BooleanMask
===========

.. cpp:class:: pandas::BooleanMask

   pandas C++ class.

Example
-------

.. code-block:: cpp

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

   // Use BooleanMask
   BooleanMask obj;
   // ... operations ...

Constructors
------------

.. list-table::
   :widths: 55 25 20
   :header-rows: 1

   * - Signature
     - Location
     - Example
   * - ``BooleanMask() = default``
     - pd_boolean_mask.h:32
     - :ref:`View <example-booleanmask-booleanmask-0>`
   * - ``explicit BooleanMask(std::vector<bool> d)``
     - pd_boolean_mask.h:34
     - :ref:`View <example-booleanmask-booleanmask-1>`
   * - ``BooleanMask(std::vector<bool> d, std::vector<bool> na)``
     - pd_boolean_mask.h:50
     - :ref:`View <example-booleanmask-booleanmask-2>`
   * - ``explicit BooleanMask(const BooleanArray& ba)``
     - pd_boolean_mask.h:57
     - :ref:`View <example-booleanmask-booleanmask-3>`

Missing Data
------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``BooleanMask fillna(bool value) const``
     - BooleanMask
     - pd_boolean_mask.h:141
     - :ref:`View <example-booleanmask-fillna-4>`

Statistics
----------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``int64_t sum() const``
     - int64_t
     - pd_boolean_mask.h:151
     - :ref:`View <example-booleanmask-sum-5>`

I/O
---

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``std::string to_string() const``
     - std::string
     - pd_boolean_mask.h:196
     - :ref:`View <example-booleanmask-to_string-6>`

Type Checking
-------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool is_na(size_t i) const { return boolean_data.is_na(i)``
     - bool
     - pd_boolean_mask.h:67
     - :ref:`View <example-booleanmask-is_na-7>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool all() const``
     - bool
     - pd_boolean_mask.h:156
     - :ref:`View <example-booleanmask-all-8>`
   * - ``bool any() const``
     - bool
     - pd_boolean_mask.h:161
     - :ref:`View <example-booleanmask-any-9>`
   * - ``bool data_at(size_t i) const``
     - bool
     - pd_boolean_mask.h:170
     - :ref:`View <example-booleanmask-data_at-10>`
   * - ``std::vector<bool> data_vector() const``
     - std::vector<bool>
     - pd_boolean_mask.h:175
     - :ref:`View <example-booleanmask-data_vector-11>`
   * - ``bool has_na() const { return boolean_data.has_na()``
     - bool
     - pd_boolean_mask.h:66
     - :ref:`View <example-booleanmask-has_na-12>`
   * - ``std::vector<bool> na_mask_vector() const``
     - std::vector<bool>
     - pd_boolean_mask.h:184
     - :ref:`View <example-booleanmask-na_mask_vector-13>`
   * - ``BooleanMask result(boolean_data & other.boolean_data)``
     - BooleanMask
     - pd_boolean_mask.h:74
     - :ref:`View <example-booleanmask-result-14>`
   * - ``BooleanMask result(boolean_data \| other.boolean_data)``
     - BooleanMask
     - pd_boolean_mask.h:84
     - :ref:`View <example-booleanmask-result-15>`
   * - ``BooleanMask result(~boolean_data)``
     - BooleanMask
     - pd_boolean_mask.h:94
     - :ref:`View <example-booleanmask-result-16>`
   * - ``BooleanMask result(boolean_data ^ other.boolean_data)``
     - BooleanMask
     - pd_boolean_mask.h:104
     - :ref:`View <example-booleanmask-result-17>`
   * - ``BooleanMask result(boolean_data & scalar)``
     - BooleanMask
     - pd_boolean_mask.h:118
     - :ref:`View <example-booleanmask-result-18>`
   * - ``BooleanMask result(boolean_data \| scalar)``
     - BooleanMask
     - pd_boolean_mask.h:128
     - :ref:`View <example-booleanmask-result-19>`
   * - ``BooleanMask result(boolean_data.fillna(value))``
     - BooleanMask
     - pd_boolean_mask.h:142
     - :ref:`View <example-booleanmask-result-20>`
   * - ``size_t size() const { return boolean_data.size()``
     - size_t
     - pd_boolean_mask.h:65
     - :ref:`View <example-booleanmask-size-21>`
   * - ``std::vector<std::optional<bool>> vals(d.size())``
     - std::vector<std::optional<bool>>
     - pd_boolean_mask.h:35
     - :ref:`View <example-booleanmask-vals-22>`
   * - ``std::vector<std::optional<bool>> vals(d.size())``
     - std::vector<std::optional<bool>>
     - pd_boolean_mask.h:44
     - :ref:`View <example-booleanmask-vals-23>`
   * - ``std::vector<std::optional<bool>> vals(d.size())``
     - std::vector<std::optional<bool>>
     - pd_boolean_mask.h:51
     - :ref:`View <example-booleanmask-vals-24>`


