DatetimeIndexOpsMixin

class pandas::DatetimeIndexOpsMixin

Mixin class providing shared functionality.

Example

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

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

Constructors

Signature	Location	Example
explicit DatetimeIndexOpsMixin(const ArrayType& array, const std::optional<std::string>& name = std::nullopt, bool copy = false)	pd_datetime_index_ops_mixin.h:140
explicit DatetimeIndexOpsMixin(ArrayType&& array, const std::optional<std::string>& name = std::nullopt)	pd_datetime_index_ops_mixin.h:150
DatetimeIndexOpsMixin(const DatetimeIndexOpsMixin& other)	pd_datetime_index_ops_mixin.h:159
DatetimeIndexOpsMixin(DatetimeIndexOpsMixin&& other) noexcept	pd_datetime_index_ops_mixin.h:167

Indexing / Selection

Signature	Return Type	Location	Example
std::optional<std::string> get_freq() const override	std::optional<std::string>	pd_datetime_index_ops_mixin.h:216	View

Data Manipulation

Signature	Return Type	Location	Example
DatetimeIndexOpsMixin rename(const std::optional<std::string>& new_name) const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1474	View

Statistics

Signature	Return Type	Location	Example
std::optional<value_type> mean(std::optional<int> axis = std::nullopt, bool skipna = true) const	std::optional<value_type>	pd_datetime_index_ops_mixin.h:1348	View
IntegerArray<numpy::int32> minute() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:692	View

Time Series

Signature	Return Type	Location	Example
DatetimeIndexOpsMixin asfreq(const std::string& freq, const std::string& how = "start") const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1273	View
DatetimeIndexOpsMixin shift(int64_t periods, const std::optional<std::string>& freq = std::nullopt) const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:423	View
ArrayType shifted(result)	ArrayType	pd_datetime_index_ops_mixin.h:455
ArrayType shifted(result)	ArrayType	pd_datetime_index_ops_mixin.h:477
PeriodArray to_period(const std::string& freq) const	PeriodArray	pd_datetime_index_ops_mixin.h:1306	View
DatetimeArray to_timestamp(const std::string& how = "start") const	DatetimeArray	pd_datetime_index_ops_mixin.h:1292	View
DatetimeIndexOpsMixin tz_convert(const std::string& tz, const std::string& tz_display = "") const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1213	View
DatetimeIndexOpsMixin tz_localize(const std::string& tz, const std::string& ambiguous = "raise", const std::string& nonexistent = "raise", const std::string& tz_display = "") const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1192	View

I/O

Signature	Return Type	Location	Example
std::string to_string() const override	std::string	pd_datetime_index_ops_mixin.h:1413	View

Conversion

Signature	Return Type	Location	Example
DatetimeIndexOpsMixin copy() const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1467	View

Type Checking

Signature	Return Type	Location	Example
BooleanArray is_leap_year() const	BooleanArray	pd_datetime_index_ops_mixin.h:1116	View
BooleanArray is_month_end() const	BooleanArray	pd_datetime_index_ops_mixin.h:962	View
BooleanArray is_month_start() const	BooleanArray	pd_datetime_index_ops_mixin.h:934	View
BooleanArray is_negative() const	BooleanArray	pd_datetime_index_ops_mixin.h:1146	View
BooleanArray is_positive() const	BooleanArray	pd_datetime_index_ops_mixin.h:1134	View
BooleanArray is_quarter_end() const	BooleanArray	pd_datetime_index_ops_mixin.h:1024	View
BooleanArray is_quarter_start() const	BooleanArray	pd_datetime_index_ops_mixin.h:992	View
BooleanArray is_year_end() const	BooleanArray	pd_datetime_index_ops_mixin.h:1087	View
BooleanArray is_year_start() const	BooleanArray	pd_datetime_index_ops_mixin.h:1058	View
BooleanArray is_zero() const	BooleanArray	pd_datetime_index_ops_mixin.h:1158	View

