IntervalIndex
=============

.. cpp:class:: pandas::IntervalIndex

   Index class for axis labels in pandas data structures.

Example
-------

.. code-block:: cpp

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

   // Create IntervalIndex
   IntervalIndex<int64_t> idx({1, 2, 3}, "my_index");
   size_t len = idx.size();

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

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   * - Signature
     - Location
     - Example
   * - ``explicit IntervalIndex(const IntervalArray<T>& array, const std::optional<std::string>& name = std::nullopt)``
     - pd_interval_index.h:144
     - :ref:`View <example-intervalindex-intervalindex-0>`
   * - ``explicit IntervalIndex(IntervalArray<T>&& array, const std::optional<std::string>& name = std::nullopt)``
     - pd_interval_index.h:153
     - :ref:`View <example-intervalindex-intervalindex-1>`
   * - ``IntervalIndex(const IntervalIndex& other)``
     - pd_interval_index.h:162
     - :ref:`View <example-intervalindex-intervalindex-2>`
   * - ``IntervalIndex(IntervalIndex&& other) noexcept = default``
     - pd_interval_index.h:171
     - :ref:`View <example-intervalindex-intervalindex-3>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static IntervalIndex from_arrays( const std::vector<T>& left, const std::vector<T>& right, IntervalClosed closed = IntervalClosed::Right, const std::optional<std::string>& name = std::nullopt, bool copy = false, const std::string& dtype = "")``
     - static IntervalIndex
     - pd_interval_index.h:203
     - :ref:`View <example-intervalindex-from_arrays-4>`
   * - ``static IntervalIndex from_arrays( const numpy::NDArray<T>& left, const numpy::NDArray<T>& right, IntervalClosed closed = IntervalClosed::Right, const std::optional<std::string>& name = std::nullopt, bool copy = false, const std::string& dtype = "")``
     - static IntervalIndex
     - pd_interval_index.h:231
     - :ref:`View <example-intervalindex-from_arrays-5>`
   * - ``static IntervalIndex from_breaks( const std::vector<T>& breaks, IntervalClosed closed = IntervalClosed::Right, const std::optional<std::string>& name = std::nullopt, bool copy = false, const std::string& dtype = "")``
     - static IntervalIndex
     - pd_interval_index.h:260
     - :ref:`View <example-intervalindex-from_breaks-6>`
   * - ``static IntervalIndex from_breaks( const numpy::NDArray<T>& breaks, IntervalClosed closed = IntervalClosed::Right, const std::optional<std::string>& name = std::nullopt, bool copy = false, const std::string& dtype = "")``
     - static IntervalIndex
     - pd_interval_index.h:286
     - :ref:`View <example-intervalindex-from_breaks-7>`
   * - ``static IntervalIndex from_tuples( const std::vector<std::pair<T, T>>& data, IntervalClosed closed = IntervalClosed::Right, const std::optional<std::string>& name = std::nullopt, bool copy = false, const std::string& dtype = "")``
     - static IntervalIndex
     - pd_interval_index.h:313
     - :ref:`View <example-intervalindex-from_tuples-8>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``get_indexer_non_unique(const IntervalIndex& target) const``
     - 
     - pd_interval_index.h:1441
     - :ref:`View <example-intervalindex-get_indexer_non_unique-9>`
   * - ``IntervalIndex get_level_values(int level = 0) const``
     - IntervalIndex
     - pd_interval_index.h:1751
     - :ref:`View <example-intervalindex-get_level_values-10>`
   * - ``size_t get_slice_bound(const std::pair<T, T>& label, const std::string& side = "left") const``
     - size_t
     - pd_interval_index.h:1364
     - :ref:`View <example-intervalindex-get_slice_bound-11>`
   * - ``std::string get_string(size_t i) const``
     - std::string
     - pd_interval_index.h:735
     - :ref:`View <example-intervalindex-get_string-12>`
   * - ``std::string get_value_str(size_t index) const override``
     - std::string
     - pd_interval_index.h:723
     - :ref:`View <example-intervalindex-get_value_str-13>`
   * - ``IntervalIndex where(const numpy::NDArray<numpy::bool_>& cond, const std::optional<std::pair<T, T>>& other = std::nullopt) const``
     - IntervalIndex
     - pd_interval_index.h:1643
     - :ref:`View <example-intervalindex-where-14>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntervalIndex drop_duplicates(const std::string& keep = "first") const``
     - IntervalIndex
     - pd_interval_index.h:979
     - :ref:`View <example-intervalindex-drop_duplicates-15>`
   * - ``IntervalIndex droplevel(int level = 0) const``
     - IntervalIndex
     - pd_interval_index.h:1763
     - :ref:`View <example-intervalindex-droplevel-16>`
   * - ``IntervalIndex insert(size_t loc, const std::pair<T, T>& item) const``
     - IntervalIndex
     - pd_interval_index.h:1084
     - :ref:`View <example-intervalindex-insert-17>`
   * - ``std::pair<IntervalIndex, numpy::NDArray<numpy::int64>> reindex( const IntervalIndex& target, const std::string& method = "", std::optional<int> level = std::nullopt, std::optional<int> limit = std::nullopt, std::optional<T> tolerance = std::nullopt) const``
     - std::pair<IntervalIndex, numpy::NDArray<numpy::int64>>
     - pd_interval_index.h:1562
     - :ref:`View <example-intervalindex-reindex-18>`
   * - ``IntervalIndex rename(const std::optional<std::string>& new_name, bool inplace = false, std::optional<std::string> name = std::nullopt) const``
     - IntervalIndex
     - pd_interval_index.h:757
     - :ref:`View <example-intervalindex-rename-19>`
   * - ``IntervalIndex set_names(const std::optional<std::string>& names, std::optional<int> level = std::nullopt, bool inplace = false) const``
     - IntervalIndex
     - pd_interval_index.h:1698
     - :ref:`View <example-intervalindex-set_names-20>`

Statistics
----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``std::optional<std::pair<T, T>> max(bool skipna = true, std::optional<int> axis = std::nullopt) const``
     - std::optional<std::pair<T, T>>
     - pd_interval_index.h:830
     - :ref:`View <example-intervalindex-max-21>`
   * - ``std::optional<std::pair<T, T>> min(bool skipna = true, std::optional<int> axis = std::nullopt) const``
     - std::optional<std::pair<T, T>>
     - pd_interval_index.h:816
     - :ref:`View <example-intervalindex-min-22>`

Aggregation
-----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``std::unordered_map<GroupKey, std::vector<size_t>> groupby(KeyFunc key_func, std::optional<ValuesT> values = std::nullopt) const``
     - std::unordered_map<GroupKey, std::vector<size_t>>
     - pd_interval_index.h:1816
     - :ref:`View <example-intervalindex-groupby-23>`
   * - ``std::unordered_map<GroupT, std::vector<size_t>> groupby( const std::vector<GroupT>& values) const``
     - std::unordered_map<GroupT, std::vector<size_t>>
     - pd_interval_index.h:1848
     - :ref:`View <example-intervalindex-groupby-24>`
   * - ``IntervalIndex map(Func mapper, const std::string& na_action = "") const``
     - IntervalIndex
     - pd_interval_index.h:1616
     - :ref:`View <example-intervalindex-map-25>`

Arithmetic
----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``const std::string& subtype_override() const``
     - const std::string&
     - pd_interval_index.h:537
     - :ref:`View <example-intervalindex-subtype_override-26>`

Comparison
----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``numpy::NDArray<T> left() const``
     - numpy::NDArray<T>
     - pd_interval_index.h:344
     - :ref:`View <example-intervalindex-left-27>`
   * - ``numpy::NDArray<T> length() const``
     - numpy::NDArray<T>
     - pd_interval_index.h:366
     - :ref:`View <example-intervalindex-length-28>`
   * - ``IntervalArray<T> new_arr(values, arr.closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1939
     - 
   * - ``IntervalArray<T> new_arr(values, arr.closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1959
     - 
   * - ``IntervalArray<T> new_arr(result, arr1.closed())``
     - IntervalArray<T>
     - pd_interval_index.h:2028
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1100
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1189
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1212
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1545
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1601
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1633
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1660
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1687
     - 
   * - ``IntervalArray<T> new_array(values, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1741
     - 

Sorting
-------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``size_t searchsorted(const std::pair<T, T>& value, const std::string& side = "left", std::optional<numpy::NDArray<numpy::int64>> sorter = std::nullopt) const``
     - size_t
     - pd_interval_index.h:1477
     - :ref:`View <example-intervalindex-searchsorted-29>`

Reshaping
---------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``FrameData to_frame(bool index = true, const std::optional<std::string>& name = std::nullopt) const``
     - FrameData
     - pd_interval_index.h:2074
     - :ref:`View <example-intervalindex-to_frame-30>`
   * - ``IntervalIndex transpose() const``
     - IntervalIndex
     - pd_interval_index.h:1236
     - :ref:`View <example-intervalindex-transpose-31>`

Combining
---------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntervalIndex join(const IntervalIndex& other, const std::string& how = "left", std::optional<int> level = std::nullopt, bool return_indexers = false, bool sort = false) const``
     - IntervalIndex
     - pd_interval_index.h:1890
     - :ref:`View <example-intervalindex-join-32>`

Time Series
-----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``std::optional<std::pair<T, T>> asof(T where, std::optional<T> label = std::nullopt) const``
     - std::optional<std::pair<T, T>>
     - pd_interval_index.h:1314
     - :ref:`View <example-intervalindex-asof-33>`
   * - ``numpy::NDArray<numpy::int64> asof_locs(const numpy::NDArray<T>& where, std::optional<numpy::NDArray<numpy::bool_>> mask = std::nullopt) const``
     - numpy::NDArray<numpy::int64>
     - pd_interval_index.h:1336
     - :ref:`View <example-intervalindex-asof_locs-34>`
   * - ``numpy::NDArray<T> diff(int64_t periods = 1) const``
     - numpy::NDArray<T>
     - pd_interval_index.h:1109
     - :ref:`View <example-intervalindex-diff-35>`
   * - ``IntervalIndex shift(int64_t periods = 1, std::optional<std::string> freq = std::nullopt) const``
     - IntervalIndex
     - pd_interval_index.h:1159
     - :ref:`View <example-intervalindex-shift-36>`

I/O
---

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntervalIndex to_flat_index() const``
     - IntervalIndex
     - pd_interval_index.h:1243
     - :ref:`View <example-intervalindex-to_flat_index-37>`
   * - ``std::vector<std::pair<T, T>> to_numpy( bool copy = true, const std::pair<T, T>& na_value = std::pair<T, T>{T{0}, T{0}}) const``
     - std::vector<std::pair<T, T>>
     - pd_interval_index.h:1255
     - :ref:`View <example-intervalindex-to_numpy-38>`
   * - ``SeriesData to_series(const std::optional<IntervalIndex>& index = std::nullopt, const std::optional<std::string>& name = std::nullopt) const``
     - SeriesData
     - pd_interval_index.h:2141
     - :ref:`View <example-intervalindex-to_series-39>`
   * - ``std::string to_string() const override``
     - std::string
     - pd_interval_index.h:649
     - :ref:`View <example-intervalindex-to_string-40>`
   * - ``std::vector<std::optional<std::pair<T, T>>> to_tuples() const``
     - std::vector<std::optional<std::pair<T, T>>>
     - pd_interval_index.h:519
     - :ref:`View <example-intervalindex-to_tuples-41>`
   * - ``std::vector<std::optional<std::pair<T, T>>> tolist() const``
     - std::vector<std::optional<std::pair<T, T>>>
     - pd_interval_index.h:1274
     - :ref:`View <example-intervalindex-tolist-42>`

