public MatrisBase <object> Sum(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nc = df.Col;
int nr = df.Row;
List <object> sums = new List <object>();
for (int c = 0; c < nc; c++)
{
sums.Add(ArrayMethods.ArraySum(df.ColList(c, 0), 0, nr, numberOnly) ?? float.NaN);
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
sums
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
sums
}));
}
public MatrisBase <object> Mean(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nc = df.Col;
int nr = df.Row;
List <object> means = new List <object>();
int pop;
for (int c = 0; c < nc; c++)
{
pop = nr - (numberOnly == 1 ? df.AmountOfNanInColumn(c) : 0);
object res = ArrayMethods.ArraySum(df.ColList(c, 0), 0, nr, numberOnly) ?? float.NaN;
if (pop == 0)
{
means.Add(float.NaN);
}
else
{
means.Add(float.IsNaN((float)res) ? res : (float)res / pop);
}
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
means
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
means
}));
}