Other Methods

Signature	Return Type	Location	Example
DatetimeIndexOpsMixin ceil(const std::string& freq) const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:361	View
ArrayType ceiled(result)	ArrayType	pd_datetime_index_ops_mixin.h:390
std::unique_ptr<IndexBase> clone() const override	std::unique_ptr<IndexBase>	pd_datetime_index_ops_mixin.h:1402	View
IntegerArray<numpy::int32> day() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:666	View
std::vector<std::string> day_name( const std::optional<std::string>& locale = std::nullopt) const	std::vector<std::string>	pd_datetime_index_ops_mixin.h:600	View
IntegerArray<numpy::int32> dayofweek() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:784	View
IntegerArray<numpy::int32> dayofyear() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:803	View
DatetimeIndexOpsMixin floor(const std::string& freq) const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:317	View
ArrayType floored(result)	ArrayType	pd_datetime_index_ops_mixin.h:346
static std::string format_datetime_strftime(const numpy::datetime64& val, const std::string& format)	static std::string	pd_datetime_index_ops_mixin.h:1520
static std::string format_period_strftime(numpy::int64 ordinal, const std::string& format, PeriodFrequency freq)	static std::string	pd_datetime_index_ops_mixin.h:1546
std::optional<std::string> freq() const	std::optional<std::string>	pd_datetime_index_ops_mixin.h:205	View
std::string freqstr() const	std::string	pd_datetime_index_ops_mixin.h:228	View
gmtime_r(&secs, &tm_time)		pd_datetime_index_ops_mixin.h:1535
gmtime_s(&tm_time, &secs)		pd_datetime_index_ops_mixin.h:1533
IntegerArray<numpy::int32> hour() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:678	View
std::optional<std::string> inferred_freq() const	std::optional<std::string>	pd_datetime_index_ops_mixin.h:241
IntegerArray<numpy::int32> microsecond() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:720	View
IntegerArray<numpy::int32> month() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:654	View
std::vector<std::string> month_name( const std::optional<std::string>& locale = std::nullopt) const	std::vector<std::string>	pd_datetime_index_ops_mixin.h:553	View
IntegerArray<numpy::int32> nanosecond() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:753	View
DatetimeIndexOpsMixin normalize() const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1177	View
static int64_t parse_freq_to_nanoseconds(const std::string& freq)	static int64_t	pd_datetime_index_ops_mixin.h:1495
static int64_t period_ordinal_to_nanoseconds(numpy::int64 ordinal, PeriodFrequency freq)	static int64_t	pd_datetime_index_ops_mixin.h:1561
IntegerArray<numpy::int32> quarter() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:815	View
DatetimeIndexOpsMixin result(std::move(localized), this->name())	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1198	View
DatetimeIndexOpsMixin result(std::move(converted), this->name())	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1216	View
DatetimeIndexOpsMixin result(\*this)	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:1475	View
DatetimeIndexOpsMixin round(const std::string& freq, int decimals = 0) const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:273	View
ArrayType rounded(result)	ArrayType	pd_datetime_index_ops_mixin.h:302
IntegerArray<numpy::int32> second() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:706	View
void set_freq(const std::optional<std::string>& freq)	void	pd_datetime_index_ops_mixin.h:252	View
DatetimeIndexOpsMixin snap(const std::string& freq = "S") const	DatetimeIndexOpsMixin	pd_datetime_index_ops_mixin.h:405	View
std::vector<std::string> strftime(const std::string& date_format) const	std::vector<std::string>	pd_datetime_index_ops_mixin.h:501	View
IntegerArray<numpy::int64> td_days() const	IntegerArray<numpy::int64>	pd_datetime_index_ops_mixin.h:870	View
IntegerArray<numpy::int64> td_microseconds() const	IntegerArray<numpy::int64>	pd_datetime_index_ops_mixin.h:894
IntegerArray<numpy::int64> td_nanoseconds() const	IntegerArray<numpy::int64>	pd_datetime_index_ops_mixin.h:906
IntegerArray<numpy::int64> td_seconds() const	IntegerArray<numpy::int64>	pd_datetime_index_ops_mixin.h:882
FloatingArray<double> total_seconds() const	FloatingArray<double>	pd_datetime_index_ops_mixin.h:918	View
IndexTypeId type_id() const override	IndexTypeId	pd_datetime_index_ops_mixin.h:1406	View
std::string tz() const	std::string	pd_datetime_index_ops_mixin.h:1228	View
bool tz_aware() const	bool	pd_datetime_index_ops_mixin.h:1254	View
std::string tz_display() const	std::string	pd_datetime_index_ops_mixin.h:1241
IntegerArray<numpy::int32> week() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:827	View
IntegerArray<numpy::int32> weekday() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:795	View
IntegerArray<numpy::int32> weekofyear() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:858
IntegerArray<numpy::int32> year() const	IntegerArray<numpy::int32>	pd_datetime_index_ops_mixin.h:642	View