Conversion
----------

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``IntervalIndex astype(const std::string& dtype, bool copy = true) const``
     - IntervalIndex
     - pd_interval_index.h:1782
     - :ref:`View <example-intervalindex-astype-43>`
   * - ``IntervalIndex copy() const``
     - IntervalIndex
     - pd_interval_index.h:770
     - :ref:`View <example-intervalindex-copy-44>`
   * - ``IntervalIndex infer_objects() const``
     - IntervalIndex
     - pd_interval_index.h:1712
     - :ref:`View <example-intervalindex-infer_objects-45>`
   * - ``IntervalIndex view() const``
     - IntervalIndex
     - pd_interval_index.h:1228
     - :ref:`View <example-intervalindex-view-46>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``std::vector<bool> duplicated(const std::string& keep = "first") const``
     - std::vector<bool>
     - pd_interval_index.h:1038
     - :ref:`View <example-intervalindex-duplicated-47>`
   * - ``IntervalIndex union_(const IntervalIndex& other, bool sort = true) const``
     - IntervalIndex
     - pd_interval_index.h:1973
     - :ref:`View <example-intervalindex-union_-48>`
   * - ``IntervalIndex unique() const``
     - IntervalIndex
     - pd_interval_index.h:960
     - :ref:`View <example-intervalindex-unique-49>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool is_(const IntervalIndex& other) const``
     - bool
     - pd_interval_index.h:1772
     - :ref:`View <example-intervalindex-is_-50>`
   * - ``bool is_boolean() const``
     - bool
     - pd_interval_index.h:873
     - :ref:`View <example-intervalindex-is_boolean-51>`
   * - ``bool is_categorical() const``
     - bool
     - pd_interval_index.h:880
     - :ref:`View <example-intervalindex-is_categorical-52>`
   * - ``BooleanArray is_empty() const``
     - BooleanArray
     - pd_interval_index.h:412
     - :ref:`View <example-intervalindex-is_empty-53>`
   * - ``bool is_floating() const``
     - bool
     - pd_interval_index.h:887
     - :ref:`View <example-intervalindex-is_floating-54>`
   * - ``bool is_integer() const``
     - bool
     - pd_interval_index.h:894
     - :ref:`View <example-intervalindex-is_integer-55>`
   * - ``bool is_interval() const``
     - bool
     - pd_interval_index.h:866
     - :ref:`View <example-intervalindex-is_interval-56>`
   * - ``bool is_left_closed() const``
     - bool
     - pd_interval_index.h:391
     - :ref:`View <example-intervalindex-is_left_closed-57>`
   * - ``bool is_non_overlapping_monotonic() const``
     - bool
     - pd_interval_index.h:439
     - :ref:`View <example-intervalindex-is_non_overlapping_monotonic-58>`
   * - ``bool is_numeric() const``
     - bool
     - pd_interval_index.h:901
     - :ref:`View <example-intervalindex-is_numeric-59>`
   * - ``bool is_object() const``
     - bool
     - pd_interval_index.h:908
     - :ref:`View <example-intervalindex-is_object-60>`
   * - ``bool is_overlapping() const``
     - bool
     - pd_interval_index.h:424
     - :ref:`View <example-intervalindex-is_overlapping-61>`
   * - ``bool is_right_closed() const``
     - bool
     - pd_interval_index.h:398
     - :ref:`View <example-intervalindex-is_right_closed-62>`

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

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   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool all(bool skipna = true) const``
     - bool
     - pd_interval_index.h:783
     - :ref:`View <example-intervalindex-all-63>`
   * - ``static bool all_values_integer(const std::vector<T>& values)``
     - static bool
     - pd_interval_index.h:63
     - 
   * - ``bool any(bool skipna = true) const``
     - bool
     - pd_interval_index.h:801
     - :ref:`View <example-intervalindex-any-64>`
   * - ``numpy::int64 argmax() const``
     - numpy::int64
     - pd_interval_index.h:848
     - :ref:`View <example-intervalindex-argmax-65>`
   * - ``numpy::int64 argmin() const``
     - numpy::int64
     - pd_interval_index.h:841
     - :ref:`View <example-intervalindex-argmin-66>`
   * - ``IntervalArray<T> arr(out, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:972
     - :ref:`View <example-intervalindex-arr-67>`
   * - ``IntervalArray<T> arr(result_vals, this->closed())``
     - IntervalArray<T>
     - pd_interval_index.h:1032
     - :ref:`View <example-intervalindex-arr-68>`
   * - ``std::unique_ptr<IndexBase> clone() const override``
     - std::unique_ptr<IndexBase>
     - pd_interval_index.h:561
     - :ref:`View <example-intervalindex-clone-69>`
   * - ``IntervalClosed closed() const``
     - IntervalClosed
     - pd_interval_index.h:377
     - :ref:`View <example-intervalindex-closed-70>`
   * - ``std::string closed_string() const``
     - std::string
     - pd_interval_index.h:384
     - :ref:`View <example-intervalindex-closed_string-71>`
   * - ``void compute_is_overlapping() const``
     - void
     - pd_interval_index.h:74
     - 
   * - ``BooleanArray contains(T value) const``
     - BooleanArray
     - pd_interval_index.h:456
     - :ref:`View <example-intervalindex-contains-72>`
   * - ``BooleanArray contains(const numpy::NDArray<T>& values) const``
     - BooleanArray
     - pd_interval_index.h:466
     - :ref:`View <example-intervalindex-contains-73>`
   * - ``IntervalIndex delete_(size_t loc) const``
     - IntervalIndex
     - pd_interval_index.h:1924
     - :ref:`View <example-intervalindex-delete_-74>`
   * - ``IntervalIndex delete_(const std::vector<size_t>& locs) const``
     - IntervalIndex
     - pd_interval_index.h:1948
     - :ref:`View <example-intervalindex-delete_-75>`
   * - ``std::string dtype_indent(14, ' ')``
     - std::string
     - pd_interval_index.h:704
     - 
   * - ``std::string dtype_name() const override``
     - std::string
     - pd_interval_index.h:544
     - :ref:`View <example-intervalindex-dtype_name-76>`
   * - ``oss << fmt_td(val->first) << ", " << fmt_td(val->second)``
     - oss <<
     - pd_interval_index.h:601
     - 
   * - ``oss << fmt_ts(val->first) << ", " << fmt_ts(val->second)``
     - oss <<
     - pd_interval_index.h:639
     - 
   * - ``std::vector<std::string> format(bool na_rep_as_string = true, std::nullptr_t formatter = nullptr, const std::string& na_rep = "NaN", bool name = false) const``
     - std::vector<std::string>
     - pd_interval_index.h:1286
     - :ref:`View <example-intervalindex-format-77>`
   * - ``std::string format_interval(size_t index) const``
     - std::string
     - pd_interval_index.h:575
     - :ref:`View <example-intervalindex-format_interval-78>`
   * - ``bool holds_integer() const``
     - bool
     - pd_interval_index.h:859
     - :ref:`View <example-intervalindex-holds_integer-79>`
   * - ``std::string indent(15, ' ')``
     - std::string
     - pd_interval_index.h:655
     - 
   * - ``std::string inferred_type() const override``
     - std::string
     - pd_interval_index.h:554
     - :ref:`View <example-intervalindex-inferred_type-80>`
   * - ``std::pair<T, T> item() const``
     - std::pair<T, T>
     - pd_interval_index.h:930
     - :ref:`View <example-intervalindex-item-81>`
   * - ``size_t memory_usage(bool deep = false) const``
     - size_t
     - pd_interval_index.h:921
     - :ref:`View <example-intervalindex-memory_usage-82>`
   * - ``FloatingArray<numpy::float64> mid() const``
     - FloatingArray<numpy::float64>
     - pd_interval_index.h:359
     - :ref:`View <example-intervalindex-mid-83>`
   * - ``BooleanArray overlaps(T other_left, T other_right) const``
     - BooleanArray
     - pd_interval_index.h:477
     - :ref:`View <example-intervalindex-overlaps-84>`
   * - ``BooleanArray overlaps(T other_left, T other_right, IntervalClosed other_closed) const``
     - BooleanArray
     - pd_interval_index.h:489
     - :ref:`View <example-intervalindex-overlaps-85>`
   * - ``IntervalIndex putmask(const numpy::NDArray<numpy::bool_>& mask, const std::pair<T, T>& value) const``
     - IntervalIndex
     - pd_interval_index.h:1670
     - :ref:`View <example-intervalindex-putmask-86>`
   * - ``IntervalIndex ravel() const``
     - IntervalIndex
     - pd_interval_index.h:1220
     - :ref:`View <example-intervalindex-ravel-87>`
   * - ``IntervalIndex repeat(size_t repeats, std::optional<int> axis = std::nullopt) const``
     - IntervalIndex
     - pd_interval_index.h:1199
     - :ref:`View <example-intervalindex-repeat-88>`
   * - ``std::string repr() const override``
     - std::string
     - pd_interval_index.h:716
     - :ref:`View <example-intervalindex-repr-89>`
   * - ``IntervalIndex result(\*this)``
     - IntervalIndex
     - pd_interval_index.h:762
     - :ref:`View <example-intervalindex-result-90>`
   * - ``numpy::NDArray<T> right() const``
     - numpy::NDArray<T>
     - pd_interval_index.h:351
     - :ref:`View <example-intervalindex-right-91>`
   * - ``IntervalIndex round(int decimals = 0) const``
     - IntervalIndex
     - pd_interval_index.h:1721
     - :ref:`View <example-intervalindex-round-92>`
   * - ``IntervalIndex set_closed(IntervalClosed new_closed) const``
     - IntervalIndex
     - pd_interval_index.h:503
     - :ref:`View <example-intervalindex-set_closed-93>`
   * - ``IntervalIndex set_closed(const std::string& new_closed) const``
     - IntervalIndex
     - pd_interval_index.h:511
     - :ref:`View <example-intervalindex-set_closed-94>`
   * - ``void set_subtype_override(const std::string& override_str)``
     - void
     - pd_interval_index.h:530
     - :ref:`View <example-intervalindex-set_subtype_override-95>`
   * - ``std::vector<size_t> slice_indexer( const std::optional<std::pair<T, T>>& start = std::nullopt, const std::optional<std::pair<T, T>>& end = std::nullopt, size_t step = 1) const``
     - std::vector<size_t>
     - pd_interval_index.h:1420
     - :ref:`View <example-intervalindex-slice_indexer-96>`
   * - ``std::pair<size_t, size_t> slice_locs( const std::optional<std::pair<T, T>>& start = std::nullopt, const std::optional<std::pair<T, T>>& end = std::nullopt, size_t step = 1) const``
     - std::pair<size_t, size_t>
     - pd_interval_index.h:1385
     - :ref:`View <example-intervalindex-slice_locs-97>`
   * - ``IntervalIndex sort(bool ascending = true) const``
     - IntervalIndex
     - pd_interval_index.h:1509
     - :ref:`View <example-intervalindex-sort-98>`
   * - ``std::pair<IntervalIndex, numpy::NDArray<numpy::int64>> sortlevel( int level = 0, bool ascending = true, const std::string& na_position = "last", bool sort_remaining = true) const``
     - std::pair<IntervalIndex, numpy::NDArray<numpy::int64>>
     - pd_interval_index.h:1522
     - :ref:`View <example-intervalindex-sortlevel-99>`
   * - ``StringMethods<IntervalIndex<T>> str() const``
     - StringMethods<IntervalIndex<T>>
     - pd_interval_index.h:743
     - :ref:`View <example-intervalindex-str-100>`
   * - ``IndexTypeId type_id() const override``
     - IndexTypeId
     - pd_interval_index.h:565
     - :ref:`View <example-intervalindex-type_id-101>`


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

The following examples are extracted from the test suite.

.. _example-intervalindex-intervalindex-0:

.. dropdown:: IntervalIndex (pd_test_5_all.cpp:1350)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1340
      :emphasize-lines: 11

          std::cout << " -> tests passed" << std::endl;
      }
      
      
      // --- cpp_f_test_pandas_advanced_indexing_compare_full_1053.cpp ---
      void f_test_pandas_advanced_indexing_compare_full_1053() {
          std::cout << "========= f_test_pandas_advanced_indexing_compare_full_1053 =======";
          int local_fail = 0;
          // Expected from pandas: str(pd.cut(range(4), bins=2).categories)
          std::string expected =
              "IntervalIndex([(-0.003, 1.5], (1.5, 3.0]], dtype='interval[float64, right]')";
      
          // Placeholder: cut() + categories accessor needed in C++ API
          // pandas_tests::check(result_categories.to_string() == expected, "binning.cut_categories.str");
          pandas_tests::check(true, "binning.cut_categories.str (expected value captured)", local_fail);
          if (local_fail > 0) {
              std::cout << "  [FAIL] : in f_test_pandas_advanced_indexing_compare_full_1053() : " << local_fail << " checks failed" << std::endl;
              throw std::runtime_error("f_test_pandas_advanced_indexing_compare_full_1053 failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-intervalindex-1:

.. dropdown:: IntervalIndex (pd_test_5_all.cpp:1350)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1340
      :emphasize-lines: 11

          std::cout << " -> tests passed" << std::endl;
      }
      
      
      // --- cpp_f_test_pandas_advanced_indexing_compare_full_1053.cpp ---
      void f_test_pandas_advanced_indexing_compare_full_1053() {
          std::cout << "========= f_test_pandas_advanced_indexing_compare_full_1053 =======";
          int local_fail = 0;
          // Expected from pandas: str(pd.cut(range(4), bins=2).categories)
          std::string expected =
              "IntervalIndex([(-0.003, 1.5], (1.5, 3.0]], dtype='interval[float64, right]')";
      
          // Placeholder: cut() + categories accessor needed in C++ API
          // pandas_tests::check(result_categories.to_string() == expected, "binning.cut_categories.str");
          pandas_tests::check(true, "binning.cut_categories.str (expected value captured)", local_fail);
          if (local_fail > 0) {
              std::cout << "  [FAIL] : in f_test_pandas_advanced_indexing_compare_full_1053() : " << local_fail << " checks failed" << std::endl;
              throw std::runtime_error("f_test_pandas_advanced_indexing_compare_full_1053 failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-intervalindex-2:

.. dropdown:: IntervalIndex (pd_test_5_all.cpp:1350)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1340
      :emphasize-lines: 11

          std::cout << " -> tests passed" << std::endl;
      }
      
      
      // --- cpp_f_test_pandas_advanced_indexing_compare_full_1053.cpp ---
      void f_test_pandas_advanced_indexing_compare_full_1053() {
          std::cout << "========= f_test_pandas_advanced_indexing_compare_full_1053 =======";
          int local_fail = 0;
          // Expected from pandas: str(pd.cut(range(4), bins=2).categories)
          std::string expected =
              "IntervalIndex([(-0.003, 1.5], (1.5, 3.0]], dtype='interval[float64, right]')";
      
          // Placeholder: cut() + categories accessor needed in C++ API
          // pandas_tests::check(result_categories.to_string() == expected, "binning.cut_categories.str");
          pandas_tests::check(true, "binning.cut_categories.str (expected value captured)", local_fail);
          if (local_fail > 0) {
              std::cout << "  [FAIL] : in f_test_pandas_advanced_indexing_compare_full_1053() : " << local_fail << " checks failed" << std::endl;
              throw std::runtime_error("f_test_pandas_advanced_indexing_compare_full_1053 failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-intervalindex-3:

.. dropdown:: IntervalIndex (pd_test_5_all.cpp:1350)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1340
      :emphasize-lines: 11

          std::cout << " -> tests passed" << std::endl;
      }
      
      
      // --- cpp_f_test_pandas_advanced_indexing_compare_full_1053.cpp ---
      void f_test_pandas_advanced_indexing_compare_full_1053() {
          std::cout << "========= f_test_pandas_advanced_indexing_compare_full_1053 =======";
          int local_fail = 0;
          // Expected from pandas: str(pd.cut(range(4), bins=2).categories)
          std::string expected =
              "IntervalIndex([(-0.003, 1.5], (1.5, 3.0]], dtype='interval[float64, right]')";
      
          // Placeholder: cut() + categories accessor needed in C++ API
          // pandas_tests::check(result_categories.to_string() == expected, "binning.cut_categories.str");
          pandas_tests::check(true, "binning.cut_categories.str (expected value captured)", local_fail);
          if (local_fail > 0) {
              std::cout << "  [FAIL] : in f_test_pandas_advanced_indexing_compare_full_1053() : " << local_fail << " checks failed" << std::endl;
              throw std::runtime_error("f_test_pandas_advanced_indexing_compare_full_1053 failed");
          }
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-from_arrays-4:

.. dropdown:: from_arrays (pd_test_1_all.cpp:1994)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1984
      :emphasize-lines: 11

      
      // ============================================================================
      // Test: from_arrays factory method
      // ============================================================================
      void test_from_arrays() {
          std::cout << "========= IntervalArray: from_arrays ======================= ";
      
          std::vector<numpy::int64> left_vec = {0, 10, 20};
          std::vector<numpy::int64> right_vec = {5, 15, 25};
      
          auto arr = pandas::IntervalArrayInt64::from_arrays(left_vec, right_vec);
      
          if (arr.size() != 3) {
              std::cout << "[FAIL] : in test_from_arrays() : size" << std::endl;
              return;
          }
      
          auto interval1 = arr[1];
          if (!interval1.has_value() || interval1->first != 10 || interval1->second != 15) {
              std::cout << "[FAIL] : in test_from_arrays() : interval values" << std::endl;
              return;

.. _example-intervalindex-from_arrays-5:

.. dropdown:: from_arrays (pd_test_1_all.cpp:1994)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1984
      :emphasize-lines: 11

      
      // ============================================================================
      // Test: from_arrays factory method
      // ============================================================================
      void test_from_arrays() {
          std::cout << "========= IntervalArray: from_arrays ======================= ";
      
          std::vector<numpy::int64> left_vec = {0, 10, 20};
          std::vector<numpy::int64> right_vec = {5, 15, 25};
      
          auto arr = pandas::IntervalArrayInt64::from_arrays(left_vec, right_vec);
      
          if (arr.size() != 3) {
              std::cout << "[FAIL] : in test_from_arrays() : size" << std::endl;
              return;
          }
      
          auto interval1 = arr[1];
          if (!interval1.has_value() || interval1->first != 10 || interval1->second != 15) {
              std::cout << "[FAIL] : in test_from_arrays() : interval values" << std::endl;
              return;

.. _example-intervalindex-from_breaks-6:

.. dropdown:: from_breaks (pd_test_1_all.cpp:1955)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1945
      :emphasize-lines: 11

      }
      
      // ============================================================================
      // Test: from_breaks factory method
      // ============================================================================
      void test_from_breaks() {
          std::cout << "========= IntervalArray: from_breaks ======================= ";
      
          // Create from breaks
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0, 3.0, 4.0};
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks);
      
          if (arr.size() != 4) {
              std::cout << "[FAIL] : in test_from_breaks() : size should be n-1" << std::endl;
              return;
          }
      
          // Check intervals
          auto interval0 = arr[0];
          if (!interval0.has_value() || interval0->first != 0.0 || interval0->second != 1.0) {
              std::cout << "[FAIL] : in test_from_breaks() : first interval" << std::endl;

.. _example-intervalindex-from_breaks-7:

.. dropdown:: from_breaks (pd_test_1_all.cpp:1955)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1945
      :emphasize-lines: 11

      }
      
      // ============================================================================
      // Test: from_breaks factory method
      // ============================================================================
      void test_from_breaks() {
          std::cout << "========= IntervalArray: from_breaks ======================= ";
      
          // Create from breaks
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0, 3.0, 4.0};
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks);
      
          if (arr.size() != 4) {
              std::cout << "[FAIL] : in test_from_breaks() : size should be n-1" << std::endl;
              return;
          }
      
          // Check intervals
          auto interval0 = arr[0];
          if (!interval0.has_value() || interval0->first != 0.0 || interval0->second != 1.0) {
              std::cout << "[FAIL] : in test_from_breaks() : first interval" << std::endl;

.. _example-intervalindex-from_tuples-8:

.. dropdown:: from_tuples (pd_test_1_all.cpp:2022)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2012
      :emphasize-lines: 11

      // ============================================================================
      void test_from_tuples() {
          std::cout << "========= IntervalArray: from_tuples ======================= ";
      
          std::vector<std::pair<numpy::float64, numpy::float64>> tuples = {
              {0.0, 1.5},
              {1.5, 3.0},
              {3.0, 4.5}
          };
      
          auto arr = pandas::IntervalArrayFloat64::from_tuples(tuples);
      
          if (arr.size() != 3) {
              std::cout << "[FAIL] : in test_from_tuples() : size" << std::endl;
              return;
          }
      
          auto interval2 = arr[2];
          if (!interval2.has_value() || interval2->first != 3.0 || interval2->second != 4.5) {
              std::cout << "[FAIL] : in test_from_tuples() : interval values" << std::endl;
              return;

.. _example-intervalindex-get_indexer_non_unique-9:

.. dropdown:: get_indexer_non_unique (pd_test_3_all.cpp:739)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 729
      :emphasize-lines: 11

          if (indexer.getElementAt({1}) != 3) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_indexers() : 'd' should be at index 3" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_indexers failed: 'd' index");
          }
          // "f" doesn't exist -> -1
          if (indexer.getElementAt({2}) != -1) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_indexers() : 'f' should be -1" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_indexers failed: 'f' index");
          }
      
          // Test get_indexer_non_unique()
          std::vector<std::string> target2 = {"a", "c", "z"};  // "z" doesn't exist
          pandas::Index<std::string> target_idx(target2);
          auto [indexer2, missing] = idx.get_indexer_non_unique(target_idx);
      
          if (indexer2.getSize() < 2) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_indexers() : get_indexer_non_unique size too small" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_indexers failed: get_indexer_non_unique size");
          }
      
          // Test slice_indexer()

.. _example-intervalindex-get_level_values-10:

.. dropdown:: get_level_values (pd_test_3_all.cpp:4524)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 4514
      :emphasize-lines: 11

          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_interval_index_get_level_values_droplevel() {
          std::cout << "========= IntervalIndex.get_level_values/droplevel() ";
      
          pandas::IntervalIndex64 idx = pandas::IntervalIndex64::from_breaks({0, 10, 20, 30});
      
          // get_level_values(0) should work
          pandas::IntervalIndex64 level_vals = idx.get_level_values(0);
          if (level_vals.size() != idx.size()) {
              throw std::runtime_error("get_level_values(0) size mismatch");
          }
      
          // get_level_values(1) should throw
          bool threw = false;
          try {
              idx.get_level_values(1);
          } catch (const std::out_of_range&) {

.. _example-intervalindex-get_slice_bound-11:

.. dropdown:: get_slice_bound (pd_test_3_all.cpp:3644)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3634
      :emphasize-lines: 11

          formatted = idx.format(custom_formatter);
      
          if (formatted[0] != "val:1") {
              throw std::runtime_error("custom formatter failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_get_slice_bound() {
          std::cout << "========= Index.get_slice_bound() ==================";
      
          pandas::Index<numpy::int64> idx({10, 20, 30, 40, 50});
      
          // Exact match, left side
          size_t bound = idx.get_slice_bound(30, "left");
          if (bound != 2) {
              throw std::runtime_error("left bound for 30 should be 2");
          }
      
          // Exact match, right side

.. _example-intervalindex-get_string-12:

.. dropdown:: get_string (pd_test_3_all.cpp:27746)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 27736
      :emphasize-lines: 11

              }
          }
      
          pandas::Series<numpy::int64> si({10, 20, 30}, "ints");
          auto result2 = si.astype("str");
          auto* str_s2 = dynamic_cast<pandas::Series<std::string>*>(result2.get());
          if (!str_s2) {
              std::cout << "    FAIL: expected Series<string> from int" << std::endl;
              fail++;
          } else {
              if (str_s2->get_string(0) != "10") {
                  std::cout << "    FAIL: expected '10', got '" << str_s2->get_string(0) << "'" << std::endl;
                  fail++;
              }
          }
      
          if (fail == 0) std::cout << "    OK" << std::endl;
      }
      
      void pd_test_astype_datetime_to_string() {
          std::cout << "  -- pd_test_astype_datetime_to_string --" << std::endl;

.. _example-intervalindex-get_value_str-13:

.. dropdown:: get_value_str (pd_test_1_all.cpp:4665)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 4655
      :emphasize-lines: 11

                  auto corr_df = df.corr();
      
                  // Check dimensions
                  bool passed = corr_df.nrows() == 2 && corr_df.ncols() == 2;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_aggregation_dataframe_corr() : corr should be 2x2" << std::endl;
                      throw std::runtime_error("pd_test_aggregation_dataframe_corr failed: corr should be 2x2");
                  }
      
                  // Diagonal should be 1.0
                  std::string aa = corr_df["A"].get_value_str(0);
                  passed = std::abs(std::stod(aa) - 1.0) < 0.001;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_aggregation_dataframe_corr() : diagonal should be 1.0" << std::endl;
                      throw std::runtime_error("pd_test_aggregation_dataframe_corr failed: diagonal should be 1.0");
                  }
      
                  // A-B correlation should be 1.0 (perfect correlation)
                  std::string ab = corr_df["B"].get_value_str(0);
                  passed = std::abs(std::stod(ab) - 1.0) < 0.001;
                  if (!passed) {

.. _example-intervalindex-where-14:

.. dropdown:: where (pd_test_1_all.cpp:22018)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 22008
      :emphasize-lines: 11

                  data["B"] = {5.0, 6.0, 7.0, 8.0};
                  pandas::DataFrame df(data);
      
                  // Create condition DataFrame (values > 2)
                  std::map<std::string, std::vector<numpy::bool_>> cond_data;
                  cond_data["A"] = {false, false, true, true};   // 1<=2, 2<=2, 3>2, 4>2
                  cond_data["B"] = {true, true, true, true};     // all >2
                  pandas::DataFrame cond(cond_data);
      
                  // Apply where with replacement value -1
                  pandas::DataFrame result = df.where(cond, -1.0);
      
                  // Get column index for A - it's sorted alphabetically in std::map
                  size_t col_a_idx = df.get_column_index("A");
                  size_t col_b_idx = df.get_column_index("B");
      
                  bool passed = true;
                  std::string error_msg;
      
                  // Check A column values
                  std::string a0 = result.iat<double>(0, col_a_idx) == -1.0 ? "ok" : "fail";

.. _example-intervalindex-drop_duplicates-15:

.. dropdown:: drop_duplicates (pd_test_1_all.cpp:6639)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6629
      :emphasize-lines: 11

                      }
                  }
      
                  // Test drop_duplicates
                  {
                      std::map<std::string, std::vector<numpy::int64>> dup_data;
                      dup_data["A"] = {1, 1, 2, 2};
                      dup_data["B"] = {1, 1, 2, 3};
                      pandas::DataFrame df_dup(dup_data);
      
                      auto deduped = df_dup.drop_duplicates();
                      // Rows 0 and 1 are duplicates (A=1, B=1), so should have 3 rows
                      if (deduped.nrows() != 3) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_manipulation() : drop_duplicates nrows != 3, got " << deduped.nrows() << std::endl;
                          throw std::runtime_error("pd_test_dataframe_manipulation failed: drop_duplicates");
                      }
                  }
      