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

The following examples are extracted from the test suite.

.. _example-booleanmask-booleanmask-0:

.. dropdown:: BooleanMask (pd_test_5_all.cpp:92531)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 92521
      :emphasize-lines: 11

          return pandas::Series<std::int64_t>({10, 20, 30, 40, 50},
                                              std::string("i5"));
      }
      
      static pandas::Series<std::string> make_str_series_5() {
          return pandas::Series<std::string>({"a", "b", "c", "d", "e"},
                                             std::string("s5"));
      }
      
      static pandas::BooleanMask make_mask_TFTFT() {
          return pandas::BooleanMask(std::vector<bool>{true, false, true, false,
                                                       true});
      }
      
      static pandas::BooleanMask make_mask_all_false() {
          return pandas::BooleanMask(std::vector<bool>{false, false, false, false,
                                                       false});
      }
      
      static pandas::BooleanMask make_mask_all_true() {
          return pandas::BooleanMask(std::vector<bool>{true, true, true, true,

.. _example-booleanmask-booleanmask-1:

.. dropdown:: BooleanMask (pd_test_5_all.cpp:92531)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 92521
      :emphasize-lines: 11

          return pandas::Series<std::int64_t>({10, 20, 30, 40, 50},
                                              std::string("i5"));
      }
      
      static pandas::Series<std::string> make_str_series_5() {
          return pandas::Series<std::string>({"a", "b", "c", "d", "e"},
                                             std::string("s5"));
      }
      
      static pandas::BooleanMask make_mask_TFTFT() {
          return pandas::BooleanMask(std::vector<bool>{true, false, true, false,
                                                       true});
      }
      
      static pandas::BooleanMask make_mask_all_false() {
          return pandas::BooleanMask(std::vector<bool>{false, false, false, false,
                                                       false});
      }
      
      static pandas::BooleanMask make_mask_all_true() {
          return pandas::BooleanMask(std::vector<bool>{true, true, true, true,

.. _example-booleanmask-booleanmask-2:

.. dropdown:: BooleanMask (pd_test_5_all.cpp:92531)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 92521
      :emphasize-lines: 11

          return pandas::Series<std::int64_t>({10, 20, 30, 40, 50},
                                              std::string("i5"));
      }
      
      static pandas::Series<std::string> make_str_series_5() {
          return pandas::Series<std::string>({"a", "b", "c", "d", "e"},
                                             std::string("s5"));
      }
      
      static pandas::BooleanMask make_mask_TFTFT() {
          return pandas::BooleanMask(std::vector<bool>{true, false, true, false,
                                                       true});
      }
      
      static pandas::BooleanMask make_mask_all_false() {
          return pandas::BooleanMask(std::vector<bool>{false, false, false, false,
                                                       false});
      }
      
      static pandas::BooleanMask make_mask_all_true() {
          return pandas::BooleanMask(std::vector<bool>{true, true, true, true,

.. _example-booleanmask-booleanmask-3:

.. dropdown:: BooleanMask (pd_test_5_all.cpp:92531)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 92521
      :emphasize-lines: 11

          return pandas::Series<std::int64_t>({10, 20, 30, 40, 50},
                                              std::string("i5"));
      }
      
      static pandas::Series<std::string> make_str_series_5() {
          return pandas::Series<std::string>({"a", "b", "c", "d", "e"},
                                             std::string("s5"));
      }
      
      static pandas::BooleanMask make_mask_TFTFT() {
          return pandas::BooleanMask(std::vector<bool>{true, false, true, false,
                                                       true});
      }
      
      static pandas::BooleanMask make_mask_all_false() {
          return pandas::BooleanMask(std::vector<bool>{false, false, false, false,
                                                       false});
      }
      
      static pandas::BooleanMask make_mask_all_true() {
          return pandas::BooleanMask(std::vector<bool>{true, true, true, true,

