The R Book

Omitting Rows Containing Missing Values, NA

In statistical modelling it is often useful to have a dataframe that contains no missing values in the response or explanatory variables. You can create a shorter dataframe using the na.omit function. Here is a sister dataframe of worms in which certain values are NA:

data<-read.table("c:\\temp\\worms.missing.txt",header=T)
data

           Field.Name  Area  Slope  Vegetation  Soil.pH   Damp  Worm.density
1         Nashs.Field   3.6     11   Grassland      4.1  FALSE             4
2      Silwood.Bottom   5.1     NA      Arable      5.2  FALSE             7
3       Nursery.Field   2.8      3   Grassland      4.3  FALSE             2
4         Rush.Meadow   2.4      5      Meadow      4.9   TRUE             5
5     Gunness.Thicket   3.8      0       Scrub      4.2  FALSE             6
6            Oak.Mead   3.1      2   Grassland      3.9  FALSE             2
7        Church.Field   3.5      3   Grassland       NA     NA            NA
8             Ashurst   2.1      0      Arable      4.8  FALSE             4
9         The.Orchard   1.9      0     Orchard      5.7  FALSE             9
10      Rookery.Slope   1.5      4   Grassland      5.0   TRUE             7
11        Garden.Wood   2.9     10       Scrub      5.2  FALSE             8
12       North.Gravel   3.3      1   Grassland      4.1  FALSE             1
13       South.Gravel   3.7      2   Grassland      4.0  FALSE             2
14  Observatory.Ridge   1.8      6   Grassland      3.8  FALSE             0
15         Pond.Field   4.1      0      Meadow      5.0   TRUE             6
16       Water.Meadow   3.9      0      Meadow      4.9   TRUE             8
17          Cheapside   2.2      8       Scrub      4.7   TRUE             4
18         Pound.Hill   4.4      2      Arable      4.5  FALSE             5
19         Gravel.Pit    NA      1   Grassland      3.5  FALSE             1
20          Farm.Wood   0.8     10       Scrub      5.1   TRUE             3

By inspection we can see that we should like to leave out row 2 (one missing value), row 7 (three missing values) and row 19 (one missing value). This could not be simpler:

na.omit(data) Field.Name Area Slope Vegetation Soil.pH Damp Worm.density 1 Nashs.Field ...