                  // Test assign
                  {
                      std::map<std::string, std::vector<numpy::int64>> assign_data;

.. _example-intervalindex-droplevel-16:

.. dropdown:: droplevel (pd_test_1_all.cpp:14428)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 14418
      :emphasize-lines: 11

              void pd_test_multiindex_droplevel() {
                  std::cout << "========= droplevel =================================== ";
      
                  std::vector<std::vector<std::string>> arrays = {
                      {"a", "a", "b"},
                      {"x", "y", "z"},
                      {"1", "2", "3"}
                  };
      
                  pandas::MultiIndex mi = pandas::MultiIndex::from_arrays<std::string>(arrays);
                  pandas::MultiIndex dropped = mi.droplevel(1);
      
                  bool passed = true;
      
                  if (dropped.nlevels() != 2) {
                      std::cout << "  [FAIL] : nlevels should be 2 after drop" << std::endl;
                      passed = false;
                  }
      
                  // Check remaining levels
                  auto tup = dropped[0];

.. _example-intervalindex-insert-17:

.. dropdown:: insert (pd_test_1_all.cpp:12028)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12018
      :emphasize-lines: 11

                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      
              void pd_test_index_insert_delete() {
                  std::cout << "========= insert and delete ===========================";
      
                  pandas::Index<numpy::int64> idx{1, 2, 4, 5};
      
                  auto inserted = idx.insert(2, 3);
                  bool passed = (inserted.size() == 5);
                  passed = passed && (inserted[2] == 3);
      
                  auto deleted = inserted.delete_(2);
                  passed = passed && (deleted.size() == 4);
                  passed = passed && deleted.equals(idx);
      
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_index_insert_delete() : insert/delete failed" << std::endl;
                      throw std::runtime_error("pd_test_index_insert_delete failed");

.. _example-intervalindex-reindex-18:

.. dropdown:: reindex (pd_test_1_all.cpp:6708)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 6698
      :emphasize-lines: 11

                      }
                  }
      
                  // Test reindex rows
                  {
                      std::map<std::string, std::vector<double>> data;
                      data["A"] = {1.0, 2.0, 3.0};
                      pandas::DataFrame df(data);
                      df = df.set_axis({"x", "y", "z"}, 0);
      
                      auto reindexed = df.reindex({"x", "z", "w"}, 0);
                      if (reindexed.nrows() != 3) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_index_ops() : reindex wrong nrows" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_index_ops failed: reindex nrows");
                      }
                      // 'w' should have NaN
                      std::string val = reindexed["A"].get_value_str(2);
                      if (!std::isnan(std::stod(val))) {
                          std::cout << "  [FAIL] : in pd_test_dataframe_index_ops() : missing label should be NaN" << std::endl;
                          throw std::runtime_error("pd_test_dataframe_index_ops failed: reindex NaN");
                      }

.. _example-intervalindex-rename-19:

.. dropdown:: rename (pd_test_1_all.cpp:5816)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5806
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_categorical_index_rename() {
          std::cout << "========= rename ======================================";
      
          pandas::CategoricalArray arr({"x", "y"});
          pandas::CategoricalIndex idx(arr, "old_name");
      
          pandas::CategoricalIndex renamed = idx.rename("new_name");
      
          bool passed = (renamed.name().has_value() && *renamed.name() == "new_name" &&
                         renamed.size() == idx.size() && renamed.categories() == idx.categories());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_rename()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_rename failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-set_names-20:

.. dropdown:: set_names (pd_test_1_all.cpp:14519)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 14509
      :emphasize-lines: 11

                  std::cout << "-> tests passed" << std::endl;
              }
      
              void pd_test_multiindex_set_names() {
                  std::cout << "========= set_names =================================== ";
      
                  std::vector<std::vector<std::string>> arrays = {{"a", "b"}, {"x", "y"}};
                  pandas::MultiIndex mi = pandas::MultiIndex::from_arrays<std::string>(arrays);
      
                  std::vector<std::optional<std::string>> new_names = {"level_a", "level_b"};
                  pandas::MultiIndex named = mi.set_names(new_names);
      
                  bool passed = (named.names()[0] == "level_a" && named.names()[1] == "level_b");
      
                  if (!passed) {
                      std::cout << "  [FAIL] : names not set correctly" << std::endl;
                      throw std::runtime_error("pd_test_multiindex_set_names failed");
                  }
      
                  std::cout << "-> tests passed" << std::endl;
              }

.. _example-intervalindex-max-21:

.. 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-intervalindex-min-22:

.. 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-intervalindex-groupby-23:

.. dropdown:: groupby (pd_test_1_all.cpp:11495)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 11485
      :emphasize-lines: 11

                  std::cout << "========= GroupBy basic =========================";
      
                  // Create DataFrame with category column
                  std::map<std::string, std::vector<double>> data = {
                      {"category", {1.0, 1.0, 2.0, 2.0, 2.0}},
                      {"value", {10.0, 20.0, 30.0, 40.0, 50.0}}
                  };
                  pandas::DataFrame df(data);
      
                  // Test groupby
                  auto grouped = df.groupby("category");
      
                  bool passed = grouped.ngroups() == 2;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_groupby_basic() : ngroups should be 2" << std::endl;
                      throw std::runtime_error("pd_test_groupby_basic failed: ngroups should be 2");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      

.. _example-intervalindex-groupby-24:

.. dropdown:: groupby (pd_test_1_all.cpp:11495)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 11485
      :emphasize-lines: 11

                  std::cout << "========= GroupBy basic =========================";
      
                  // Create DataFrame with category column
                  std::map<std::string, std::vector<double>> data = {
                      {"category", {1.0, 1.0, 2.0, 2.0, 2.0}},
                      {"value", {10.0, 20.0, 30.0, 40.0, 50.0}}
                  };
                  pandas::DataFrame df(data);
      
                  // Test groupby
                  auto grouped = df.groupby("category");
      
                  bool passed = grouped.ngroups() == 2;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_groupby_basic() : ngroups should be 2" << std::endl;
                      throw std::runtime_error("pd_test_groupby_basic failed: ngroups should be 2");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      

.. _example-intervalindex-map-25:

.. dropdown:: map (pd_test_1_all.cpp:5839)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5829
      :emphasize-lines: 11

      // Map Tests
      // ============================================================================
      
      void pd_test_categorical_index_map() {
          std::cout << "========= map =========================================";
      
          pandas::CategoricalArray arr({"yes", "no", "yes"});
          pandas::CategoricalIndex idx(arr);
      
          std::unordered_map<std::string, std::string> mapping = {{"yes", "1"}, {"no", "0"}};
          pandas::CategoricalIndex mapped = idx.map(mapping);
      
          bool passed = (mapped.has_category("1") && mapped.has_category("0") &&
                         !mapped.has_category("yes") && !mapped.has_category("no"));
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_map()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_map failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-subtype_override-26:

.. dropdown:: subtype_override (pd_test_3_all.cpp:24889)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24879
      :emphasize-lines: 11

          return dataframe_tests_bdate_timedelta_range::pd_test_bdate_timedelta_range_main();
      }
      // ------------------- pd_test_bdate_timedelta_range (end) ---------------------------
      
      // ------------------- pd_test_interval_type_inference (begin) ---------------------------
      namespace dataframe_tests_interval_type_inference {
      
      void pd_test_interval_type_inference_breaks_int() {
          std::cout << "========= interval_type_inference_breaks_int ======================= ";
          auto idx = pandas::IntervalIndex<double>::from_breaks({0.0, 1.0, 2.0, 3.0});
          if (idx.subtype_override() != "int64")
              throw std::runtime_error("expected subtype_override 'int64', got '" + idx.subtype_override() + "'");
          std::string dtype = idx.dtype_name();
          if (dtype.find("int64") == std::string::npos)
              throw std::runtime_error("expected dtype containing 'int64', got '" + dtype + "'");
          std::string fmt = idx.format_interval(0);
          if (fmt.find('.') != std::string::npos)
              throw std::runtime_error("expected integer format without decimal, got '" + fmt + "'");
          std::cout << " -> tests passed" << std::endl;
      }
      

.. _example-intervalindex-left-27:

.. dropdown:: left (pd_test_1_all.cpp:1909)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1899
      :emphasize-lines: 11

          if (empty.size() != 0) {
              std::cout << "[FAIL] : in test_constructors() : default constructor size" << std::endl;
              return;
          }
          if (empty.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_constructors() : default closure" << std::endl;
              return;
          }
      
          // Constructor from left/right arrays
          numpy::NDArray<numpy::float64> left(std::vector<size_t>{3});
          numpy::NDArray<numpy::float64> right(std::vector<size_t>{3});
          left.setElementAt({0}, 0.0);  right.setElementAt({0}, 1.0);
          left.setElementAt({1}, 1.0);  right.setElementAt({1}, 2.0);
          left.setElementAt({2}, 2.0);  right.setElementAt({2}, 3.0);
      
          pandas::IntervalArrayFloat64 arr1(left, right);
          if (arr1.size() != 3) {
              std::cout << "[FAIL] : in test_constructors() : array size" << std::endl;
              return;
          }

.. _example-intervalindex-length-28:

.. dropdown:: length (pd_test_1_all.cpp:2137)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2127
      :emphasize-lines: 11

          auto mid0 = mid_arr[0];
          auto mid1 = mid_arr[1];
          auto mid2 = mid_arr[2];
          if (!mid0.has_value() || std::abs(mid0.value() - 1.0) > 1e-10 ||
              !mid1.has_value() || std::abs(mid1.value() - 3.5) > 1e-10 ||
              !mid2.has_value() || std::abs(mid2.value() - 7.5) > 1e-10) {
              std::cout << "[FAIL] : in test_left_right_mid_length() : mid()" << std::endl;
              return;
          }
      
          // Test length()
          auto len_arr = arr.length();
          if (len_arr.getElementAt({0}) != 2.0 ||
              len_arr.getElementAt({1}) != 3.0 ||
              len_arr.getElementAt({2}) != 5.0) {
              std::cout << "[FAIL] : in test_left_right_mid_length() : length()" << std::endl;
              return;
          }
      
          std::cout << "-> tests passed" << std::endl;
      }

.. _example-intervalindex-searchsorted-29:

.. dropdown:: searchsorted (pd_test_1_all.cpp:18958)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 18948
      :emphasize-lines: 11

      
          // =========================================================================
          // Search Tests
          // =========================================================================
      
          void pd_test_range_index_searchsorted() {
              std::cout << "========= searchsorted ================================ ";
      
              pandas::RangeIndex ri(0, 10, 2);  // [0, 2, 4, 6, 8]
      
              bool passed = (ri.searchsorted(4, "left") == 2 &&
                            ri.searchsorted(4, "right") == 3 &&
                            ri.searchsorted(3, "left") == 2 &&   // 3 would go between 2 and 4
                            ri.searchsorted(-1, "left") == 0 &&  // Before all
                            ri.searchsorted(10, "left") == 5);   // After all
      
              if (!passed) {
                  std::cout << "  [FAIL] : searchsorted" << std::endl;
                  throw std::runtime_error("pd_test_range_index_searchsorted failed");
              }
      

.. _example-intervalindex-to_frame-30:

.. dropdown:: to_frame (pd_test_3_all.cpp:4931)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 4921
      :emphasize-lines: 11

      
          size_t usage = mi.memory_usage(true);
          if (usage == 0) {
              throw std::runtime_error("memory_usage() should return > 0");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_multiindex_to_frame() {
          std::cout << "========= MultiIndex.to_frame() =======================";
      
          std::vector<std::vector<std::string>> arrays = {{"a", "b"}, {"x", "y"}};
          std::vector<std::optional<std::string>> names = {"first", "second"};
          pandas::MultiIndex mi = pandas::MultiIndex::from_arrays<std::string>(arrays, names);
      
          auto frame = mi.to_frame();
          if (frame.find("first") == frame.end() || frame.find("second") == frame.end()) {
              throw std::runtime_error("to_frame() missing columns");
          }
      

.. _example-intervalindex-transpose-31:

.. dropdown:: transpose (pd_test_1_all.cpp:16648)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 16638
      :emphasize-lines: 11

                      std::cout << "  [FAIL] : in pd_test_ndframe_transpose() : T_() size" << std::endl;
                      throw std::runtime_error("pd_test_ndframe_transpose failed: T_() size");
                  }
      
                  passed = transposed[0] == 1 && transposed[1] == 2 && transposed[2] == 3;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_ndframe_transpose() : T_() values" << std::endl;
                      throw std::runtime_error("pd_test_ndframe_transpose failed: T_() values");
                  }
      
                  // Test transpose() alias
                  auto transposed2 = s.transpose();
                  passed = transposed2.size() == s.size();
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_ndframe_transpose() : transpose() size" << std::endl;
                      throw std::runtime_error("pd_test_ndframe_transpose failed: transpose() size");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      

.. _example-intervalindex-join-32:

.. dropdown:: join (pd_test_1_all.cpp:12353)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12343
      :emphasize-lines: 11

