Hello,

It is about the application of the *skewness* function. But I admit that I am not (yet) a Julia expert. But to my question:

I have a DataFrame *Rotwein* and when I make the following function call …

```
julia> StatsBase.skewness(Rotwein[:residual_sugar])
```

… I get the following error message:

```
julia> StatsBase.skewness(Rotwein[:residual_sugar])
ERROR: MethodError: no method matching skewness(::Array{Union{Missing, Float64},1})
Closest candidates are:
skewness(::Distributions.DiscreteUniform) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\univariate\discrete\discreteuniform.jl:58
skewness(::Distributions.Hypergeometric) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\univariate\discrete\hypergeometric.jl:61
skewness(::Distributions.EmpiricalUnivariateDistribution) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\empirical.jl:46
...
```

Okay, doesn’t seem to work with the DataFrame type. Now I convert this vector of the DataFrame into the vector M1:

```
julia> M1
1599-element Array{Union{Missing, Float64},1}:
7.4
7.8
7.8
11.2
7.4
7.4
7.9
7.3
7.8
7.5
⋮
6.3
5.4
6.3
6.8
6.2
5.9
6.3
5.9
6.0
```

and then call the function again:

```
julia> StatsBase.skewness(M1)
ERROR: MethodError: no method matching skewness(::Array{Union{Missing, Float64},1})
Closest candidates are:
skewness(::Distributions.DiscreteUniform) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\univariate\discrete\discreteuniform.jl:58
skewness(::Distributions.Hypergeometric) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\univariate\discrete\hypergeometric.jl:61
skewness(::Distributions.EmpiricalUnivariateDistribution) at C:\Users\guent\.juliapro\packages\Distributions\WHjOk\src\empirical.jl:46
```

And get the same error message. I don’t understand, what’s wrong? Isn’t it enough if I simply pass a vector like in R?

```
> library(e1071)
> skewness(Rotwein$residual.sugar)
[1] 4.53214
```

Does anyone have a clue for me?

Thank you,

Guenter