// IntColByIdx returns the slice of IntVals for the indexed column. The error
// is non-nil if there is a problem (no such column or it's not an int
// column)
IntColByIdx returns the slice of IntVals for the indexed column. The error
is non-nil if there is a problem (no such column or it's not an int
column)
// IntColByIdx returns the slice of IntVals for the indexed column . The error // is non - nil if there is a problem ( no such column or it ' s not an int // column )
func (df DF) IntColByIdx(i int) ([]IntVal, error) {
	if i < 0 || i >= len(df.mci.info) {
		return nil, dfErrorf("There is no column %d (valid range: 0-%d)",
			i, len(df.mci.info)-1)
	}
	ci := df.mci.info[i]
	if err := assertTypeByIdx(ci.colType, ColTypeInt, i); err != nil {
		return nil, err
	}
	return df.intCols[df.mci.valIdx[i]], nil
}
func ( df DF ) IntColByIdx ( i int ) ( [ ] IntVal , error ) { if i < 0 || i >= len ( df . mci . info ) { return nil , dfErrorf ( " " , i , len ( df . mci . info ) - 1 ) } ci := df . mci . info [ i ] if err := assertTypeByIdx ( ci . colType , ColTypeInt , i ) ; err != nil { return nil , err } return df . intCols [ df . mci . valIdx [ i ] ] , nil }
IntColByIdx returns the slice of IntVals for the indexed column.
IntColByIdx returns the slice of IntVals for the indexed column .