IntegerArray
============

.. cpp:class:: pandas::IntegerArray

   Extension array type for specialized data storage.

Example
-------

.. code-block:: cpp

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

   // Use IntegerArray
   IntegerArray obj;
   // ... operations ...

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

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

   * - Signature
     - Location
     - Example
   * - ``IntegerArray(const numpy::NDArray<T>& data, const numpy::NDArray<numpy::bool_>& mask, bool copy = false)``
     - pd_integer_array.h:68
     - :ref:`View <example-integerarray-integerarray-0>`
   * - ``explicit IntegerArray(const numpy::NDArray<T>& data)``
     - pd_integer_array.h:81
     - :ref:`View <example-integerarray-integerarray-1>`
   * - ``explicit IntegerArray(const std::vector<std::optional<T>>& values)``
     - pd_integer_array.h:112
     - :ref:`View <example-integerarray-integerarray-2>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static IntegerArray<T> from_sequence(const std::vector<std::optional<T>>& scalars)``
     - static IntegerArray<T>
     - pd_integer_array.h:317
     - 

Indexing / Selection
--------------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``T at(size_t index) const``
     - T
     - pd_integer_array.h:214
     - :ref:`View <example-integerarray-at-3>`
   * - ``const numpy::NDArray<numpy::bool_>& mask() const``
     - const numpy::NDArray<numpy::bool_>&
     - pd_integer_array.h:194
     - :ref:`View <example-integerarray-mask-4>`
   * - ``IntegerArray<T> take(const std::vector<size_t>& indices, bool allow_fill = false, std::optional<T> fill_value = std::nullopt) const``
     - IntegerArray<T>
     - pd_integer_array.h:264
     - :ref:`View <example-integerarray-take-5>`

Data Manipulation
-----------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntegerArray<T> dropna() const``
     - IntegerArray<T>
     - pd_integer_array.h:367
     - :ref:`View <example-integerarray-dropna-6>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntegerArray<T> fillna(T value) const``
     - IntegerArray<T>
     - pd_integer_array.h:353
     - :ref:`View <example-integerarray-fillna-7>`
   * - ``numpy::NDArray<numpy::bool_> isna() const``
     - numpy::NDArray<numpy::bool_>
     - pd_integer_array.h:236
     - :ref:`View <example-integerarray-isna-8>`
   * - ``numpy::NDArray<numpy::bool_> notna() const``
     - numpy::NDArray<numpy::bool_>
     - pd_integer_array.h:243
     - :ref:`View <example-integerarray-notna-9>`

Statistics
----------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``size_t count() const``
     - size_t
     - pd_integer_array.h:398
     - :ref:`View <example-integerarray-count-10>`
   * - ``std::optional<T> max(bool skipna = true) const``
     - std::optional<T>
     - pd_integer_array.h:733
     - :ref:`View <example-integerarray-max-11>`
   * - ``std::optional<double> mean(bool skipna = true) const``
     - std::optional<double>
     - pd_integer_array.h:692
     - :ref:`View <example-integerarray-mean-12>`
   * - ``std::optional<T> min(bool skipna = true) const``
     - std::optional<T>
     - pd_integer_array.h:713
     - :ref:`View <example-integerarray-min-13>`
   * - ``std::optional<T> prod(bool skipna = true) const``
     - std::optional<T>
     - pd_integer_array.h:785
     - :ref:`View <example-integerarray-prod-14>`
   * - ``std::optional<double> std(bool skipna = true, int ddof = 1) const``
     - std::optional<double>
     - pd_integer_array.h:753
     - :ref:`View <example-integerarray-std-15>`
   * - ``std::optional<T> sum(bool skipna = true) const``
     - std::optional<T>
     - pd_integer_array.h:671
     - :ref:`View <example-integerarray-sum-16>`
   * - ``std::optional<double> var(bool skipna = true, int ddof = 1) const``
     - std::optional<double>
     - pd_integer_array.h:762
     - :ref:`View <example-integerarray-var-17>`

Comparison
----------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``numpy::NDArray<numpy::bool_> compare_op(const IntegerArray<T>& other, Op op) const``
     - numpy::NDArray<numpy::bool_>
     - pd_integer_array.h:932
     - 
   * - ``size_t len() const``
     - size_t
     - pd_integer_array.h:176
     - :ref:`View <example-integerarray-len-18>`