.. _example-booleanmask-fillna-4:

.. dropdown:: fillna (pd_test_1_all.cpp:537)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 527
      :emphasize-lines: 11

                  throw std::runtime_error("pd_test_categorical_array_na_handling failed: isna size != 4");
              }
      
              // Test dropna
              pandas::CategoricalArray dropped = arr.dropna();
              if (dropped.size() != 2) {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_na_handling() : dropna size != 2" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_na_handling failed: dropna size != 2");
              }
      
              // Test fillna (fill with existing category)
              pandas::CategoricalArray filled = arr.fillna("a");  // 'a' is in categories
              if (filled.has_na()) {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_na_handling() : fillna should have no NA" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_na_handling failed: fillna should have no NA");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_categorical_array_add_categories() {

.. _example-booleanmask-sum-5:

.. dropdown:: sum (pd_test_1_all.cpp:276)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 266
      :emphasize-lines: 11

              }
      
              // Test sum/mean
              pandas::BooleanArray arr({
                  std::optional<bool>(true),
                  std::optional<bool>(false),
                  std::optional<bool>(true),
                  std::optional<bool>(true)
              });
      
              auto s = arr.sum();
              if (!s.has_value() || s.value() != 3) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : sum should be 3" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_reductions failed: sum");
              }
      
              auto m = arr.mean();
              if (!m.has_value() || std::abs(m.value() - 0.75) > 0.001) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : mean should be 0.75" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_reductions failed: mean");
              }

.. _example-booleanmask-to_string-6:

.. dropdown:: to_string (pd_test_1_all.cpp:2693)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2683
      :emphasize-lines: 11

              pandas::PeriodArray arr_m(std::vector<std::string>{
                  "2020-01",
                  "NaT",
                  "2025-06"
              }, "M");
      
              // Year
              auto years = arr_m.year();
              auto y0 = years[0];
              if (!y0.has_value() || y0.value() != 2020) {
                  std::cout << "  [FAIL] : year[0] should be 2020, got " << (y0.has_value() ? std::to_string(y0.value()) : "NA") << std::endl;
                  throw std::runtime_error("pd_test_period_array_year_month_quarter failed: year[0]");
              }
      
              auto y1 = years[1];
              if (y1.has_value()) {
                  std::cout << "  [FAIL] : year[1] should be NA (NaT)" << std::endl;
                  throw std::runtime_error("pd_test_period_array_year_month_quarter failed: year[1] should be NA");
              }
      
              auto y2 = years[2];

.. _example-booleanmask-is_na-7:

.. dropdown:: is_na (pd_test_1_all.cpp:51)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 41
      :emphasize-lines: 11

      
          void pd_test_boolean_array_na_handling() {
              std::cout << "========= BooleanArray: NA handling ======================= ";
      
              pandas::BooleanArray arr({
                  std::optional<bool>(true),
                  std::nullopt,  // NA at index 1
                  std::optional<bool>(false)
              });
      
              if (!arr.is_na(1)) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : is_na(1) should be true" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: is_na(1) should be true");
              }
      
              if (arr.is_na(0)) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : is_na(0) should be false" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: is_na(0) should be false");
              }
      
              if (!arr.has_na()) {

.. _example-booleanmask-all-8:

.. dropdown:: all (pd_test_1_all.cpp:247)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 237
      :emphasize-lines: 11

              pandas::BooleanArray has_true({
                  std::optional<bool>(false),
                  std::optional<bool>(true)
              });
              any_result = has_true.any();
              if (!any_result.has_value() || !any_result.value()) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : any() with True" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_reductions failed: any() with True");
              }
      
              // Test all()
              pandas::BooleanArray all_true({
                  std::optional<bool>(true),
                  std::optional<bool>(true)
              });
              auto all_result = all_true.all();
              if (!all_result.has_value() || !all_result.value()) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : all() of all True" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_reductions failed: all() all True");
              }
      

