I transformed my data into a boxplot (used geom_boxplot of ggplot), so that the outliers got visible. Afterwards I wanted to remove them from my data. That is why I used "ggplot_build" to get on all the informations of the plot and saved it with a new name.

```
Outlier_boxplot<-ggplot_build(boxplot)
```

Now it was possible to extract the column with the outliers. In the next step I used the function "subset" to select only the values of my data.frame, which are not equal to the extracted outliers.

```
Without_Outlier_dF<-subset(round(dF[1],digits=3),Test !=c(round(Outlier_boxplot$data[[1]]$outliers[[4]],digits=3))))
```

That worked out well for nearly all cases. The problem is, that sometimes values (even so they look the same) are not left out.

Extract of values data.frame:

```
-234,347 75,764 93,34 95,237 99,005 100,044 97,924 98,875 98,072 99,569 98,848 98,414 99,33 96,901 99,29 100,359 99,169 97,828 97,146 97,229 94,278 97,146 97,229 94,278
```

Outliers

```
-234.347 75.764 93.340 94.278
```

Results: Outliers removed except for the value 94,278

```
95,237 99,005 100,044 97,924 98,875 98,072 99,569 98,848 98,414 99,33 96,901 99,29 100,359 99,169 97,828 97,146 97,229 94,278
```

I already tried to round all values (as you can see) but it didn't help. Do you have any ideas?

Answer:

`geom_boxplot`

calls `boxplot.stats`

to calculate the positions of the upper and lower whiskers. You can do it too:

```
> boxplot.stats(v)
$stats
[1] 93.340 96.069 97.876 99.087 100.359
$n
[1] 24
$conf
[1] 96.90265 98.84935
$out
[1] -234.347 75.764
```

(`v`

is assumed to be your input data vector):

From the `boxplot.stats`

documentation:

stats a vector of length 5, containing the extreme of the lower whisker, the lower ‘hinge’, the median, the upper ‘hinge’ and the extreme of the upper whisker.

n the number of non-NA observations in the sample.

conf the lower and upper extremes of the ‘notch’ (if(do.conf)). See the details.

out the values of any data points which lie beyond the extremes of the whiskers (if(do.out)).

I guess it contains all the data you might need for further analysis.

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