.

NA is a logical constant of length 1 which contains a missing value indicator.

## Function

### is.na

• Is NA NA ?
``````> is.na(NA)
[1] TRUE```
```
• Where is NA ?
``````> v =  c(1, NA, 2)
> is.na(v)
[1] FALSE  TRUE FALSE```
```
``````> is.na(NaN)
[1] TRUE```
```

## Management

### analytics

````vapply(data.frame, function(x) mean(!is.na(x)), numeric(1))`
```

### remove

#### vector

``````v =  c(1, NA, 2)
> v[!is.na(v)]
[1] 1 2```
```

#### matrix

``````colA = c(1, 2, 3, 4, NA, 6)
colB = c(1, 2, NA, 4, 5, 6)
m=cbind(colA,colB)
m```
```
``````colA colB
[1,]    1    1
[2,]    2    2
[3,]    3   NA
[4,]    4    4
[5,]   NA    5
[6,]    6    6
```
```
``````rowWithoutNa = complete.cases(m)
rowWithoutNa```
```
``````[1]  TRUE  TRUE FALSE  TRUE FALSE  TRUE
```
```
````m[rowWithoutNa,]`
```
``````colA colB
[1,]    1    1
[2,]    2    2
[3,]    4    4
[4,]    6    6
```
```

### eliminate the row

to eliminate any row in the data frame that's got a missing value in it, there's a nice function called na.omit

````myDataFrame=na.omit(myDataFrame)`
```

### Count

in a variable

````with(dataFrame,sum(is.na(myVariableName)))`
```

### Create them

````myNaVector=rep(NA,10)`
```

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