Sorting
-------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``numpy::NDArray<size_t> argsort(bool ascending = true, const std::string& na_position = "last") const``
     - numpy::NDArray<size_t>
     - pd_integer_array.h:490
     - :ref:`View <example-integerarray-argsort-19>`

Combining
---------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static IntegerArray<T> concat(const std::vector<IntegerArray<T>>& arrays)``
     - static IntegerArray<T>
     - pd_integer_array.h:324
     - :ref:`View <example-integerarray-concat-20>`

I/O
---

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``numpy::NDArray<U> to_numpy(bool copy = true, U na_value = U{}) const``
     - numpy::NDArray<U>
     - pd_integer_array.h:381
     - :ref:`View <example-integerarray-to_numpy-21>`
   * - ``std::string to_string() const``
     - std::string
     - pd_integer_array.h:846
     - :ref:`View <example-integerarray-to_string-22>`

Conversion
----------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntegerArray<T> copy() const``
     - IntegerArray<T>
     - pd_integer_array.h:254
     - :ref:`View <example-integerarray-copy-23>`

Set Operations
--------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntegerArray<T> unique() const``
     - IntegerArray<T>
     - pd_integer_array.h:427
     - :ref:`View <example-integerarray-unique-24>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool is_na(size_t index) const``
     - bool
     - pd_integer_array.h:225
     - :ref:`View <example-integerarray-is_na-25>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool all() const``
     - bool
     - pd_integer_array.h:818
     - :ref:`View <example-integerarray-all-26>`
   * - ``bool any() const``
     - bool
     - pd_integer_array.h:806
     - :ref:`View <example-integerarray-any-27>`
   * - ``std::optional<size_t> argmax() const``
     - std::optional<size_t>
     - pd_integer_array.h:540
     - :ref:`View <example-integerarray-argmax-28>`
   * - ``std::optional<size_t> argmin() const``
     - std::optional<size_t>
     - pd_integer_array.h:521
     - :ref:`View <example-integerarray-argmin-29>`
   * - ``IntegerArray<T> binary_op(const IntegerArray<T>& other, Op op) const``
     - IntegerArray<T>
     - pd_integer_array.h:895
     - 
   * - ``const numpy::NDArray<T>& data() const``
     - const numpy::NDArray<T>&
     - pd_integer_array.h:187
     - :ref:`View <example-integerarray-data-30>`
   * - ``dtype_type dtype() const``
     - dtype_type
     - pd_integer_array.h:134
     - :ref:`View <example-integerarray-dtype-31>`
   * - ``bool empty() const``
     - bool
     - pd_integer_array.h:169
     - :ref:`View <example-integerarray-empty-32>`
   * - ``std::pair<numpy::NDArray<numpy::int64>, IntegerArray<T>> factorize() const``
     - std::pair<numpy::NDArray<numpy::int64>, IntegerArray<T>>
     - pd_integer_array.h:454
     - :ref:`View <example-integerarray-factorize-33>`
   * - ``bool has_na() const``
     - bool
     - pd_integer_array.h:411
     - :ref:`View <example-integerarray-has_na-34>`
   * - ``size_t nbytes() const``
     - size_t
     - pd_integer_array.h:148
     - :ref:`View <example-integerarray-nbytes-35>`
   * - ``constexpr int ndim() const``
     - constexpr int
     - pd_integer_array.h:155
     - :ref:`View <example-integerarray-ndim-36>`
   * - ``op(data_.getElementAt({i}), other.data_.getElementAt({i}))))``
     - 
     - pd_integer_array.h:945
     - 
   * - ``op(data_.getElementAt({i}), scalar)))``
     - 
     - pd_integer_array.h:961
     - 
   * - ``std::string repr() const``
     - std::string
     - pd_integer_array.h:863
     - :ref:`View <example-integerarray-repr-37>`
   * - ``numpy::NDArray<numpy::bool_> scalar_compare(T scalar, Op op) const``
     - numpy::NDArray<numpy::bool_>
     - pd_integer_array.h:953
     - 
   * - ``IntegerArray<T> scalar_op(T scalar, Op op) const``
     - IntegerArray<T>
     - pd_integer_array.h:916
     - 
   * - ``std::vector<size_t> shape() const``
     - std::vector<size_t>
     - pd_integer_array.h:162
     - :ref:`View <example-integerarray-shape-38>`
   * - ``size_t size() const``
     - size_t
     - pd_integer_array.h:141
     - :ref:`View <example-integerarray-size-39>`
   * - ``void validate_arrays()``
     - void
     - pd_integer_array.h:876
     - 

Internal Methods
----------------

*1 internal methods (prefixed with underscore)*


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

The following examples are extracted from the test suite.