Code Examples

The following examples are extracted from the test suite.

get_freq (pd_test_2_all.cpp:20397)

    std::vector<numpy::datetime64> ts = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Day),
        numpy::datetime64(1LL, numpy::DateTimeUnit::Day),
        numpy::datetime64(2LL, numpy::DateTimeUnit::Day)
    };
    auto dt_idx = std::make_unique<pandas::DatetimeIndex>(ts);
    dt_idx->set_freq(std::string("D"));
    df.set_index(std::move(dt_idx));

    auto s = df.extract_column_as_numeric_series("val");
    check(s.get_freq().has_value(), "freq propagated");
    if (s.get_freq().has_value()) {
        check(s.get_freq().value() == "D", "freq value D");
    }

    // Test MultiIndex propagation
    pandas::DataFrame df2;
    std::vector<numpy::float64> vals2 = {10.0, 20.0};
    df2.insert(0, "A", std::make_unique<pandas::Series<numpy::float64>>(vals2, "A"), true);
    std::vector<std::vector<std::string>> arrays = {{"x", "y"}, {"1", "2"}};
    std::vector<std::optional<std::string>> names = {std::string("first"), std::string("second")};

rename (pd_test_1_all.cpp:5816)

    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;
}

mean (pd_test_1_all.cpp:282)

            std::optional<bool>(true),
            std::optional<bool>(true)
        });

        auto s = arr.sum();
        if (!s.has_value() || s.value() != 3) {
            std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : sum should be 3" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_reductions failed: sum");
        }

        auto m = arr.mean();
        if (!m.has_value() || std::abs(m.value() - 0.75) > 0.001) {
            std::cout << "  [FAIL] : in pd_test_boolean_array_reductions() : mean should be 0.75" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_reductions failed: mean");
        }

        std::cout << " -> tests passed" << std::endl;
    }

    void pd_test_boolean_array_dtype() {
        std::cout << "========= BooleanArray: dtype ======================= ";

minute (pd_test_1_all.cpp:7505)

    std::cout << "========= minute property =============================";

    std::vector<std::optional<numpy::datetime64>> values = {
        make_dt(0),                    // Minute 0
        make_dt(30 * NS_PER_MIN),      // Minute 30
        make_dt(59 * NS_PER_MIN)       // Minute 59
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeIndex idx(arr);

    auto minutes = idx.minute();

    bool passed = (minutes.size() == 3);
    auto m0 = minutes[0];
    auto m1 = minutes[1];
    auto m2 = minutes[2];
    passed = passed && m0.has_value() && *m0 == 0;
    passed = passed && m1.has_value() && *m1 == 30;
    passed = passed && m2.has_value() && *m2 == 59;

    if (!passed) {

asfreq (pd_test_1_all.cpp:2869)

        std::cout << "========= PeriodArray: asfreq ======================= ";

        // Monthly to quarterly
        pandas::PeriodArray arr_m(std::vector<std::string>{
            "2024-01",
            "2024-04",
            "2024-07",
            "NaT"
        }, "M");

        auto arr_q = arr_m.asfreq("Q");
        if (arr_q.size() != 4) {
            std::cout << "  [FAIL] : asfreq size should be 4" << std::endl;
            throw std::runtime_error("pd_test_period_array_asfreq failed: size");
        }
        if (arr_q.freqstr() != "Q") {
            std::cout << "  [FAIL] : asfreq freqstr should be 'Q'" << std::endl;
            throw std::runtime_error("pd_test_period_array_asfreq failed: freqstr");
        }

        // Check NaT is preserved

shift (pd_test_1_all.cpp:5188)

