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Signature Description Parameters 
template<hashable_equal ... Ts>
DataFrame<T, H>
duplication_mask(bool include_index,
                 bool binary = false) const;
This returns a new DataFrame with the same index column as self and an integer column with the same name for each column in self. The integer columns in returned DataFrame show a duplication mask for each column in self.

For example, if self has a column like:
   -----------------------------------------
  | aa | bb | cc | aa | dd | aa | bb | hh |
   -----------------------------------------
The returned DataFrame has a corresponding integer column with the same name
If binary is false:
   -----------------------------
  | 3 | 2 | 1 | 3 | 1 | 3 | 2 | 1 |
   -----------------------------
If binary is true:
   -----------------------------
  | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 0 |
   -----------------------------

NOTE: All column types must be hash-able and have == operator well defined
 Ts: List all the types of all data columns. A type should be specified in the list only once.
include_index: If true, it includes the index column to determine uniqueness
binary: If false, the returned integer columns contain the count of each item in the original column. If true, the returned integer columns contain 0's and 1's depending on if original items in the column had duplicates or not.
 
static void test_duplication_mask()  {

    std::cout << "\nTesting duplication_mask( ) ..." << std::endl;

    MyDataFrame                 df;
    StlVecType<unsigned long>  idxvec = { 1UL, 2UL, 3UL, 10UL, 5UL, 7UL, 8UL, 12UL, 9UL, 12UL, 10UL, 13UL, 10UL, 15UL, 14UL };
    StlVecType<double>         dblvec = { 0.0, 15.0, 14.0, 2.0, 15.0, 12.0, 11.0, 8.0, 7.0, 11.0, 5.0, 11.0, 3.0, 9.0, 15.0 };
    StlVecType<double>         dblvec2 = { 100.0, 101.0, 102.0, 103.0, 101.0, 105.0, 106.55, 107.34, 1.8, 111.0, 112.0, 113.0, 114.0, 115.0, 116.0 };
    StlVecType<int>            intvec = { 1, 2, 3, 4, 2, 8, 6, 7, 1 };
    StlVecType<std::string>    strvec = { "zz", "hh", "cc", "ww", "bb", "ff", "gg", "hh", "ii", "jj", "kk", "ll", "mm", "ww", "oo" };

    df.load_data(std::move(idxvec),
                 std::make_pair("dbl_col", dblvec),
                 std::make_pair("dbl_col_2", dblvec2),
                 std::make_pair("str_col", strvec));
    df.load_column("int_col",
                   std::move(intvec),
                   nan_policy::dont_pad_with_nans);

    const auto  df2 = df.duplication_mask<double, int, std::string>(false);

    {
        StlVecType<unsigned long>   res_idx = { 1, 2, 3, 10, 5, 7, 8, 12, 9, 12, 10, 13, 10, 15, 14 };
        StlVecType<int>             res_dbl_col = { 1, 3, 1, 1, 3, 1, 3, 1, 1, 3, 1, 3, 1, 1, 3 };
        StlVecType<int>             res_dbl_col_2 = { 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
        StlVecType<int>             res_str_col = { 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1 };
        StlVecType<int>             res_int_col = { 2, 2, 1, 1, 2, 1, 1, 1, 2 };

        assert(df2.get_index() == res_idx);
        assert(df2.get_column<int>("dbl_col") == res_dbl_col);
        assert(df2.get_column<int>("dbl_col_2") == res_dbl_col_2);
        assert(df2.get_column<int>("str_col") == res_str_col);
        assert(df2.get_column<int>("int_col") == res_int_col);
    }

    const auto  df3 = df.duplication_mask<double, int, std::string>(true);

    {
        StlVecType<unsigned long>   res_idx = { 1, 2, 3, 10, 5, 7, 8, 12, 9, 12, 10, 13, 10, 15, 14 };
        StlVecType<int>             res_dbl_col = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
        StlVecType<int>             res_dbl_col_2 = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
        StlVecType<int>             res_str_col = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
        StlVecType<int>             res_int_col = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };

        assert(df3.get_index() == res_idx);
        assert(df3.get_column<int>("dbl_col") == res_dbl_col);
        assert(df3.get_column<int>("dbl_col_2") == res_dbl_col_2);
        assert(df3.get_column<int>("str_col") == res_str_col);
        assert(df3.get_column<int>("int_col") == res_int_col);
    }

    const auto  df4 =
        df.duplication_mask<double, int, std::string>(false, true);

    {
        StlVecType<unsigned long>   res_idx = { 1, 2, 3, 10, 5, 7, 8, 12, 9, 12, 10, 13, 10, 15, 14 };
        StlVecType<int>             res_dbl_col = { 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1 };
        StlVecType<int>             res_dbl_col_2 = { 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
        StlVecType<int>             res_str_col = { 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0 };
        StlVecType<int>             res_int_col = { 1, 1, 0, 0, 1, 0, 0, 0, 1 };

        assert(df4.get_index() == res_idx);
        assert(df4.get_column<int>("dbl_col") == res_dbl_col);
        assert(df4.get_column<int>("dbl_col_2") == res_dbl_col_2);
        assert(df4.get_column<int>("str_col") == res_str_col);
        assert(df4.get_column<int>("int_col") == res_int_col);
    }
}

C++ DataFrame