.. _example-integerarray-integerarray-0:

.. dropdown:: IntegerArray (pd_test_5_all.cpp:39055)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 39045
      :emphasize-lines: 11

          } catch (const std::exception& e) {
              std::cout << tag << " exception: " << e.what() << "\n";
          }
          std::cout << tag << " === end ===\n";
      }
      
      void case_16_integer_array_take_mixed() {
          const std::string tag = "[S16]";
          std::cout << "\n" << tag << " === begin IntegerArray.take mixed ===\n";
          try {
              // Source = IntegerArray<int64>([10, NA, 30])
              pandas::IntegerArray<int64_t> ia({
                  std::optional<int64_t>(10),
                  std::nullopt,
                  std::optional<int64_t>(30)
              });
              std::cout << tag << " source size=" << ia.size()
                        << " is_na(0)=" << ia.is_na(0)
                        << " is_na(1)=" << ia.is_na(1)
                        << " is_na(2)=" << ia.is_na(2) << "\n";
      

.. _example-integerarray-integerarray-1:

.. dropdown:: IntegerArray (pd_test_5_all.cpp:39055)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 39045
      :emphasize-lines: 11

          } catch (const std::exception& e) {
              std::cout << tag << " exception: " << e.what() << "\n";
          }
          std::cout << tag << " === end ===\n";
      }
      
      void case_16_integer_array_take_mixed() {
          const std::string tag = "[S16]";
          std::cout << "\n" << tag << " === begin IntegerArray.take mixed ===\n";
          try {
              // Source = IntegerArray<int64>([10, NA, 30])
              pandas::IntegerArray<int64_t> ia({
                  std::optional<int64_t>(10),
                  std::nullopt,
                  std::optional<int64_t>(30)
              });
              std::cout << tag << " source size=" << ia.size()
                        << " is_na(0)=" << ia.is_na(0)
                        << " is_na(1)=" << ia.is_na(1)
                        << " is_na(2)=" << ia.is_na(2) << "\n";
      

.. _example-integerarray-integerarray-2:

.. dropdown:: IntegerArray (pd_test_5_all.cpp:39055)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 39045
      :emphasize-lines: 11

          } catch (const std::exception& e) {
              std::cout << tag << " exception: " << e.what() << "\n";
          }
          std::cout << tag << " === end ===\n";
      }
      
      void case_16_integer_array_take_mixed() {
          const std::string tag = "[S16]";
          std::cout << "\n" << tag << " === begin IntegerArray.take mixed ===\n";
          try {
              // Source = IntegerArray<int64>([10, NA, 30])
              pandas::IntegerArray<int64_t> ia({
                  std::optional<int64_t>(10),
                  std::nullopt,
                  std::optional<int64_t>(30)
              });
              std::cout << tag << " source size=" << ia.size()
                        << " is_na(0)=" << ia.is_na(0)
                        << " is_na(1)=" << ia.is_na(1)
                        << " is_na(2)=" << ia.is_na(2) << "\n";
      

.. _example-integerarray-at-3:

.. dropdown:: at (pd_test_1_all.cpp:6581)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6571
      :emphasize-lines: 11

                  // Test isna/notna with float data
                  {
                      std::map<std::string, std::vector<numpy::float64>> float_data;
                      float_data["X"] = {1.0, std::nan(""), 3.0};
                      float_data["Y"] = {4.0, 5.0, std::nan("")};
                      pandas::DataFrame df_na(float_data);
      
                      auto na_mask = df_na.isna();
                      // Row 1, col 0 (X) should be NA
                      if (!na_mask.getElementAt({1, 0})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : isna at (1,0) should be true" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: isna at (1,0)");
                      }
                      // Row 2, col 1 (Y) should be NA
                      if (!na_mask.getElementAt({2, 1})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : isna at (2,1) should be true" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: isna at (2,1)");
                      }
                      // Row 0, col 0 should NOT be NA
                      if (na_mask.getElementAt({0, 0})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : isna at (0,0) should be false" << std::endl;

.. _example-integerarray-mask-4:

.. dropdown:: mask (pd_test_1_all.cpp:9119)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 9109
      :emphasize-lines: 11

      
      void pd_test_datetime_mixin_array_constructor() {
          std::cout << "========= DatetimeTDMixin array constructor =========================";
      