            // 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;
        }

to_period (pd_test_2_all.cpp:14554)

        std::cout << "====================================== [OK] pd_test_to_parquet test suite ========================" << std::endl;
        return 0;
    }

} // namespace dataframe_tests
// ------------------- pd_test_to_parquet.cpp (end) -----------------------------

// ------------------- pd_test_to_period.cpp (start) -----------------------------
// dataframe_tests/pd_test_to_period.cpp
// Test suite for DataFrame.to_period() method

#include <iostream>
#include <stdexcept>
#include <vector>
#include <string>
#include <map>

#include "../pandas/pd_dataframe.h"

// CRITICAL: No using namespace directives

to_timestamp (pd_test_1_all.cpp:2830)

    void pd_test_period_array_to_timestamp() {
        std::cout << "========= PeriodArray: to_timestamp ======================= ";

        pandas::PeriodArray arr(std::vector<std::string>{
            "2024-01",
            "2024-06",
            "NaT"
        }, "M");

        // to_timestamp with start
        auto ts_start = arr.to_timestamp("start");
        if (ts_start.size() != 3) {
            std::cout << "  [FAIL] : to_timestamp size should be 3" << std::endl;
            throw std::runtime_error("pd_test_period_array_to_timestamp failed: size");
        }

        auto ts0 = ts_start[0];
        if (!ts0.has_value()) {
            std::cout << "  [FAIL] : ts_start[0] should have value" << std::endl;
            throw std::runtime_error("pd_test_period_array_to_timestamp failed: ts_start[0]");
        }

tz_convert (pd_test_2_all.cpp:17874)

        std::cout << "====================================== [OK] pd_test_transform test suite ========================== " << std::endl;
        return 0;
    }

} // namespace dataframe_tests
// ------------------- pd_test_transform.cpp (end) -----------------------------

// ------------------- pd_test_tz_convert.cpp (start) -----------------------------
// dataframe_tests/pd_test_tz_convert.cpp
// Test for DataFrame.tz_convert() method

#include <iostream>
#include <stdexcept>
#include <cmath>
#include "../pandas/pd_dataframe.h"

namespace dataframe_tests {
    namespace dataframe_tests_tz_convert {

        void pd_test_tz_convert_basic() {

tz_localize (pd_test_1_all.cpp:1431)

            "2023-06-15"
        });

        // Initially should be timezone-naive
        if (arr.is_tz_aware()) {
            std::cout << "  [FAIL] : array should be timezone-naive initially" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_timezone failed: naive");
        }

        // Localize to UTC
        auto localized = arr.tz_localize("UTC");
        if (!localized.is_tz_aware()) {
            std::cout << "  [FAIL] : localized array should be timezone-aware" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_timezone failed: localize");
        }

        // Verify timezone name in dtype
        auto dt = localized.dtype();
        if (!dt.is_tz_aware()) {
            std::cout << "  [FAIL] : dtype should be timezone-aware" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_timezone failed: dtype tz");

to_string (pd_test_1_all.cpp:2693)

        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];

copy (pd_test_1_all.cpp:5798)

// ============================================================================
// 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;
}

is_leap_year (pd_test_1_all.cpp:1280)

        }

        // is_month_end
        auto me = arr.is_month_end();
        if (!me[1].has_value() || !me[1].value()) {
            std::cout << "  [FAIL] : 2023-03-31 should be month end" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: month end");
        }

        // is_leap_year
        auto ly = arr.is_leap_year();
        if (!ly[2].has_value() || !ly[2].value()) {
            std::cout << "  [FAIL] : 2024 should be leap year" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: leap year");
        }
        if (!ly[0].has_value() || ly[0].value()) {
            std::cout << "  [FAIL] : 2023 should not be leap year" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: not leap year");
        }

        std::cout << " -> tests passed" << std::endl;

is_month_end (pd_test_1_all.cpp:1273)

        }

        // is_month_start
        auto ms = arr.is_month_start();
        if (!ms[0].has_value() || !ms[0].value()) {
            std::cout << "  [FAIL] : 2023-01-01 should be month start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: month start");
        }