      
                  std::cout << " -> tests passed" << std::endl;
              }
      
              void pd_test_index_join() {
                  std::cout << "========= join ========================================";
      
                  pandas::Index<numpy::int64> idx1{1, 2, 3};
                  pandas::Index<numpy::int64> idx2{2, 3, 4};
      
                  auto [inner_joined, left_idx, right_idx] = idx1.join(idx2, "inner");
                  bool passed = (inner_joined.size() == 2);  // {2, 3}
      
                  auto [outer_joined, ol_idx, or_idx] = idx1.join(idx2, "outer");
                  passed = passed && (outer_joined.size() == 4);  // {1, 2, 3, 4}
      
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_index_join() : join failed" << std::endl;
                      throw std::runtime_error("pd_test_index_join failed");
                  }
      

.. _example-intervalindex-asof-33:

.. dropdown:: asof (pd_test_2_all.cpp:366)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 356
      :emphasize-lines: 11

      
              std::cout << "====================================== [OK] pd_test_add_prefix test suite ========================== " << std::endl;
              return 0;
          }
      
      } // namespace dataframe_tests
      // ------------------- pd_test_add_prefix.cpp (end) -----------------------------
      
      // ------------------- pd_test_asof.cpp (start) -----------------------------
      // dataframe_tests/pd_test_asof.cpp
      // Test for DataFrame.asof() method
      
      #include <iostream>
      #include <cmath>
      #include <stdexcept>
      #include <limits>
      #include "../pandas/pd_dataframe.h"
      
      // CRITICAL: No using namespace directives
      
      namespace dataframe_tests {

.. _example-intervalindex-asof_locs-34:

.. dropdown:: asof_locs (pd_test_3_all.cpp:3557)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3547
      :emphasize-lines: 11

              throw std::runtime_error("all() should be true for empty index");
          }
          if (empty_idx.any()) {
              throw std::runtime_error("any() should be false for empty index");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_asof() {
          std::cout << "========= Index.asof()/asof_locs() =================";
      
          // Test with monotonically increasing index
          pandas::Index<numpy::int64> idx({10, 20, 30, 40, 50});
      
          // Exact match
          auto result = idx.asof(30);
          if (!result.has_value() || result.value() != 30) {
              throw std::runtime_error("asof() exact match should return 30");
          }
      

.. _example-intervalindex-diff-35:

.. dropdown:: diff (pd_test_1_all.cpp:5171)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5161
      :emphasize-lines: 11

              }
      
              void pd_test_arithmetic_dataframe_diff_shift() {
                  std::cout << "========= DataFrame diff/shift ==================";
      
                  std::map<std::string, std::vector<double>> data;
                  data["A"] = {1.0, 3.0, 6.0, 10.0};
                  pandas::DataFrame df(data);
      
                  // diff: [NaN, 2, 3, 4]
                  auto d = df.diff();
                  std::string val = d["A"].get_value_str(1);
                  bool passed = std::abs(std::stod(val) - 2.0) < 0.001;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_arithmetic_dataframe_diff_shift() : diff failed" << std::endl;
                      throw std::runtime_error("pd_test_arithmetic_dataframe_diff_shift failed: diff failed");
                  }
      
                  // First element should be NaN
                  val = d["A"].get_value_str(0);
                  passed = std::isnan(std::stod(val));

.. _example-intervalindex-shift-36:

.. dropdown:: shift (pd_test_1_all.cpp:5188)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5178
      :emphasize-lines: 11

      
                  // First element should be NaN
                  val = d["A"].get_value_str(0);
                  passed = std::isnan(std::stod(val));
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_arithmetic_dataframe_diff_shift() : diff NaN failed" << std::endl;
                      throw std::runtime_error("pd_test_arithmetic_dataframe_diff_shift failed: diff NaN failed");
                  }
      
                  // shift: [NaN, 1, 3, 6]
                  auto s = df.shift();
                  val = s["A"].get_value_str(1);
                  passed = std::abs(std::stod(val) - 1.0) < 0.001;
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_arithmetic_dataframe_diff_shift() : shift failed" << std::endl;
                      throw std::runtime_error("pd_test_arithmetic_dataframe_diff_shift failed: shift failed");
                  }
      
                  std::cout << " -> tests passed" << std::endl;
              }
      

.. _example-intervalindex-to_flat_index-37:

.. dropdown:: to_flat_index (pd_test_1_all.cpp:14733)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 14723
      :emphasize-lines: 11

      
              void pd_test_multiindex_to_flat_index() {
                  std::cout << "========= to_flat_index =============================== ";
      
                  std::vector<std::vector<std::string>> arrays = {
                      {"a", "b"},
                      {"x", "y"}
                  };
      
                  pandas::MultiIndex mi = pandas::MultiIndex::from_arrays<std::string>(arrays);
                  auto flat = mi.to_flat_index();
      
                  bool passed = (flat.size() == 2 &&
                                flat[0][0] == "a" && flat[0][1] == "x" &&
                                flat[1][0] == "b" && flat[1][1] == "y");
      
                  if (!passed) {
                      std::cout << "  [FAIL] : to_flat_index incorrect" << std::endl;
                      throw std::runtime_error("pd_test_multiindex_to_flat_index failed");
                  }
      

.. _example-intervalindex-to_numpy-38:

.. 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-intervalindex-to_series-39:

.. dropdown:: to_series (pd_test_3_all.cpp:5788)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5778
      :emphasize-lines: 11

              throw std::runtime_error("to_frame use_index should be false when index=false");
          }
          if (frame3.column_name != "0") {
              throw std::runtime_error("to_frame column_name should be '0' when no name");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_period_index_to_series() {
          std::cout << "========= PeriodIndex.to_series() =====================";
      
          pandas::PeriodIndex idx = make_period_index({1, 2, 3}, "M").rename("periods");
      
          // Test to_series() with default parameters
          pandas::PeriodIndex::SeriesData series = idx.to_series();
      
          // values should have same size
          if (series.values.size() != 3) {
              throw std::runtime_error("to_series values size should be 3");
          }

.. _example-intervalindex-to_string-40:

.. 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-intervalindex-to_tuples-41:

.. dropdown:: to_tuples (pd_test_1_all.cpp:13037)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 13027
      :emphasize-lines: 11

          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_index_to_tuples() {
          std::cout << "========= to_tuples =========================";
      
          auto idx = pandas::IntervalIndex64::from_breaks({0, 1, 2, 3});
      
          auto tuples = idx.to_tuples();
      
          bool passed = (tuples.size() == 3 &&
                         tuples[0].has_value() && tuples[0]->first == 0 && tuples[0]->second == 1 &&
                         tuples[1].has_value() && tuples[1]->first == 1 && tuples[1]->second == 2 &&
                         tuples[2].has_value() && tuples[2]->first == 2 && tuples[2]->second == 3);
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_interval_index_to_tuples() : check failed" << std::endl;
              throw std::runtime_error("pd_test_interval_index_to_tuples failed");
          }
      

.. _example-intervalindex-tolist-42:

.. dropdown:: tolist (pd_test_3_all.cpp:2300)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2290
      :emphasize-lines: 11

              threw = true;
          }
          if (!threw) {
              throw std::runtime_error("swapaxes should throw for invalid axes");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_categorical_to_list() {
          std::cout << "========= CategoricalArray.to_list()/tolist() =========";
      
          std::vector<std::optional<std::string>> values = {"a", "b", std::nullopt, "c"};
          pandas::CategoricalArray arr(values);
      
          auto list = arr.to_list();
          if (list.size() != 4 || *list[0] != "a" || *list[1] != "b" ||
              list[2].has_value() || *list[3] != "c") {
              throw std::runtime_error("to_list failed");
          }
      

.. _example-intervalindex-astype-43:

.. dropdown:: astype (pd_test_1_all.cpp:21292)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 21282
      :emphasize-lines: 11

                  std::cout << "========= astype all columns to float64 =============";
      
                  // Create DataFrame with int64 columns
                  std::map<std::string, std::vector<numpy::int64>> data;
                  data["A"] = {1, 2, 3, 4, 5};
                  data["B"] = {10, 20, 30, 40, 50};
      
                  pandas::DataFrame df(data);
      
                  // Convert all columns to float64
                  pandas::DataFrame df_float = df.astype("float64");
      
                  // Verify dtype changed
                  pandas::Series<std::string> dtypes = df_float.dtypes();
      
                  bool passed = true;
                  if (dtypes[static_cast<size_t>(0)] != "float64") {
                      std::cout << "  [FAIL] : in pd_test_astype_all_columns_to_float64() : column A dtype is " << dtypes[static_cast<size_t>(0)] << ", expected float64" << std::endl;
                      passed = false;
                  }
                  if (dtypes[static_cast<size_t>(1)] != "float64") {

.. _example-intervalindex-copy-44:

.. 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-intervalindex-infer_objects-45:

.. dropdown:: infer_objects (pd_test_1_all.cpp:27595)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 27585
      :emphasize-lines: 11

                  // Create DataFrame with string column containing integers
                  std::map<std::string, std::vector<std::string>> data;
                  data["A"] = {"1", "2", "3", "4", "5"};
      
                  pandas::DataFrame df(data);
      
                  // Before inference, dtype should be string/object
                  std::string before_dtype = df["A"].dtype_name();
      
                  // Apply infer_objects
                  pandas::DataFrame result = df.infer_objects();
      
                  // After inference, dtype should be int64
                  std::string after_dtype = result["A"].dtype_name();
      
                  bool passed = (after_dtype == "int64");
                  if (!passed) {
                      std::cout << "  [FAIL] : in pd_test_infer_objects_integer_column() : expected int64, got " << after_dtype << std::endl;
                      throw std::runtime_error("pd_test_infer_objects_integer_column failed");
                  }
      

.. _example-intervalindex-view-46:

.. dropdown:: view (pd_test_3_all.cpp:2147)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2137
      :emphasize-lines: 11

              throw std::runtime_error("memory_usage shallow too small");
          }
          if (deep < shallow) {
              throw std::runtime_error("memory_usage deep should be >= shallow");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_categorical_ravel_view() {
          std::cout << "========= CategoricalArray.ravel()/view() =============";
      
          std::vector<std::optional<std::string>> values = {"a", "b", "c"};
          pandas::CategoricalArray arr(values);
      
          auto raveled = arr.ravel();
          if (raveled.size() != 3 || !raveled.equals(arr)) {
              throw std::runtime_error("ravel failed");
          }
      
          auto viewed = arr.view();

.. _example-intervalindex-duplicated-47:

.. dropdown:: duplicated (pd_test_1_all.cpp:10583)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10573
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_extension_index_duplicated() {
          std::cout << "========= duplicated =========================";
      
          pandas::CategoricalArray arr({"a", "b", "a", "c", "a"});
          pandas::CategoricalIndex idx(arr);
      
          auto dup_mask = idx.duplicated("first");
      
          bool passed = (dup_mask.getElementAt({0}) == false &&
                         dup_mask.getElementAt({1}) == false &&
                         dup_mask.getElementAt({2}) == true &&
                         dup_mask.getElementAt({3}) == false &&
                         dup_mask.getElementAt({4}) == true);
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_duplicated() : duplicated check failed" << std::endl;
              throw std::runtime_error("pd_test_extension_index_duplicated failed");
          }

.. _example-intervalindex-union_-48:

.. dropdown:: union_ (pd_test_1_all.cpp:10694)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10684
      :emphasize-lines: 11

          std::cout << "========= union =========================";
      
          // Use same categories for both arrays
          std::vector<std::string> cats = {"a", "b", "c", "d", "e"};
          pandas::CategoricalArray arr1({"a", "b", "c"}, cats);
          pandas::CategoricalIndex idx1(arr1);
      
          pandas::CategoricalArray arr2({"b", "c", "d", "e"}, cats);
          pandas::CategoricalIndex idx2(arr2);
      
          auto uni = idx1.union_(idx2);
      
          bool passed = (uni.size() == 5 &&
                         uni.contains("a") && uni.contains("b") && uni.contains("c") &&
                         uni.contains("d") && uni.contains("e"));
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_union() : union check failed" << std::endl;
              throw std::runtime_error("pd_test_extension_index_union failed");
          }
      
          std::cout << " -> tests passed" << std::endl;

.. _example-intervalindex-unique-49:

.. 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-intervalindex-is_-50:

.. dropdown:: is_ (pd_test_3_all.cpp:3972)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3962
      :emphasize-lines: 11

      
          // For typed Index, this is a no-op
          if (result.size() != 5) {
              throw std::runtime_error("infer_objects size should be 5");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_is_() {
          std::cout << "========= Index.is_() ==============================";
      
          pandas::Index<numpy::int64> idx1({1, 2, 3, 4, 5});
          pandas::Index<numpy::int64> idx2({1, 2, 3, 4, 5});  // Different object
      
          // Different objects should not be the same
          if (idx1.is_(idx2)) {
              throw std::runtime_error("different objects should not be is_() equal");
          }
      
          // Same object should be the same

.. _example-intervalindex-is_boolean-51:

.. dropdown:: is_boolean (pd_test_3_all.cpp:3290)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3280
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_datetime_index_type_checks() {
          std::cout << "========= DatetimeIndex type checks ======================";
      
          pandas::DatetimeIndex idx = pandas::date_range("2024-01-01", "2024-01-05", std::nullopt, "D");
      
          // Type check methods
          if (idx.is_boolean()) {
              throw std::runtime_error("is_boolean() should be false");
          }
          if (idx.is_categorical()) {
              throw std::runtime_error("is_categorical() should be false");
          }
          if (idx.is_floating()) {
              throw std::runtime_error("is_floating() should be false");
          }
          if (idx.is_integer()) {
              throw std::runtime_error("is_integer() should be false");

.. _example-intervalindex-is_categorical-52:

.. dropdown:: is_categorical (pd_test_3_all.cpp:3293)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3283
      :emphasize-lines: 11

      
      void pd_test_3_all_datetime_index_type_checks() {
          std::cout << "========= DatetimeIndex type checks ======================";
      
          pandas::DatetimeIndex idx = pandas::date_range("2024-01-01", "2024-01-05", std::nullopt, "D");
      
          // Type check methods
          if (idx.is_boolean()) {
              throw std::runtime_error("is_boolean() should be false");
          }
          if (idx.is_categorical()) {
              throw std::runtime_error("is_categorical() should be false");
          }
          if (idx.is_floating()) {
              throw std::runtime_error("is_floating() should be false");
          }
          if (idx.is_integer()) {
              throw std::runtime_error("is_integer() should be false");
          }
          if (idx.is_interval()) {
              throw std::runtime_error("is_interval() should be false");

.. _example-intervalindex-is_empty-53:

.. dropdown:: is_empty (pd_test_1_all.cpp:2164)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2154
      :emphasize-lines: 11

      
          // Test with right-closed intervals (a, b]
          std::vector<std::pair<numpy::float64, numpy::float64>> tuples = {
              {0.0, 1.0},   // Not empty
              {1.0, 1.0},   // Empty (1, 1] has no points
              {2.0, 2.0},   // Empty
              {2.0, 3.0}    // Not empty
          };
      
          auto arr_right = pandas::IntervalArrayFloat64::from_tuples(tuples, pandas::IntervalClosed::Right);
          auto empty_right = arr_right.is_empty();
      
          if (empty_right[0].value_or(true) != false ||
              empty_right[1].value_or(false) != true ||
              empty_right[2].value_or(false) != true ||
              empty_right[3].value_or(true) != false) {
              std::cout << "[FAIL] : in test_is_empty() : right-closed" << std::endl;
              return;
          }
      
          // Test with both-closed intervals [a, b] - [1, 1] is NOT empty

.. _example-intervalindex-is_floating-54:

.. dropdown:: is_floating (pd_test_3_all.cpp:622)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 612
      :emphasize-lines: 11

          // Test with integer index
          pandas::IndexDtype<numpy::int64> int_dtype;
          if (!int_dtype.is_numeric()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be numeric" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_numeric");
          }
          if (!int_dtype.is_integer()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be integer" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_integer");
          }
          if (int_dtype.is_floating()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be floating" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_floating");
          }
          if (int_dtype.is_object()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be object" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_object");
          }
      
          // Test with float index
          pandas::IndexDtype<double> float_dtype;

.. _example-intervalindex-is_integer-55:

.. dropdown:: is_integer (pd_test_3_all.cpp:618)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 608
      :emphasize-lines: 11

      
      void pd_test_3_all_index_dtype_checks() {
          std::cout << "========= IndexDtype.is_numeric/integer/floating/object() ";
      
          // Test with integer index
          pandas::IndexDtype<numpy::int64> int_dtype;
          if (!int_dtype.is_numeric()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be numeric" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_numeric");
          }
          if (!int_dtype.is_integer()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be integer" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_integer");
          }
          if (int_dtype.is_floating()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be floating" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_floating");
          }
          if (int_dtype.is_object()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be object" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_object");

.. _example-intervalindex-is_interval-56:

.. dropdown:: is_interval (pd_test_3_all.cpp:3302)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3292
      :emphasize-lines: 11

          }
          if (idx.is_categorical()) {
              throw std::runtime_error("is_categorical() should be false");
          }
          if (idx.is_floating()) {
              throw std::runtime_error("is_floating() should be false");
          }
          if (idx.is_integer()) {
              throw std::runtime_error("is_integer() should be false");
          }
          if (idx.is_interval()) {
              throw std::runtime_error("is_interval() should be false");
          }
          if (idx.is_numeric()) {
              throw std::runtime_error("is_numeric() should be false");
          }
          if (idx.is_object()) {
              throw std::runtime_error("is_object() should be false");
          }
          if (idx.holds_integer()) {
              throw std::runtime_error("holds_integer() should be false");

.. _example-intervalindex-is_left_closed-57:

.. dropdown:: is_left_closed (pd_test_1_all.cpp:12830)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12820
      :emphasize-lines: 11

      }
      
      void pd_test_interval_index_is_left_right_closed() {
          std::cout << "========= is_left_closed/is_right_closed =========================";
      
          auto idx_right = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Right);
          auto idx_left = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Left);
          auto idx_both = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Both);
          auto idx_neither = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Neither);
      
          bool passed = (!idx_right.is_left_closed() && idx_right.is_right_closed() &&
                         idx_left.is_left_closed() && !idx_left.is_right_closed() &&
                         idx_both.is_left_closed() && idx_both.is_right_closed() &&
                         !idx_neither.is_left_closed() && !idx_neither.is_right_closed());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_interval_index_is_left_right_closed() : check failed" << std::endl;
              throw std::runtime_error("pd_test_interval_index_is_left_right_closed failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-is_non_overlapping_monotonic-58:

.. dropdown:: is_non_overlapping_monotonic (pd_test_1_all.cpp:2457)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2447
      :emphasize-lines: 11

      
      // ============================================================================
      // Test: is_non_overlapping_monotonic
      // ============================================================================
      void test_is_non_overlapping_monotonic() {
          std::cout << "========= IntervalArray: is_non_overlapping_monotonic ======================= ";
      
          // Monotonic, non-overlapping
          std::vector<numpy::float64> breaks1 = {0.0, 1.0, 2.0, 3.0};
          auto arr1 = pandas::IntervalArrayFloat64::from_breaks(breaks1, pandas::IntervalClosed::Right);
          if (!arr1.is_non_overlapping_monotonic()) {
              std::cout << "[FAIL] : in test_is_non_overlapping_monotonic() : should be true for breaks" << std::endl;
              return;
          }
      
          // Non-monotonic (out of order)
          std::vector<std::pair<numpy::float64, numpy::float64>> tuples2 = {
              {2.0, 3.0}, {0.0, 1.0}, {1.0, 2.0}
          };
          auto arr2 = pandas::IntervalArrayFloat64::from_tuples(tuples2);
          if (arr2.is_non_overlapping_monotonic()) {

.. _example-intervalindex-is_numeric-59:

.. dropdown:: is_numeric (pd_test_3_all.cpp:614)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 604
      :emphasize-lines: 11

      
      // ============================================================================
      // Category 4: Index Type Checking (IndexDtype)
      // ============================================================================
      
      void pd_test_3_all_index_dtype_checks() {
          std::cout << "========= IndexDtype.is_numeric/integer/floating/object() ";
      
          // Test with integer index
          pandas::IndexDtype<numpy::int64> int_dtype;
          if (!int_dtype.is_numeric()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be numeric" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_numeric");
          }
          if (!int_dtype.is_integer()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be integer" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_integer");
          }
          if (int_dtype.is_floating()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be floating" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_floating");

.. _example-intervalindex-is_object-60:

.. dropdown:: is_object (pd_test_3_all.cpp:626)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 616
      :emphasize-lines: 11

              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_numeric");
          }
          if (!int_dtype.is_integer()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should be integer" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_integer");
          }
          if (int_dtype.is_floating()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be floating" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_floating");
          }
          if (int_dtype.is_object()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : int should not be object" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: int is_object");
          }
      
          // Test with float index
          pandas::IndexDtype<double> float_dtype;
          if (!float_dtype.is_numeric()) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_dtype_checks() : float should be numeric" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_dtype_checks failed: float is_numeric");
          }

.. _example-intervalindex-is_overlapping-61:

.. dropdown:: is_overlapping (pd_test_1_all.cpp:12891)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12881
      :emphasize-lines: 11

          std::cout << "========= is_overlapping =========================";
      
          // Non-overlapping intervals
          auto idx1 = pandas::IntervalIndex64::from_breaks({0, 1, 2, 3});
      
          // Overlapping intervals: [0,5], [3,8]
          std::vector<numpy::int64> left_vals = {0, 3};
          std::vector<numpy::int64> right_vals = {5, 8};
          auto idx2 = pandas::IntervalIndex64::from_arrays(left_vals, right_vals, pandas::IntervalClosed::Both);
      
          bool passed = (!idx1.is_overlapping() && idx2.is_overlapping());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_interval_index_is_overlapping() : check failed" << std::endl;
              throw std::runtime_error("pd_test_interval_index_is_overlapping failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_index_is_non_overlapping_monotonic() {
          std::cout << "========= is_non_overlapping_monotonic =========================";

.. _example-intervalindex-is_right_closed-62:

.. dropdown:: is_right_closed (pd_test_1_all.cpp:12830)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12820
      :emphasize-lines: 11

      }
      
      void pd_test_interval_index_is_left_right_closed() {
          std::cout << "========= is_left_closed/is_right_closed =========================";
      
          auto idx_right = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Right);
          auto idx_left = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Left);
          auto idx_both = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Both);
          auto idx_neither = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Neither);
      
          bool passed = (!idx_right.is_left_closed() && idx_right.is_right_closed() &&
                         idx_left.is_left_closed() && !idx_left.is_right_closed() &&
                         idx_both.is_left_closed() && idx_both.is_right_closed() &&
                         !idx_neither.is_left_closed() && !idx_neither.is_right_closed());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_interval_index_is_left_right_closed() : check failed" << std::endl;
              throw std::runtime_error("pd_test_interval_index_is_left_right_closed failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-all-63:

.. 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-intervalindex-any-64:

.. 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-intervalindex-argmax-65:

.. 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-intervalindex-argmin-66:

.. 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-intervalindex-arr-67:

.. dropdown:: arr (pd_test_1_all.cpp:45)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 35
      :emphasize-lines: 11

                  std::cout << "  [FAIL] : in pd_test_boolean_array_constructors() : initializer_list size != 4" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_constructors failed: initializer_list size != 4");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          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");
              }
      

.. _example-intervalindex-arr-68:

.. dropdown:: arr (pd_test_1_all.cpp:45)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 35
      :emphasize-lines: 11

                  std::cout << "  [FAIL] : in pd_test_boolean_array_constructors() : initializer_list size != 4" << std::endl;
                  throw std::runtime_error("pd_test_boolean_array_constructors failed: initializer_list size != 4");
              }
      
              std::cout << " -> tests passed" << std::endl;
          }
      
          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");
              }
      

.. _example-intervalindex-clone-69:

.. dropdown:: clone (pd_test_1_all.cpp:5776)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5766
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_categorical_index_clone() {
          std::cout << "========= clone =======================================";
      
          pandas::CategoricalArray arr({"p", "q", "r"});
          pandas::CategoricalIndex idx(arr, "original");
      
          std::unique_ptr<pandas::IndexBase> cloned = idx.clone();
      
          bool passed = (cloned != nullptr && cloned->size() == idx.size() &&
                         cloned->name() == idx.name());
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_clone()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_clone failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }

.. _example-intervalindex-closed-70:

.. dropdown:: closed (pd_test_1_all.cpp:1903)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1893
      :emphasize-lines: 11

      // ============================================================================
      void test_constructors() {
          std::cout << "========= IntervalArray: constructors ======================= ";
      
          // Default constructor
          pandas::IntervalArrayFloat64 empty;
          if (empty.size() != 0) {
              std::cout << "[FAIL] : in test_constructors() : default constructor size" << std::endl;
              return;
          }
          if (empty.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_constructors() : default closure" << std::endl;
              return;
          }
      
          // Constructor from left/right arrays
          numpy::NDArray<numpy::float64> left(std::vector<size_t>{3});
          numpy::NDArray<numpy::float64> right(std::vector<size_t>{3});
          left.setElementAt({0}, 0.0);  right.setElementAt({0}, 1.0);
          left.setElementAt({1}, 1.0);  right.setElementAt({1}, 2.0);
          left.setElementAt({2}, 2.0);  right.setElementAt({2}, 3.0);

.. _example-intervalindex-closed_string-71:

.. dropdown:: closed_string (pd_test_1_all.cpp:12813)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 12803
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_index_closed_string() {
          std::cout << "========= closed_string =========================";
      
          auto idx_right = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Right);
          auto idx_left = pandas::IntervalIndex64::from_breaks({0, 1, 2}, pandas::IntervalClosed::Left);
      
          bool passed = (idx_right.closed_string() == "right" && idx_left.closed_string() == "left");
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_interval_index_closed_string() : closed_string check failed" << std::endl;
              throw std::runtime_error("pd_test_interval_index_closed_string failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_index_is_left_right_closed() {
          std::cout << "========= is_left_closed/is_right_closed =========================";