          // Create DatetimeArray with some values
          numpy::NDArray<numpy::datetime64> data(std::vector<size_t>{3});
          data.setElementAt({0}, numpy::datetime64(1000000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2001
          data.setElementAt({1}, numpy::datetime64(1500000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2017
          data.setElementAt({2}, numpy::datetime64(1600000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2020
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{3});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
          mask.setElementAt({2}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);
          pandas::DatetimeTDMixin idx(arr, "timestamps");
      
          bool passed = (idx.size() == 3 && !idx.empty() &&
                         idx.name().has_value() && *idx.name() == "timestamps" &&
                         idx.inferred_type() == "datetime");

.. _example-integerarray-take-5:

.. dropdown:: take (pd_test_1_all.cpp:5903)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5893
      :emphasize-lines: 11

      // Inherited Operations Tests
      // ============================================================================
      
      void pd_test_categorical_index_take() {
          std::cout << "========= inherited take ==============================";
      
          pandas::CategoricalArray arr({"a", "b", "c", "d"});
          pandas::CategoricalIndex idx(arr);
      
          std::vector<size_t> indices = {0, 2, 3};
          pandas::ExtensionIndex<pandas::CategoricalArray> taken = idx.take(indices);
      
          bool passed = (taken.size() == 3);
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_take()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_take failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      

.. _example-integerarray-dropna-6:

.. dropdown:: dropna (pd_test_1_all.cpp:531)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 521
      :emphasize-lines: 11

              }
      
              // Test isna array
              numpy::NDArray<numpy::bool_> na_mask = arr.isna();
              if (na_mask.getSize() != 4) {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_na_handling() : isna size != 4" << std::endl;
                  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");

.. _example-integerarray-fillna-7:

.. 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-integerarray-isna-8:

.. dropdown:: isna (pd_test_1_all.cpp:524)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 514
      :emphasize-lines: 11

                  throw std::runtime_error("pd_test_categorical_array_na_handling failed: has_na() should be true");
              }
      
              // Test count (non-NA)
              if (arr.count() != 2) {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_na_handling() : count() != 2" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_na_handling failed: count() != 2");
              }
      
              // Test isna array
              numpy::NDArray<numpy::bool_> na_mask = arr.isna();
              if (na_mask.getSize() != 4) {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_na_handling() : isna size != 4" << std::endl;
                  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");

.. _example-integerarray-notna-9:

.. dropdown:: notna (pd_test_1_all.cpp:6595)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6585
      :emphasize-lines: 11

                      if (!na_mask.getElementAt({2, 1})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : isna at (2,1) should be true" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: isna at (2,1)");
                      }
                      // Row 0, col 0 should NOT be NA
                      if (na_mask.getElementAt({0, 0})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : isna at (0,0) should be false" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: isna at (0,0)");
                      }
      
                      auto notna_mask = df_na.notna();
                      if (notna_mask.getElementAt({1, 0})) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : notna at (1,0) should be false" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: notna at (1,0)");
                      }
                  }
      
                  // Test fillna
                  {
                      std::map<std::string, std::vector<numpy::float64>> float_data;
                      float_data["X"] = {1.0, std::nan(""), 3.0};

.. _example-integerarray-count-10:

.. dropdown:: count (pd_test_1_all.cpp:66)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 56
      :emphasize-lines: 11

              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;
          }
      
          void pd_test_boolean_array_kleene_and() {
              std::cout << "========= BooleanArray: Kleene AND ======================= ";
      

.. _example-integerarray-max-11:

.. dropdown:: max (pd_test_1_all.cpp:771)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 761
      :emphasize-lines: 11

              pandas::CategoricalArray arr = pandas::CategoricalArray::from_codes(codes, cats, true);  // ordered
      
              // Test min
              std::optional<std::string> min_val = arr.min();
              if (!min_val.has_value() || *min_val != "low") {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_ordered_operations() : min != 'low'" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_ordered_operations failed: min != 'low'");
              }
      
              // Test max
              std::optional<std::string> max_val = arr.max();
              if (!max_val.has_value() || *max_val != "high") {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_ordered_operations() : max != 'high'" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_ordered_operations failed: max != 'high'");
              }
      
              // Test unordered throws for min/max
              pandas::CategoricalArray unordered = arr.as_unordered();
              bool threw = false;
              try {
                  unordered.min();

.. _example-integerarray-mean-12:

.. dropdown:: mean (pd_test_1_all.cpp:282)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 272
      :emphasize-lines: 11

                  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");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_boolean_array_dtype() {
              std::cout << "========= BooleanArray: dtype ======================= ";

.. _example-integerarray-min-13:

.. dropdown:: min (pd_test_1_all.cpp:764)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 754
      :emphasize-lines: 11

          }
      
          void pd_test_categorical_array_ordered_operations() {
              std::cout << "========= CategoricalArray: ordered operations (min/max) ======================= ";
      
              std::vector<std::string> cats = {"low", "medium", "high"};
              std::vector<numpy::int32> codes = {0, 2, 1, 0, -1};  // low, high, medium, low, NA
              pandas::CategoricalArray arr = pandas::CategoricalArray::from_codes(codes, cats, true);  // ordered
      
              // Test min
              std::optional<std::string> min_val = arr.min();
              if (!min_val.has_value() || *min_val != "low") {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_ordered_operations() : min != 'low'" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_ordered_operations failed: min != 'low'");
              }
      
              // Test max
              std::optional<std::string> max_val = arr.max();
              if (!max_val.has_value() || *max_val != "high") {
                  std::cout << "  [FAIL] : in pd_test_categorical_array_ordered_operations() : max != 'high'" << std::endl;
                  throw std::runtime_error("pd_test_categorical_array_ordered_operations failed: max != 'high'");

.. _example-integerarray-prod-14:

.. dropdown:: prod (pd_test_1_all.cpp:26082)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 26072
      :emphasize-lines: 11

      
              std::cout << "====================================== [OK] pd_test_pivot_table test suite ========================== " << std::endl;
              return 0;
          }
      
      } // namespace dataframe_tests
      // ------------------- pd_test_pivot_table.cpp (end) -----------------------------
      
      // ------------------- pd_test_prod.cpp (start) -----------------------------
      // dataframe_tests/pd_test_prod.cpp
      // Tests for DataFrame.prod() and DataFrame.prod_cols() methods
      
      #include <iostream>
      #include <stdexcept>
      #include <cmath>
      #include <limits>
      #include "../pandas/pd_dataframe.h"
      
      // CRITICAL: No using namespace directives
      
      namespace dataframe_tests {

.. _example-integerarray-std-15:

.. dropdown:: std (pd_test_1_all.cpp:4526)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 4516
      :emphasize-lines: 11

      #include "../pandas/pd_series.h"
      
      namespace dataframe_tests {
          namespace dataframe_tests_aggregation {
      
              void pd_test_aggregation_series_sem() {
                  std::cout << "========= Series sem ============================";
      
                  pandas::Series<double> s({1.0, 2.0, 3.0, 4.0, 5.0});
                  auto sem_val = s.sem();
                  // std(ddof=1) = sqrt(2.5), sem = sqrt(2.5)/sqrt(5) ≈ 0.707
                  bool passed = sem_val.has_value() && std::abs(*sem_val - 0.707) < 0.01;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_aggregation_series_sem() : sem value incorrect" << std::endl;
                      throw std::runtime_error("pd_test_aggregation_series_sem failed: sem value incorrect");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      
              void pd_test_aggregation_series_quantile() {

.. _example-integerarray-sum-16:

.. 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-integerarray-var-17:

.. dropdown:: var (pd_test_1_all.cpp:20890)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 20880
      :emphasize-lines: 11

                      throw std::runtime_error("pd_test_expanding_std failed: expanding std values incorrect");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      
              void pd_test_expanding_var() {
                  std::cout << "========= Expanding var =========================";
      
                  pandas::Series<double> s({1.0, 2.0, 3.0, 4.0, 5.0});
                  auto result = s.expanding().var();
      
                  // Expanding var (ddof=1): NaN, 0.5, 1.0, 1.6667, 2.5
                  bool passed = std::isnan(result[0]) &&
                                std::abs(result[1] - 0.5) < 0.001 &&
                                std::abs(result[2] - 1.0) < 0.001 &&
                                std::abs(result[3] - 1.6667) < 0.001 &&
                                std::abs(result[4] - 2.5) < 0.001;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_expanding_var() : expanding var values incorrect" << std::endl;
                      throw std::runtime_error("pd_test_expanding_var failed: expanding var values incorrect");

.. _example-integerarray-len-18:

.. dropdown:: len (pd_test_3_all.cpp:20867)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 20857
      :emphasize-lines: 11

          auto title_result = s.str().title();
          if (title_result[0] != "Hello World" || title_result[1] != "Hello World" || title_result[2] != "Hello World") {
              std::cout << "  [FAIL] : title() failed" << std::endl;
              throw std::runtime_error("pd_test_str_capitalize_title: title() failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      // ============================================================================
      // Test str().len()
      // ============================================================================
      
      void pd_test_str_len() {
          std::cout << "========= Series.str().len() ============================";
      
          pandas::Series<std::string> s({"a", "bb", "ccc", ""});
      
          auto lens = s.str().len();
          if (lens[0] != 1 || lens[1] != 2 || lens[2] != 3 || lens[3] != 0) {
              std::cout << "  [FAIL] : len() failed" << std::endl;

.. _example-integerarray-argsort-19:

.. dropdown:: argsort (pd_test_1_all.cpp:1304)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1294
      :emphasize-lines: 11

              std::cout << "========= DatetimeArray: sorting ======================= ";
      
              pandas::DatetimeArray arr(std::vector<std::string>{
                  "2023-06-15",
                  "NaT",
                  "2023-01-01",
                  "2023-12-31"
              });
      
              // argsort ascending
              auto indices = arr.argsort(true, "last");
              // Expected order: 2023-01-01(2), 2023-06-15(0), 2023-12-31(3), NaT(1)
              if (indices.getElementAt({0}) != 2) {
                  std::cout << "  [FAIL] : argsort: first should be index 2 (2023-01-01)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argsort first");
              }
              if (indices.getElementAt({3}) != 1) {
                  std::cout << "  [FAIL] : argsort: last should be index 1 (NaT)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: NaT position");
              }
      

.. _example-integerarray-concat-20:

.. dropdown:: concat (pd_test_1_all.cpp:17717)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 17707
      :emphasize-lines: 11

      }
      
      void pd_test_period_index_concat() {
          std::cout << "========= concat factory ==============================";
      
          std::vector<int64_t> ordinals1 = {0, 1};
          std::vector<int64_t> ordinals2 = {2, 3};
          pandas::PeriodIndex idx1(ordinals1, "D");
          pandas::PeriodIndex idx2(ordinals2, "D");
      
          pandas::PeriodIndex concatenated = pandas::PeriodIndex::concat({idx1, idx2});
      
          bool passed = (concatenated.size() == 4);
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_period_index_concat()" << std::endl;
              throw std::runtime_error("pd_test_period_index_concat failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      

.. _example-integerarray-to_numpy-21:

.. dropdown:: to_numpy (pd_test_1_all.cpp:16764)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 16754
      :emphasize-lines: 11

      
              // =====================================================================
              // to_numpy Tests
              // =====================================================================
      
              void pd_test_ndframe_to_numpy() {
                  std::cout << "========= to_numpy =============================================" << std::endl;
      
                  pandas::Series<int> s({10, 20, 30});
      
                  auto arr = s.to_numpy();
      
                  bool passed = arr.getSize() == 3;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_ndframe_to_numpy() : size" << std::endl;
                      throw std::runtime_error("pd_test_ndframe_to_numpy failed: size");
                  }
      
                  passed = arr.getElementAt({0}) == 10 && arr.getElementAt({1}) == 20 && arr.getElementAt({2}) == 30;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_ndframe_to_numpy() : values" << std::endl;

.. _example-integerarray-to_string-22:

.. 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-integerarray-copy-23:

.. dropdown:: copy (pd_test_1_all.cpp:5798)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5788
      :emphasize-lines: 11

      // ============================================================================
      // Copy/Rename Tests
      // ============================================================================
      
      void pd_test_categorical_index_copy() {
          std::cout << "========= copy ========================================";
      
          pandas::CategoricalArray arr({"a", "b", "c"});
          pandas::CategoricalIndex idx(arr, "original");
      
          pandas::CategoricalIndex copied = idx.copy();
      
          bool passed = (copied.size() == idx.size() && copied.name() == idx.name() &&
                         copied.categories() == idx.categories() && copied.ordered() == idx.ordered());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_copy()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_copy failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-integerarray-unique-24:

.. dropdown:: unique (pd_test_1_all.cpp:1345)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1335
      :emphasize-lines: 11

              pandas::DatetimeArray arr(std::vector<std::string>{
                  "2023-01-01",
                  "2023-06-15",
                  "2023-01-01",
                  "NaT",
                  "2023-06-15",
                  "NaT"
              });
      