.. _example-booleanmask-any-9:

.. dropdown:: any (pd_test_1_all.cpp:226)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 216
      :emphasize-lines: 11

                  std::cout << "  [FAIL] : in pd_test_boolean_array_kleene_not() : ~NA should be NA" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_kleene_not failed: ~NA");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_boolean_array_reductions() {
              std::cout << "========= BooleanArray: reductions ======================= ";
      
              // Test any()
              pandas::BooleanArray all_false({
                  std::optional<bool>(false),
                  std::optional<bool>(false)
              });
              auto any_result = all_false.any();
              if (!any_result.has_value() || any_result.value()) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : any() of all False" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_reductions failed: any() all False");
              }
      

.. _example-booleanmask-data_at-10:

.. dropdown:: data_at (pd_test_3_all.cpp:24087)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24077
      :emphasize-lines: 11

      // ------------------- pd_test_agg_to_series.cpp (end) ---------------------------
      
      // ------------------- pd_test_df_boolean_mask_core.cpp (begin) --------------------
      namespace dataframe_tests_df_boolean_mask_core {
      
      void test_boolean_mask_construct_data() {
          std::cout << "========= BooleanMask construct from vector<bool> ====== ";
          std::vector<bool> d1 = {true, false, true};
          pandas::BooleanMask m(d1);
          assert(m.size() == 3);
          assert(m.data_at(0) == true);
          assert(m.data_at(1) == false);
          assert(m.data_at(2) == true);
          auto dv = m.data_vector();
          assert(dv.size() == 3);
          assert(dv[0] == true);
          assert(dv[1] == false);
          assert(dv[2] == true);
          std::cout << " -> tests passed" << std::endl;
      }
      

.. _example-booleanmask-data_vector-11:

.. dropdown:: data_vector (pd_test_3_all.cpp:24090)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24080
      :emphasize-lines: 11

      namespace dataframe_tests_df_boolean_mask_core {
      
      void test_boolean_mask_construct_data() {
          std::cout << "========= BooleanMask construct from vector<bool> ====== ";
          std::vector<bool> d1 = {true, false, true};
          pandas::BooleanMask m(d1);
          assert(m.size() == 3);
          assert(m.data_at(0) == true);
          assert(m.data_at(1) == false);
          assert(m.data_at(2) == true);
          auto dv = m.data_vector();
          assert(dv.size() == 3);
          assert(dv[0] == true);
          assert(dv[1] == false);
          assert(dv[2] == true);
          std::cout << " -> tests passed" << std::endl;
      }
      
      void test_boolean_mask_construct_na() {
          std::cout << "========= BooleanMask construct with NA mask ====== ";
          std::vector<bool> d1 = {true, false, true};

.. _example-booleanmask-has_na-12:

.. dropdown:: has_na (pd_test_1_all.cpp:61)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 51
      :emphasize-lines: 11

              if (!arr.is_na(1)) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : is_na(1) should be true" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: is_na(1) should be true");
              }
      
              if (arr.is_na(0)) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : is_na(0) should be false" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: is_na(0) should be false");
              }
      
              if (!arr.has_na()) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : has_na() should be true" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: has_na() should be true");
              }
      
              if (arr.count() != 2) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_na_handling() : count() should be 2" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_na_handling failed: count() should be 2");
              }
      
              std::cout << " -> tests passed" << std::endl;

.. _example-booleanmask-na_mask_vector-13:

.. dropdown:: na_mask_vector (pd_test_3_all.cpp:24108)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24098
      :emphasize-lines: 11

      void test_boolean_mask_construct_na() {
          std::cout << "========= BooleanMask construct with NA mask ====== ";
          std::vector<bool> d1 = {true, false, true};
          std::vector<bool> na1 = {false, true, false};
          pandas::BooleanMask m(d1, na1);
          assert(m.size() == 3);
          assert(m.has_na());
          assert(!m.is_na(0));
          assert(m.is_na(1));
          assert(!m.is_na(2));
          auto nav = m.na_mask_vector();
          assert(nav.size() == 3);
          assert(nav[0] == false);
          assert(nav[1] == true);
          assert(nav[2] == false);
          std::cout << " -> tests passed" << std::endl;
      }
      
      void test_boolean_mask_construct_index() {
          std::cout << "========= BooleanMask construct with index labels ====== ";
          std::vector<bool> d1 = {true, false};