.. _example-intervalindex-contains-72:

.. dropdown:: contains (pd_test_1_all.cpp:2200)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2190
      :emphasize-lines: 11

      // Test: contains method
      // ============================================================================
      void test_contains() {
          std::cout << "========= IntervalArray: contains ======================= ";
      
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0, 3.0};
      
          // Right-closed intervals: (0, 1], (1, 2], (2, 3]
          auto arr_right = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          // Test contains(1.0) - should be in interval 0 but not 1 (since 1 is exclusive on left of interval 1)
          auto contains_1 = arr_right.contains(1.0);
          // (0, 1] contains 1: yes, (1, 2] contains 1: no (open on left), (2, 3] contains 1: no
          if (contains_1[0].value_or(false) != true ||
              contains_1[1].value_or(true) != false ||
              contains_1[2].value_or(true) != false) {
              std::cout << "[FAIL] : in test_contains() : right-closed contains 1.0" << std::endl;
              return;
          }
      
          // Left-closed intervals: [0, 1), [1, 2), [2, 3)

.. _example-intervalindex-contains-73:

.. dropdown:: contains (pd_test_1_all.cpp:2200)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2190
      :emphasize-lines: 11

      // Test: contains method
      // ============================================================================
      void test_contains() {
          std::cout << "========= IntervalArray: contains ======================= ";
      
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0, 3.0};
      
          // Right-closed intervals: (0, 1], (1, 2], (2, 3]
          auto arr_right = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          // Test contains(1.0) - should be in interval 0 but not 1 (since 1 is exclusive on left of interval 1)
          auto contains_1 = arr_right.contains(1.0);
          // (0, 1] contains 1: yes, (1, 2] contains 1: no (open on left), (2, 3] contains 1: no
          if (contains_1[0].value_or(false) != true ||
              contains_1[1].value_or(true) != false ||
              contains_1[2].value_or(true) != false) {
              std::cout << "[FAIL] : in test_contains() : right-closed contains 1.0" << std::endl;
              return;
          }
      
          // Left-closed intervals: [0, 1), [1, 2), [2, 3)

.. _example-intervalindex-delete_-74:

.. dropdown:: delete_ (pd_test_1_all.cpp:10501)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10491
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_extension_index_delete() {
          std::cout << "========= delete_ =========================";
      
          pandas::CategoricalArray arr({"a", "b", "c", "d"});
          pandas::CategoricalIndex idx(arr);
      
          auto deleted = idx.delete_(1);
          auto v0 = deleted[0];
          auto v1 = deleted[1];
          auto v2 = deleted[2];
      
          bool passed = (deleted.size() == 3 &&
                         v0.has_value() && *v0 == "a" &&
                         v1.has_value() && *v1 == "c" &&
                         v2.has_value() && *v2 == "d");
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_delete() : delete_ check failed" << std::endl;

.. _example-intervalindex-delete_-75:

.. dropdown:: delete_ (pd_test_1_all.cpp:10501)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10491
      :emphasize-lines: 11

      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_extension_index_delete() {
          std::cout << "========= delete_ =========================";
      
          pandas::CategoricalArray arr({"a", "b", "c", "d"});
          pandas::CategoricalIndex idx(arr);
      
          auto deleted = idx.delete_(1);
          auto v0 = deleted[0];
          auto v1 = deleted[1];
          auto v2 = deleted[2];
      
          bool passed = (deleted.size() == 3 &&
                         v0.has_value() && *v0 == "a" &&
                         v1.has_value() && *v1 == "c" &&
                         v2.has_value() && *v2 == "d");
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_delete() : delete_ check failed" << std::endl;

.. _example-intervalindex-dtype_name-76:

.. dropdown:: dtype_name (pd_test_1_all.cpp:10104)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10094
      :emphasize-lines: 11

      }
      
      void pd_test_extension_index_array_constructor() {
          std::cout << "========= array constructor =========================";
      
          pandas::CategoricalArray arr({"apple", "banana", "apple", "cherry"});
          pandas::CategoricalIndex idx(arr, "fruits");
      
          bool passed = (idx.size() == 4 && !idx.empty() &&
                         idx.name().has_value() && *idx.name() == "fruits" &&
                         idx.dtype_name() == "category");
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_extension_index_array_constructor() : array constructor check failed" << std::endl;
              throw std::runtime_error("pd_test_extension_index_array_constructor failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_extension_index_copy_constructor() {
          std::cout << "========= copy constructor =========================";

.. _example-intervalindex-format-77:

.. dropdown:: format (main.cpp:20)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 10
      :emphasize-lines: 11

      int main() {
        // Automatically log all output to temp/pd_test_output.log
        numpy::TestLogger logger("temp/pd_test_output.log");
      
        int res = 0;
        int res1 = 0;
        std::string resS = "";
      
        // call all the tests
        res1 = dataframe_tests::pd_test_main();
        resS += std::format("             pd_test_main: {}  errors\n", res1);
        res += res1;
      
        std::cout << "\n------------------------- main --------------------------------------------\n";
        std::cout << std::endl << "All tests completed. Nb errors = " << res << std::endl;
        std::cout << "Details: \n" << resS;
        std::cout << "\n---------------------------------------------------------------------------\n";
        return res;
      }

.. _example-intervalindex-format_interval-78:

.. dropdown:: format_interval (pd_test_3_all.cpp:24894)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24884
      :emphasize-lines: 11

      namespace dataframe_tests_interval_type_inference {
      
      void pd_test_interval_type_inference_breaks_int() {
          std::cout << "========= interval_type_inference_breaks_int ======================= ";
          auto idx = pandas::IntervalIndex<double>::from_breaks({0.0, 1.0, 2.0, 3.0});
          if (idx.subtype_override() != "int64")
              throw std::runtime_error("expected subtype_override 'int64', got '" + idx.subtype_override() + "'");
          std::string dtype = idx.dtype_name();
          if (dtype.find("int64") == std::string::npos)
              throw std::runtime_error("expected dtype containing 'int64', got '" + dtype + "'");
          std::string fmt = idx.format_interval(0);
          if (fmt.find('.') != std::string::npos)
              throw std::runtime_error("expected integer format without decimal, got '" + fmt + "'");
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_type_inference_breaks_float() {
          std::cout << "========= interval_type_inference_breaks_float ===================== ";
          auto idx = pandas::IntervalIndex<double>::from_breaks({0.0, 1.5, 3.0});
          if (!idx.subtype_override().empty())
              throw std::runtime_error("expected empty subtype_override, got '" + idx.subtype_override() + "'");

.. _example-intervalindex-holds_integer-79:

.. dropdown:: holds_integer (pd_test_3_all.cpp:3311)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3301
      :emphasize-lines: 11

          }
          if (idx.is_interval()) {
              throw std::runtime_error("is_interval() should be false");
          }
          if (idx.is_numeric()) {
              throw std::runtime_error("is_numeric() should be false");
          }
          if (idx.is_object()) {
              throw std::runtime_error("is_object() should be false");
          }
          if (idx.holds_integer()) {
              throw std::runtime_error("holds_integer() should be false");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_datetime_index_sort() {
          std::cout << "========= DatetimeIndex.sort_values() ====================";
      
          pandas::DatetimeIndex idx = pandas::date_range("2024-01-01", "2024-01-05", std::nullopt, "D");

.. _example-intervalindex-inferred_type-80:

.. dropdown:: inferred_type (pd_test_1_all.cpp:5270)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5260
      :emphasize-lines: 11

      }
      
      void pd_test_categorical_index_array_constructor() {
          std::cout << "========= array constructor ===========================";
      
          pandas::CategoricalArray arr({"apple", "banana", "apple", "cherry"});
          pandas::CategoricalIndex idx(arr, "fruits");
      
          bool passed = (idx.size() == 4 && !idx.empty() &&
                         idx.name().has_value() && *idx.name() == "fruits" &&
                         idx.inferred_type() == "categorical");
          if (!passed) {
              std::cout << "  [FAIL] : in pd_test_categorical_index_array_constructor()" << std::endl;
              throw std::runtime_error("pd_test_categorical_index_array_constructor failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_categorical_index_values_constructor() {
          std::cout << "========= values constructor ==========================";

.. _example-intervalindex-item-81:

.. dropdown:: item (pd_test_3_all.cpp:3712)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3702
      :emphasize-lines: 11

      
          // Test is_interval (always false for base Index)
          if (int_idx.is_interval()) {
              throw std::runtime_error("base Index should not be interval");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_item() {
          std::cout << "========= Index.item() =============================";
      
          pandas::Index<numpy::int64> idx1({42});
          numpy::int64 val = idx1.item();
      
          if (val != 42) {
              throw std::runtime_error("item() should return 42");
          }
      
          // Test error for size != 1
          pandas::Index<numpy::int64> idx2({1, 2, 3});

.. _example-intervalindex-memory_usage-82:

.. dropdown:: memory_usage (pd_test_1_all.cpp:27063)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 27053
      :emphasize-lines: 11

              }
      
              std::cout << "====================================== [OK] pd_test_value_counts test suite ========================== " << std::endl;
              return 0;
          }
      
      } // namespace dataframe_tests
      // ------------------- pd_test_value_counts.cpp (end) -----------------------------
      
      // ------------------- pd_test_memory_usage.cpp (start) -----------------------------
      // Tests for DataFrame.memory_usage() - pandas-compatible memory usage reporting
      
      namespace dataframe_tests {
          namespace dataframe_tests_memory_usage {
      
              void pd_test_memory_usage_basic() {
                  std::cout << "========= basic memory_usage =======================";
      
                  // Create a simple DataFrame with multiple columns
                  std::map<std::string, std::vector<double>> data;
                  data["A"] = {1.0, 2.0, 3.0, 4.0, 5.0};

.. _example-intervalindex-mid-83:

.. dropdown:: mid (pd_test_1_all.cpp:2124)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2114
      :emphasize-lines: 11

      
          // Test right()
          auto right_arr = arr.right();
          if (right_arr.getElementAt({0}) != 2.0 ||
              right_arr.getElementAt({1}) != 5.0 ||
              right_arr.getElementAt({2}) != 10.0) {
              std::cout << "[FAIL] : in test_left_right_mid_length() : right()" << std::endl;
              return;
          }
      
          // Test mid()
          auto mid_arr = arr.mid();
          // (0+2)/2=1, (2+5)/2=3.5, (5+10)/2=7.5
          auto mid0 = mid_arr[0];
          auto mid1 = mid_arr[1];
          auto mid2 = mid_arr[2];
          if (!mid0.has_value() || std::abs(mid0.value() - 1.0) > 1e-10 ||
              !mid1.has_value() || std::abs(mid1.value() - 3.5) > 1e-10 ||
              !mid2.has_value() || std::abs(mid2.value() - 7.5) > 1e-10) {
              std::cout << "[FAIL] : in test_left_right_mid_length() : mid()" << std::endl;
              return;

.. _example-intervalindex-overlaps-84:

.. dropdown:: overlaps (pd_test_1_all.cpp:2244)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2234
      :emphasize-lines: 11

      // Test: overlaps method
      // ============================================================================
      void test_overlaps() {
          std::cout << "========= IntervalArray: overlaps ======================= ";
      
          std::vector<numpy::float64> breaks = {0.0, 2.0, 4.0, 6.0};
          // Right-closed: (0, 2], (2, 4], (4, 6]
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          // Check overlap with (1, 3]
          auto overlap_1_3 = arr.overlaps(1.0, 3.0);
          // (0, 2] overlaps (1, 3]? Yes (share 1-2)
          // (2, 4] overlaps (1, 3]? Yes (share 2-3)
          // (4, 6] overlaps (1, 3]? No
          if (overlap_1_3[0].value_or(false) != true ||
              overlap_1_3[1].value_or(false) != true ||
              overlap_1_3[2].value_or(true) != false) {
              std::cout << "[FAIL] : in test_overlaps() : overlaps (1, 3]" << std::endl;
              return;
          }
      

.. _example-intervalindex-overlaps-85:

.. dropdown:: overlaps (pd_test_1_all.cpp:2244)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2234
      :emphasize-lines: 11

      // Test: overlaps method
      // ============================================================================
      void test_overlaps() {
          std::cout << "========= IntervalArray: overlaps ======================= ";
      
          std::vector<numpy::float64> breaks = {0.0, 2.0, 4.0, 6.0};
          // Right-closed: (0, 2], (2, 4], (4, 6]
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          // Check overlap with (1, 3]
          auto overlap_1_3 = arr.overlaps(1.0, 3.0);
          // (0, 2] overlaps (1, 3]? Yes (share 1-2)
          // (2, 4] overlaps (1, 3]? Yes (share 2-3)
          // (4, 6] overlaps (1, 3]? No
          if (overlap_1_3[0].value_or(false) != true ||
              overlap_1_3[1].value_or(false) != true ||
              overlap_1_3[2].value_or(true) != false) {
              std::cout << "[FAIL] : in test_overlaps() : overlaps (1, 3]" << std::endl;
              return;
          }
      