              // unique
              auto uniq = arr.unique();
              // Should have: NaT, 2023-01-01, 2023-06-15 (3 unique values)
              if (uniq.size() != 3) {
                  std::cout << "  [FAIL] : unique size should be 3, got " << uniq.size() << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_unique failed: size");
              }
      
              // factorize
              auto [codes, uniques] = arr.factorize();
              // Codes for NaT should be -1
              if (codes.getElementAt({3}) != -1) {

.. _example-integerarray-is_na-25:

.. 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-integerarray-all-26:

.. 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-integerarray-any-27:

.. 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-integerarray-argmax-28:

.. dropdown:: argmax (pd_test_1_all.cpp:1323)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1313
      :emphasize-lines: 11

              }
      
              // argmin
              auto min_idx = arr.argmin();
              if (!min_idx.has_value() || min_idx.value() != 2) {
                  std::cout << "  [FAIL] : argmin should be 2 (2023-01-01)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argmin");
              }
      
              // argmax
              auto max_idx = arr.argmax();
              if (!max_idx.has_value() || max_idx.value() != 3) {
                  std::cout << "  [FAIL] : argmax should be 3 (2023-12-31)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argmax");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_datetime_array_unique() {
              std::cout << "========= DatetimeArray: unique/factorize ======================= ";

.. _example-integerarray-argmin-29:

.. dropdown:: argmin (pd_test_1_all.cpp:1316)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1306
      :emphasize-lines: 11

              if (indices.getElementAt({0}) != 2) {
                  std::cout << "  [FAIL] : argsort: first should be index 2 (2023-01-01)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argsort first");
              }
              if (indices.getElementAt({3}) != 1) {
                  std::cout << "  [FAIL] : argsort: last should be index 1 (NaT)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: NaT position");
              }
      
              // argmin
              auto min_idx = arr.argmin();
              if (!min_idx.has_value() || min_idx.value() != 2) {
                  std::cout << "  [FAIL] : argmin should be 2 (2023-01-01)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argmin");
              }
      
              // argmax
              auto max_idx = arr.argmax();
              if (!max_idx.has_value() || max_idx.value() != 3) {
                  std::cout << "  [FAIL] : argmax should be 3 (2023-12-31)" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_sorting failed: argmax");

.. _example-integerarray-data-30:

.. dropdown:: data (pd_test_1_all.cpp:9114)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 9104
      :emphasize-lines: 11

              throw std::runtime_error("pd_test_datetime_mixin_default_constructor failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_datetime_mixin_array_constructor() {
          std::cout << "========= DatetimeTDMixin array constructor =========================";
      
          // Create DatetimeArray with some values
          numpy::NDArray<numpy::datetime64> data(std::vector<size_t>{3});
          data.setElementAt({0}, numpy::datetime64(1000000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2001
          data.setElementAt({1}, numpy::datetime64(1500000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2017
          data.setElementAt({2}, numpy::datetime64(1600000000000000000LL, numpy::DateTimeUnit::Nanosecond));  // ~2020
      
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{3});
          mask.setElementAt({0}, numpy::bool_(false));
          mask.setElementAt({1}, numpy::bool_(false));
          mask.setElementAt({2}, numpy::bool_(false));
      
          pandas::DatetimeArray arr(data, mask);

.. _example-integerarray-dtype-31:

.. dropdown:: dtype (pd_test_1_all.cpp:295)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 285
      :emphasize-lines: 11

                  throw std::runtime_error("pd_test_boolean_array_reductions failed: mean");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          void pd_test_boolean_array_dtype() {
              std::cout << "========= BooleanArray: dtype ======================= ";
      
              pandas::BooleanArray arr;
              if (arr.dtype().name() != "boolean") {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype name should be 'boolean'" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype name");
              }
      
              if (arr.dtype().kind() != "b") {
                  std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype kind should be 'b'" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype kind");
              }
      
              std::cout << " -> tests passed" << std::endl;

.. _example-integerarray-empty-32:

.. dropdown:: empty (pd_test_1_all.cpp:941)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 931
      :emphasize-lines: 11

