RowTuple
========

.. cpp:class:: pandas::RowTuple

   Iterator class for traversing pandas data structures.

Example
-------

.. code-block:: cpp

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

   // Use RowTuple
   RowTuple obj;
   // ... operations ...

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``const std::string& at(size_t pos) const``
     - const std::string&
     - pd_dataframe.h:2326
     - :ref:`View <example-rowtuple-at-0>`

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_dataframe.h:2340
     - :ref:`View <example-rowtuple-to_string-1>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``size_t size() const``
     - size_t
     - pd_dataframe.h:2333
     - :ref:`View <example-rowtuple-size-2>`


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

The following examples are extracted from the test suite.

.. _example-rowtuple-at-0:

.. 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-rowtuple-to_string-1:

.. 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-rowtuple-size-2:

.. 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)