BoolColumnRefNode
=================

.. cpp:class:: pandas::BoolColumnRefNode

   pandas C++ class.

Example
-------

.. code-block:: cpp

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

   // Use BoolColumnRefNode
   BoolColumnRefNode obj;
   // ... operations ...

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``explicit BoolColumnRefNode(std::string col) : column(std::move(col))``
     - explicit BoolColumnRefNode(std::string col) :
     - pd_query.h:358
     - :ref:`View <example-boolcolumnrefnode-column-0>`
   * - ``NodeType type() const override``
     - NodeType
     - pd_query.h:357
     - :ref:`View <example-boolcolumnrefnode-type-1>`


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

The following examples are extracted from the test suite.

.. _example-boolcolumnrefnode-column-0:

.. dropdown:: column (pd_test_1_all.cpp:22039)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 22029
      :emphasize-lines: 11

                  std::string a1 = result.iat<double>(1, col_a_idx) == -1.0 ? "ok" : "fail";
                  std::string a2 = result.iat<double>(2, col_a_idx) == 3.0 ? "ok" : "fail";
                  std::string a3 = result.iat<double>(3, col_a_idx) == 4.0 ? "ok" : "fail";
      
                  if (a0 != "ok" || a1 != "ok" || a2 != "ok" || a3 != "ok") {
                      passed = false;
                      error_msg = "Column A values incorrect: A[0]=" + a0 + ", A[1]=" + a1 +
                                  ", A[2]=" + a2 + ", A[3]=" + a3;
                  }
      
                  // Check B column (all should be original)
                  double b0 = result.iat<double>(0, col_b_idx);
                  if (b0 != 5.0) {
                      passed = false;
                      error_msg = "B[0] should be 5, got " + std::to_string(b0);
                  }
      
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_where_basic() : " << error_msg << std::endl;
                      throw std::runtime_error("pd_test_where_basic failed: " + error_msg);
                  }

.. _example-boolcolumnrefnode-type-1:

.. dropdown:: type (pd_test_3_all.cpp:15450)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15440
      :emphasize-lines: 11

      /**
       * Test Series.convert_dtypes() parameter flags
       */
      void pd_test_series_convert_dtypes_flags() {
          std::cout << "========= Series.convert_dtypes() flags =================";
      
          // Test convert_integer=false - with floats disabled too, so it becomes string/object
          pandas::Series<std::string> s({"1", "2", "3"}, "numbers");
          auto converted = s.convert_dtypes(true, true, false, true, false);  // convert_integer=false, convert_floating=false
      
          // Should remain object type (Series<std::string> has dtype_name()="object")
          // When integer and floating are both disabled for integer-like strings, it falls back to string type
          if (converted->dtype_name() != "object") {
              std::cout << "  [FAIL] : dtype should be object when convert_integer=false and convert_floating=false, got " << converted->dtype_name() << std::endl;
              throw std::runtime_error("pd_test_series_convert_dtypes_flags failed: convert_integer");
          }
      
          // Test convert_boolean=false - strings stay as object/string type
          pandas::Series<std::string> s_bool({"true", "false"}, "bools");
          auto converted_bool = s_bool.convert_dtypes(true, true, true, false, true);  // convert_boolean=false