      
      #include "../pandas/pd_config.h"
      
      namespace dataframe_tests {
      
      namespace dataframe_tests_config {
      
          void pd_test_config_version() {
              std::cout << "========= df_config: version info ======================= ";
              const char* version = pandas::DataFrameInfo::version();
              if (version == nullptr || std::string(version).empty()) {
                  std::cout << "[FAIL] : in pd_test_config_version() : version is null or empty" << std::endl;
                  throw std::runtime_error("pd_test_config_version failed: version is null or empty");
              }
              std::cout << "-> tests passed" << std::endl;
          }
      
          void pd_test_config_na_repr() {
              std::cout << "========= df_config: NA representation ======================= ";
              const char* na_repr = pandas::DataFrameConfig::get_na_repr();
              if (na_repr == nullptr) {

.. _example-integerarray-factorize-33:

.. dropdown:: factorize (pd_test_1_all.cpp:1353)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1343
      :emphasize-lines: 11

      
              // unique
              auto uniq = arr.unique();
              // Should have: NaT, 2023-01-01, 2023-06-15 (3 unique values)
              if (uniq.size() != 3) {
                  std::cout << "  [FAIL] : unique size should be 3, got " << uniq.size() << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_unique failed: size");
              }
      
              // factorize
              auto [codes, uniques] = arr.factorize();
              // Codes for NaT should be -1
              if (codes.getElementAt({3}) != -1) {
                  std::cout << "  [FAIL] : factorize: NaT code should be -1" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_unique failed: NaT code");
              }
              // Same values should have same codes
              if (codes.getElementAt({0}) != codes.getElementAt({2})) {
                  std::cout << "  [FAIL] : factorize: 2023-01-01 values should have same code" << std::endl;
                  throw std::runtime_error("pd_test_datetime_array_unique failed: same code");
              }

.. _example-integerarray-has_na-34:

.. 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-integerarray-nbytes-35:

.. dropdown:: nbytes (pd_test_1_all.cpp:6214)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6204
      :emphasize-lines: 11

                  }
      
                  // Test empty DataFrame
                  pandas::DataFrame empty_df;
                  if (!empty_df.empty()) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : should be empty" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: should be empty");
                  }
      
                  // Test nbytes > 0 for non-empty
                  if (df.nbytes() == 0) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : nbytes should be > 0" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: nbytes should be > 0");
                  }
      
                  // Test columns index
                  if (df.columns().size() != 3) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : columns size != 3" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: columns size != 3");
                  }
      

.. _example-integerarray-ndim-36:

.. dropdown:: ndim (pd_test_1_all.cpp:6195)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6185
      :emphasize-lines: 11

                  pandas::DataFrame df(data);
      
                  // Test shape
                  auto shape = df.shape();
                  if (shape.size() != 2 || shape[0] != 4 || shape[1] != 3) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : shape mismatch" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: shape mismatch");
                  }
      
                  // Test ndim
                  if (df.ndim() != 2) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : ndim != 2" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: ndim != 2");
                  }
      
                  // Test empty
                  if (df.empty()) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : should not be empty" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: should not be empty");
                  }
      

.. _example-integerarray-repr-37:

.. dropdown:: repr (pd_test_1_all.cpp:10906)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10896
      :emphasize-lines: 11

          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_extension_index_repr() {
          std::cout << "========= repr =========================";
      
          pandas::CategoricalArray arr({"a", "b", "c"});
          // Use ExtensionIndex<CategoricalArray> directly to test base class repr
          pandas::ExtensionIndex<pandas::CategoricalArray> idx(arr, "test");
      
          std::string repr_str = idx.repr();
      
          bool passed = (!repr_str.empty() && repr_str.find("ExtensionIndex") != std::string::npos);
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_repr() : repr check failed" << std::endl;
              throw std::runtime_error("pd_test_extension_index_repr failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      

.. _example-integerarray-shape-38:

.. dropdown:: shape (pd_test_1_all.cpp:6188)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6178
      :emphasize-lines: 11

                  std::cout << "========= properties =======================";
      
                  std::map<std::string, std::vector<numpy::float64>> data;
                  data["A"] = {1.0, 2.0, 3.0, 4.0};
                  data["B"] = {5.0, 6.0, 7.0, 8.0};
                  data["C"] = {9.0, 10.0, 11.0, 12.0};
      
                  pandas::DataFrame df(data);
      
                  // Test shape
                  auto shape = df.shape();
                  if (shape.size() != 2 || shape[0] != 4 || shape[1] != 3) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : shape mismatch" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: shape mismatch");
                  }
      
                  // Test ndim
                  if (df.ndim() != 2) {
                      std::cout << "  [FAIL] : in pd_test_dataframe_properties() : ndim != 2" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_properties failed: ndim != 2");
                  }

.. _example-integerarray-size-39:

.. 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)