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
}));
}
public MatrisBase <object> Median(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int pop;
int nr = df.Row;
int nc = df.Col;
List <object> meds = new List <object>();
if (df is Dataframe dataframe)
{
for (int j = 0; j < nc; j++)
{
if (!dataframe.IsAllNumberColumn(j, 0))
{
if (numberOnly == 1)
{
List <object> col = new List <object>();
foreach (object o in dataframe.ColList(j, 0))
{
if (o is None ||
o is null ||
((!float.TryParse(o.ToString(), out float res) ||
float.IsNaN(res))))
{
continue;
}
col.Add(o);
}
if (col.Count == 0)
{
meds.Add(float.NaN);
continue;
}
pop = nr - df.AmountOfNanInColumn(j);
col.Sort();
meds.Add((pop % 2 == 1)
? (float)col[((pop + 1) / 2) - 1]
: ((float)col[(pop / 2) - 1] + (float)col[(int)Math.Round((decimal)(pop + 1) / 2, 0) - 1]) / 2);
}
else
{
meds.Add(float.NaN);
}
}
else
{
List <object> col = dataframe.ColList(j, 0);
col.Sort();
meds.Add((nr % 2 == 1)
? (float)col[((nr + 1) / 2) - 1]
: ((float)col[(nr / 2) - 1] + (float)col[(int)Math.Round((decimal)(nr + 1) / 2, 0) - 1]) / 2);
}
}
return(new Dataframe(new List <List <object> >()
{
meds
},
dataframe.Delimiter,
dataframe.NewLine,
null,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()),
null,
dataframe.GetColSettings().Copy()));
}
else
{
for (int j = 0; j < nc; j++)
{
if (numberOnly == 1)
{
List <object> col = new List <object>();
foreach (object o in df.ColList(j, 0))
{
if (o is None ||
o is null ||
((!float.TryParse(o.ToString(), out float res) ||
float.IsNaN(res))))
{
continue;
}
col.Add(o);
}
if (col.Count == 0)
{
meds.Add(float.NaN);
continue;
}
pop = nr - df.AmountOfNanInColumn(j);
col.Sort();
meds.Add((pop % 2 == 1)
? (float)col[((pop + 1) / 2) - 1]
: ((float)col[(pop / 2) - 1] + (float)col[(int)Math.Round((decimal)(pop + 1) / 2, 0) - 1]) / 2);
}
else
{
List <object> col = df.ColList(j, 0);
col.Sort();
meds.Add((nr % 2 == 1)
? (float)col[((nr + 1) / 2) - 1]
: (float)col[(nr / 2) - 1] + (float)col[(int)Math.Round((decimal)(nr + 1) / 2, 0) - 1]);
}
}
return(new MatrisBase <object>(new List <List <object> >()
{
meds
}));
}
}
public MatrisBase <object> SDev(MatrisBase <object> df,
int usePopulation = 0,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
if (usePopulation != 0 && usePopulation != 1)
{
throw new Exception(CompilerMessage.ARG_INVALID_VALUE("usePopulation", "Örneklem için 0, popülasyon için 1 olmalı!"));
}
int nr = df.Row;
int nc = df.Col;
if (nr == 1 && usePopulation == 1)
{
usePopulation = 0;
}
List <object> means = Mean(df).RowList(1);
List <object> sdevs = new List <object>();
List <List <object> > vals = df.GetValues();
int pop;
for (int j = 0; j < nc; j++)
{
float sdev = 0;
float mean = (float)means[j];
if (float.IsNaN(mean))
{
if (numberOnly == 1)
{
sdevs.Add(0);
}
else
{
sdevs.Add(float.NaN);
}
continue;
}
for (int i = 0; i < nr; i++)
{
if (float.TryParse(vals[i][j].ToString(), out float res))
{
if (numberOnly == 1 && float.IsNaN(res))
{
continue;
}
sdev += (float)Math.Pow(res - mean, 2);
}
else
{
if (numberOnly == 1)
{
continue;
}
else
{
sdev = float.NaN;
break;
}
}
}
pop = nr - usePopulation - (numberOnly == 1 ? df.AmountOfNanInColumn(j) : 0);
if (pop == 0)
{
sdevs.Add(0);
}
else
{
sdevs.Add((float)Math.Pow(sdev * (1.0 / pop), 0.5));
}
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
sdevs
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
sdevs
}));
}