.. _example-booleanmask-result-14:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-15:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-16:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-17:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-18:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-19:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-result-20:

.. dropdown:: result (pd_test_1_all.cpp:15406)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 15396
      :emphasize-lines: 11

          data.setElementAt({0}, numpy::datetime64(100LL, numpy::DateTimeUnit::Nanosecond));
          data.setElementAt({1}, numpy::datetime64(200LL, numpy::DateTimeUnit::Nanosecond));
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{2});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeIndexBase idx(arr, "original");
      
          // Create join result (int64 values)
          numpy::NDArray<numpy::int64> join_result(std::vector<size_t>{3});
          join_result.setElementAt({0}, numpy::int64(500LL));
          join_result.setElementAt({1}, numpy::int64(600LL));
          join_result.setElementAt({2}, numpy::int64(700LL));
      
          auto new_idx = idx._from_join_target(join_result);
      
          bool passed = (new_idx.size() == 3 &&
                         new_idx.name().has_value() && *new_idx.name() == "original");
          if (!passed) {

.. _example-booleanmask-size-21:

.. dropdown:: size (pd_test_1_all.cpp:22)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12
      :emphasize-lines: 11

      #include "../pandas/pd_boolean_array.h"
      
      namespace dataframe_tests {
      
      namespace dataframe_tests_boolean_array {
          void pd_test_boolean_array_constructors() {
              std::cout << "========= BooleanArray: constructors ======================= ";
      
              // Default constructor
              pandas::BooleanArray arr1;
              if (arr1.size() != 0) {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_constructors() : default constructor size != 0" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_constructors failed: default constructor size != 0");
              }
      
              // Initializer list constructor
              pandas::BooleanArray arr2({
                  std::optional<bool>(true),
                  std::optional<bool>(false),
                  std::nullopt,
                  std::optional<bool>(true)

.. _example-booleanmask-vals-22:

.. dropdown:: vals (pd_test_3_all.cpp:12418)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12408
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      // ============================================================================
      // Test 22: memory_usage()
      // ============================================================================
      void pd_test_series_memory_usage() {
          std::cout << "========= Series.memory_usage() ====================";
      
          std::vector<double> vals(1000);
          pandas::Series<double> s(vals, "test");
      
          size_t mem = s.memory_usage();
          // Should be at least 1000 * sizeof(double)
          if (mem < 1000 * sizeof(double)) {
              std::cout << "  [FAIL] : memory_usage too small" << std::endl;
              throw std::runtime_error("pd_test_series_memory_usage failed");
          }
      
          std::cout << " -> tests passed" << std::endl;

.. _example-booleanmask-vals-23:

.. dropdown:: vals (pd_test_3_all.cpp:12418)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12408
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      // ============================================================================
      // Test 22: memory_usage()
      // ============================================================================
      void pd_test_series_memory_usage() {
          std::cout << "========= Series.memory_usage() ====================";
      
          std::vector<double> vals(1000);
          pandas::Series<double> s(vals, "test");
      
          size_t mem = s.memory_usage();
          // Should be at least 1000 * sizeof(double)
          if (mem < 1000 * sizeof(double)) {
              std::cout << "  [FAIL] : memory_usage too small" << std::endl;
              throw std::runtime_error("pd_test_series_memory_usage failed");
          }
      
          std::cout << " -> tests passed" << std::endl;

.. _example-booleanmask-vals-24:

.. dropdown:: vals (pd_test_3_all.cpp:12418)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12408
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      // ============================================================================
      // Test 22: memory_usage()
      // ============================================================================
      void pd_test_series_memory_usage() {
          std::cout << "========= Series.memory_usage() ====================";
      
          std::vector<double> vals(1000);
          pandas::Series<double> s(vals, "test");
      
          size_t mem = s.memory_usage();
          // Should be at least 1000 * sizeof(double)
          if (mem < 1000 * sizeof(double)) {
              std::cout << "  [FAIL] : memory_usage too small" << std::endl;
              throw std::runtime_error("pd_test_series_memory_usage failed");
          }
      
          std::cout << " -> tests passed" << std::endl;