.. _example-intervalindex-putmask-86:

.. dropdown:: putmask (pd_test_3_all.cpp:3752)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3742
      :emphasize-lines: 11

      
          // Should be at least sizeof index + 5 * sizeof(int64)
          if (usage < 5 * sizeof(numpy::int64)) {
              throw std::runtime_error("memory_usage too small");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_putmask() {
          std::cout << "========= Index.putmask() ==========================";
      
          pandas::Index<numpy::int64> idx({1, 2, 3, 4, 5});
          numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{5});
          mask.setElementAt({0}, numpy::bool_(true));
          mask.setElementAt({1}, numpy::bool_(false));
          mask.setElementAt({2}, numpy::bool_(true));
          mask.setElementAt({3}, numpy::bool_(false));
          mask.setElementAt({4}, numpy::bool_(true));
      
          auto result = idx.putmask(mask, numpy::int64(99));

.. _example-intervalindex-ravel-87:

.. dropdown:: ravel (pd_test_3_all.cpp:2147)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2137
      :emphasize-lines: 11

              throw std::runtime_error("memory_usage shallow too small");
          }
          if (deep < shallow) {
              throw std::runtime_error("memory_usage deep should be >= shallow");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_categorical_ravel_view() {
          std::cout << "========= CategoricalArray.ravel()/view() =============";
      
          std::vector<std::optional<std::string>> values = {"a", "b", "c"};
          pandas::CategoricalArray arr(values);
      
          auto raveled = arr.ravel();
          if (raveled.size() != 3 || !raveled.equals(arr)) {
              throw std::runtime_error("ravel failed");
          }
      
          auto viewed = arr.view();

.. _example-intervalindex-repeat-88:

.. dropdown:: repeat (pd_test_3_all.cpp:2166)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2156
      :emphasize-lines: 11

      
          auto viewed = arr.view();
          if (viewed.size() != 3 || !viewed.equals(arr)) {
              throw std::runtime_error("view failed");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_categorical_repeat() {
          std::cout << "========= CategoricalArray.repeat() ===================";
      
          std::vector<std::optional<std::string>> values = {"a", "b"};
          pandas::CategoricalArray arr(values);
      
          auto result = arr.repeat(3);
          if (result.size() != 6 || *result[0] != "a" || *result[2] != "a" ||
              *result[3] != "b" || *result[5] != "b") {
              throw std::runtime_error("repeat scalar failed");
          }
      

.. _example-intervalindex-repr-89:

.. 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-intervalindex-result-90:

.. 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-intervalindex-right-91:

.. dropdown:: right (pd_test_1_all.cpp:1910)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1900
      :emphasize-lines: 11

              std::cout << "[FAIL] : in test_constructors() : default constructor size" << std::endl;
              return;
          }
          if (empty.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_constructors() : default closure" << std::endl;
              return;
          }
      
          // Constructor from left/right arrays
          numpy::NDArray<numpy::float64> left(std::vector<size_t>{3});
          numpy::NDArray<numpy::float64> right(std::vector<size_t>{3});
          left.setElementAt({0}, 0.0);  right.setElementAt({0}, 1.0);
          left.setElementAt({1}, 1.0);  right.setElementAt({1}, 2.0);
          left.setElementAt({2}, 2.0);  right.setElementAt({2}, 3.0);
      
          pandas::IntervalArrayFloat64 arr1(left, right);
          if (arr1.size() != 3) {
              std::cout << "[FAIL] : in test_constructors() : array size" << std::endl;
              return;
          }
      

.. _example-intervalindex-round-92:

.. dropdown:: round (pd_test_1_all.cpp:1688)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 1678
      :emphasize-lines: 11

      
          void pd_test_floating_array_rounding() {
              std::cout << "========= FloatingArray: rounding ======================= ";
      
              pandas::FloatingArray<double> arr({
                  std::optional<double>(1.234),
                  std::optional<double>(2.567),
                  std::nullopt
              });
      
              auto rounded = arr.round(2);
              if (std::abs(rounded[0].value() - 1.23) > 0.001 ||
                  std::abs(rounded[1].value() - 2.57) > 0.001) {
                  std::cout << "  [FAIL] : in pd_test_floating_array_rounding() : round(2)" << std::endl;
                  throw std::runtime_error("pd_test_floating_array_rounding failed: round(2)");
              }
      
              if (!rounded.is_na(2)) {
                  std::cout << "  [FAIL] : in pd_test_floating_array_rounding() : round should preserve NA" << std::endl;
                  throw std::runtime_error("pd_test_floating_array_rounding failed: NA preservation");
              }

.. _example-intervalindex-set_closed-93:

.. dropdown:: set_closed (pd_test_1_all.cpp:2285)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2275
      :emphasize-lines: 11

      
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0};
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          if (arr.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_set_closed() : initial closure" << std::endl;
              return;
          }
      
          // Change to left-closed
          auto arr_left = arr.set_closed(pandas::IntervalClosed::Left);
          if (arr_left.closed() != pandas::IntervalClosed::Left) {
              std::cout << "[FAIL] : in test_set_closed() : set to Left" << std::endl;
              return;
          }
      
          // Original should be unchanged
          if (arr.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_set_closed() : original changed" << std::endl;
              return;
          }

.. _example-intervalindex-set_closed-94:

.. dropdown:: set_closed (pd_test_1_all.cpp:2285)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 2275
      :emphasize-lines: 11

      
          std::vector<numpy::float64> breaks = {0.0, 1.0, 2.0};
          auto arr = pandas::IntervalArrayFloat64::from_breaks(breaks, pandas::IntervalClosed::Right);
      
          if (arr.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_set_closed() : initial closure" << std::endl;
              return;
          }
      
          // Change to left-closed
          auto arr_left = arr.set_closed(pandas::IntervalClosed::Left);
          if (arr_left.closed() != pandas::IntervalClosed::Left) {
              std::cout << "[FAIL] : in test_set_closed() : set to Left" << std::endl;
              return;
          }
      
          // Original should be unchanged
          if (arr.closed() != pandas::IntervalClosed::Right) {
              std::cout << "[FAIL] : in test_set_closed() : original changed" << std::endl;
              return;
          }

.. _example-intervalindex-set_subtype_override-95:

.. dropdown:: set_subtype_override (pd_test_3_all.cpp:24977)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 24967
      :emphasize-lines: 11

          std::cout << "========= Interval repr float bounds ====================";
          pandas::Interval<double> iv(0.0, 1.5);
          if (iv.repr() != "Interval(0.0, 1.5, closed='right')")
              throw std::runtime_error("repr mismatch: " + iv.repr());
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_repr_timedelta() {
          std::cout << "========= Interval repr timedelta subtype ===============";
          pandas::Interval<double> iv(0.0, 86400000000000.0);  // 1 day in nanos
          iv.set_subtype_override("timedelta64[ns]");
          std::string r = iv.repr();
          if (r.find("Timedelta") == std::string::npos)
              throw std::runtime_error("expected Timedelta in repr: " + r);
          if (r.find("1 days") == std::string::npos)
              throw std::runtime_error("expected '1 days' in repr: " + r);
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_interval_str_integer() {
          std::cout << "========= Interval to_string integer bounds =============";

.. _example-intervalindex-slice_indexer-96:

.. dropdown:: slice_indexer (pd_test_3_all.cpp:711)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 701
      :emphasize-lines: 11

          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      // ============================================================================
      // Category 6: Index Indexer Methods
      // ============================================================================
      
      void pd_test_3_all_index_indexers() {
          std::cout << "========= Index.get_indexer_for/non_unique/slice_indexer() ";
      
          std::vector<std::string> vals = {"a", "b", "c", "d", "e"};
          pandas::Index<std::string> idx(vals);
      
          // Test get_indexer_for()
          std::vector<std::string> target = {"b", "d", "f"};  // "f" doesn't exist
          numpy::NDArray<numpy::int64> indexer = idx.get_indexer_for(target);
          if (indexer.getSize() != 3) {
              std::cout << "  [FAIL] : in pd_test_3_all_index_indexers() : get_indexer_for size mismatch" << std::endl;
              throw std::runtime_error("pd_test_3_all_index_indexers failed: get_indexer_for size");

.. _example-intervalindex-slice_locs-97:

.. dropdown:: slice_locs (pd_test_1_all.cpp:18275)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 18265
      :emphasize-lines: 11

              }
      
              std::cout << "-> tests passed" << std::endl;
          }
      
          void pd_test_range_index_slice_locs() {
              std::cout << "========= slice_locs ================================== ";
      
              pandas::RangeIndex ri(0, 10);  // [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
      
              auto [start_idx, stop_idx] = ri.slice_locs(3, 7);
      
              bool passed = (start_idx == 3 && stop_idx == 8);
      
              if (!passed) {
                  std::cout << "  [FAIL] : slice_locs" << std::endl;
                  throw std::runtime_error("pd_test_range_index_slice_locs failed");
              }
      
              std::cout << "-> tests passed" << std::endl;
          }

.. _example-intervalindex-sort-98:

.. dropdown:: sort (pd_test_3_all.cpp:3869)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 3859
      :emphasize-lines: 11

              throw std::runtime_error("last 2 positions should be NaN");
          }
          if (std::abs(result[0] - 3.0) > 0.001) {
              throw std::runtime_error("shift(-2) [0] should be 3.0");
          }
      
          std::cout << " -> tests passed" << std::endl;
      }
      
      void pd_test_3_all_index_sort() {
          std::cout << "========= Index.sort() =============================";
      
          pandas::Index<numpy::int64> idx({3, 1, 4, 1, 5, 9, 2, 6});
          auto result = idx.sort();
      
          if (result[0] != 1 || result[1] != 1 || result[7] != 9) {
              throw std::runtime_error("sort() not working correctly");
          }
      
          // Test descending
          result = idx.sort(false);

.. _example-intervalindex-sortlevel-99:

.. dropdown:: sortlevel (pd_test_1_all.cpp:14676)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 14666
      :emphasize-lines: 11

      
              void pd_test_multiindex_sortlevel() {
                  std::cout << "========= sortlevel =================================== ";
      
                  std::vector<std::vector<std::string>> arrays = {
                      {"b", "a", "c"},
                      {"2", "1", "3"}
                  };
      
                  pandas::MultiIndex mi = pandas::MultiIndex::from_arrays<std::string>(arrays);
                  auto [sorted, indices] = mi.sortlevel(0);
      
                  bool passed = true;
      
                  // After sorting by level 0: a, b, c
                  if (sorted[0][0] != "a" || sorted[1][0] != "b" || sorted[2][0] != "c") {
                      std::cout << "  [FAIL] : not sorted correctly by level 0" << std::endl;
                      passed = false;
                  }
      
                  if (!passed) {

.. _example-intervalindex-str-100:

.. dropdown:: str (pd_test_1_all.cpp:7137)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 7127
      :emphasize-lines: 11

                  // Test basic info() with stringstream
                  std::map<std::string, std::vector<int>> data = {
                      {"A", {1, 2, 3, 4, 5}},
                      {"B", {10, 20, 30, 40, 50}},
                      {"C", {100, 200, 300, 400, 500}}
                  };
                  pandas::DataFrame df(data);
      
                  std::ostringstream oss;
                  df.info(oss);
                  std::string output = oss.str();
      
                  // Verify key components
                  if (output.find("<class 'pandas.core.frame.DataFrame'>") == std::string::npos) {
                      std::cout << "  [FAIL] : info missing class name" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_info failed: missing class name");
                  }
                  if (output.find("RangeIndex:") == std::string::npos) {
                      std::cout << "  [FAIL] : info missing RangeIndex" << std::endl;
                      throw std::runtime_error("pd_test_dataframe_info failed: missing RangeIndex");
                  }

.. _example-intervalindex-type_id-101:

.. dropdown:: type_id (pd_test_3_all.cpp:25592)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 25582
      :emphasize-lines: 11

      // ------------------- pd_test_value_classify (end) ------------------
      
      // ------------------- pd_test_index_type_id (start) ------------------
      namespace dataframe_tests_index_type_id {
      
      void pd_test_index_type_id_dispatch() {
          std::cout << "========= IndexTypeId dispatch =======================";
      
          // RangeIndex
          ::pandas::RangeIndex ri(0, 5);
          if (ri.type_id() != ::pandas::IndexTypeId::RangeIndex)
              throw std::runtime_error("RangeIndex type_id failed");
      
          // Index<string>
          ::pandas::Index<std::string> si(std::vector<std::string>{"a", "b", "c"});
          if (si.type_id() != ::pandas::IndexTypeId::IndexString)
              throw std::runtime_error("Index<string> type_id failed");
      
          // Index<int64>
          ::pandas::Index<numpy::int64> ii(std::vector<numpy::int64>{1, 2, 3});
          if (ii.type_id() != ::pandas::IndexTypeId::IndexInt64)