GenericScalar
=============

.. cpp:class:: pandas::GenericScalar

   pandas C++ class.

Example
-------

.. code-block:: cpp

   #include <pandas/pandas.h>
   using namespace pandas;

   // Use GenericScalar
   GenericScalar obj;
   // ... operations ...

Construction
------------

.. list-table::
   :widths: 40 20 15 25
   :header-rows: 1

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static GenericScalar from_bool(bool v)``
     - static GenericScalar
     - pd_generic_array_formatter.h:63
     - 
   * - ``static GenericScalar from_string(std::string s)``
     - static GenericScalar
     - pd_generic_array_formatter.h:66
     - :ref:`View <example-genericscalar-from_string-0>`

Other Methods
-------------

.. list-table::
   :widths: 40 20 15 25
   :header-rows: 1

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static GenericScalar na()``
     - static GenericScalar
     - pd_generic_array_formatter.h:60
     - :ref:`View <example-genericscalar-na-1>`
   * - ``static GenericScalar nan()``
     - static GenericScalar
     - pd_generic_array_formatter.h:62
     - :ref:`View <example-genericscalar-nan-2>`
   * - ``static GenericScalar nat()``
     - static GenericScalar
     - pd_generic_array_formatter.h:61
     - :ref:`View <example-genericscalar-nat-3>`
   * - ``static GenericScalar none()``
     - static GenericScalar
     - pd_generic_array_formatter.h:59
     - :ref:`View <example-genericscalar-none-4>`


Code Examples
-------------

The following examples are extracted from the test suite.

.. _example-genericscalar-from_string-0:

.. dropdown:: from_string (pd_test_3_all.cpp:10837)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10827
      :emphasize-lines: 11

          const auto& s1 = df.column<int64_t>("A");
          const auto& s2 = df.col<int64_t>("A");
          if (s1.size() != s2.size() || s1[0] != s2[0]) {
              std::cout << "  [FAIL] : in pd_test_3_all_column_alias() : mismatch" << std::endl;
              throw std::runtime_error("pd_test_3_all_column_alias failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_timedelta_from_string() {
          std::cout << "========= Timedelta::from_string() ======================";
          auto td1 = pandas::Timedelta::from_string("1 days");
          pandas::Timedelta td2("1 days");
          if (td1.value() != td2.value()) {
              std::cout << "  [FAIL] : in pd_test_3_all_timedelta_from_string() : mismatch" << std::endl;
              throw std::runtime_error("pd_test_3_all_timedelta_from_string failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_replace_int() {

.. _example-genericscalar-na-1:

.. dropdown:: na (pd_test_1_all.cpp:84)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 74
      :emphasize-lines: 11

          void pd_test_boolean_array_kleene_and() {
              std::cout << "========= BooleanArray: Kleene AND ======================= ";
      
              // Kleene AND truth table:
              // T & T = T, T & F = F, T & NA = NA
              // F & T = F, F & F = F, F & NA = F (False dominates)
              // NA & T = NA, NA & F = F, NA & NA = NA
      
              pandas::BooleanArray t({std::optional<bool>(true)});
              pandas::BooleanArray f({std::optional<bool>(false)});
              pandas::BooleanArray na({std::nullopt});
      
              // T & T = T
              auto tt = (t & t);
              if (!tt[0].has_value() || !tt[0].value()) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_kleene_and() : T & T should be T" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_kleene_and failed: T & T");
              }
      
              // T & F = F
              auto tf = (t & f);

.. _example-genericscalar-nan-2:

.. dropdown:: nan (pd_test_1_all.cpp:1556)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1546
      :emphasize-lines: 11

      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_floating_array_nan_conversion() {
              std::cout << "========= FloatingArray: NaN to NA conversion ======================= ";
      
              // NaN values should be automatically converted to NA
              pandas::FloatingArray<double> arr({
                  std::optional<double>(1.0),
                  std::optional<double>(std::nan("")),  // NaN
                  std::optional<double>(3.0)
              });
      
              if (!arr.is_na(1)) {
                  std::cout << "  [FAIL] : in pd_test_floating_array_nan_conversion() : NaN should be converted to NA" << std::endl;
                  throw std::runtime_error("pd_test_floating_array_nan_conversion failed: NaN should be NA");
              }
      
              if (arr.is_na(0) || arr.is_na(2)) {
                  std::cout << "  [FAIL] : in pd_test_floating_array_nan_conversion() : non-NaN should not be NA" << std::endl;

.. _example-genericscalar-nat-3:

.. dropdown:: nat (pd_test_5_all.cpp:97717)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 97707
      :emphasize-lines: 11

          std::string result_override;
          std::string variant_label;
      };
      
      static pandas::FillValue fv_none()         { return pandas::FillValue::none(); }
      
      static pandas::FillValue fv_nan()          { return pandas::FillValue::nan(); }
      
      static pandas::FillValue fv_na()           { return pandas::FillValue::na(); }
      
      static pandas::FillValue fv_nat()          { return pandas::FillValue::nat(); }
      
      static pandas::FillValue fv_bool_false()   { return pandas::FillValue::of_bool(false); }
      
      static pandas::FillValue fv_num_zero()     { return pandas::FillValue::of_numeric(0.0); }
      
      static pandas::FillValue fv_string_x()     { return pandas::FillValue::of_string("x"); }
      
      static Probe probe_result(pandas::Result& r) {
          Probe p;
          std::visit([&](auto& alt) {

.. _example-genericscalar-none-4:

.. dropdown:: none (pd_test_5_all.cpp:90413)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 90403
      :emphasize-lines: 11

                                          pandas::FillValue::of_bool(true));
              (void)r;
          }, local_fail);
      }
      
      static void f_20_847312_dispatch_complex_none(int& local_fail) {
          std::cout << "-- f_20_847312_dispatch_complex_none\n";
          expect_value_error_duplicate("c12_dispatch_complex_none", [] {
              auto s = make_series<cplx>({{1, 2}, {3, 4}, {5, 6}}, {"c1", "c1", "c2"});
              auto r = s.reindex_dispatch({"c1", "c2", "c3"}, "",
                                          pandas::FillValue::none());
              (void)r;
          }, local_fail);
      }
      
      static void f_20_847313_df_dup_rows_axis0(int& local_fail) {
          std::cout << "-- f_20_847313_df_dup_rows_axis0\n";
          expect_value_error_duplicate("c13_df_dup_rows_axis0", [] {
              std::vector<pandas::Series<std::int64_t>> cols;
              cols.emplace_back(std::vector<std::int64_t>{10, 20, 30});
              cols.emplace_back(std::vector<std::int64_t>{40, 50, 60});