        // is_month_end
        auto me = arr.is_month_end();
        if (!me[1].has_value() || !me[1].value()) {
            std::cout << "  [FAIL] : 2023-03-31 should be month end" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: month end");
        }

        // is_leap_year
        auto ly = arr.is_leap_year();
        if (!ly[2].has_value() || !ly[2].value()) {
            std::cout << "  [FAIL] : 2024 should be leap year" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: leap year");

is_month_start (pd_test_1_all.cpp:1266)

        if (!ys[0].has_value() || !ys[0].value()) {
            std::cout << "  [FAIL] : 2023-01-01 should be year start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: year start");
        }
        if (!ys[1].has_value() || ys[1].value()) {
            std::cout << "  [FAIL] : 2023-03-31 should not be year start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: not year start");
        }

        // is_month_start
        auto ms = arr.is_month_start();
        if (!ms[0].has_value() || !ms[0].value()) {
            std::cout << "  [FAIL] : 2023-01-01 should be month start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: month start");
        }

        // is_month_end
        auto me = arr.is_month_end();
        if (!me[1].has_value() || !me[1].value()) {
            std::cout << "  [FAIL] : 2023-03-31 should be month end" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: month end");

is_negative (pd_test_1_all.cpp:4269)

        if (!pos[0].has_value() || !pos[0].value()) {
            std::cout << "  [FAIL] : 1 day should be positive" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: is_positive");
        }
        if (!pos[1].has_value() || pos[1].value()) {
            std::cout << "  [FAIL] : -5 hours should not be positive" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: not positive");
        }

        // is_negative
        auto neg = arr.is_negative();
        if (!neg[1].has_value() || !neg[1].value()) {
            std::cout << "  [FAIL] : -5 hours should be negative" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: is_negative");
        }
        if (!neg[0].has_value() || neg[0].value()) {
            std::cout << "  [FAIL] : 1 day should not be negative" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: not negative");
        }

        // is_zero

is_positive (pd_test_1_all.cpp:4258)

        std::cout << "========= TimedeltaArray: boolean properties ======================= ";

        pandas::TimedeltaArray arr({
            std::optional<numpy::timedelta64>(numpy::timedelta64(1, numpy::DateTimeUnit::Day)),   // positive
            std::optional<numpy::timedelta64>(numpy::timedelta64(-5, numpy::DateTimeUnit::Hour)), // negative
            std::optional<numpy::timedelta64>(numpy::timedelta64(0, numpy::DateTimeUnit::Second)), // zero
            std::nullopt
        });

        // is_positive
        auto pos = arr.is_positive();
        if (!pos[0].has_value() || !pos[0].value()) {
            std::cout << "  [FAIL] : 1 day should be positive" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: is_positive");
        }
        if (!pos[1].has_value() || pos[1].value()) {
            std::cout << "  [FAIL] : -5 hours should not be positive" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: not positive");
        }

        // is_negative

is_quarter_end (pd_test_3_all.cpp:25056)

    };
    pandas::Series<numpy::datetime64> s(dates);
    pandas::DatetimeProperties<pandas::Series<numpy::datetime64>> dt(s);
    if (dt.has_nat()) throw std::runtime_error("has_nat should be false for clean series");
    auto ms = dt.is_month_start();
    if (ms[0] != true || ms[1] != false) throw std::runtime_error("is_month_start failed");
    auto me = dt.is_month_end();
    if (me[1] != true || me[0] != false) throw std::runtime_error("is_month_end failed");
    auto qs = dt.is_quarter_start();
    if (qs[0] != true || qs[1] != false) throw std::runtime_error("is_quarter_start failed");
    auto qe = dt.is_quarter_end();
    if (qe[2] != true || qe[0] != false) throw std::runtime_error("is_quarter_end failed");
    auto ys = dt.is_year_start();
    if (ys[0] != true || ys[1] != false) throw std::runtime_error("is_year_start failed");
    auto ye = dt.is_year_end();
    if (ye[3] != true || ye[0] != false) throw std::runtime_error("is_year_end failed");
    std::cout << " -> tests passed" << std::endl;
}

void pd_test_dt_bool_na_with_nat() {
    std::cout << "========= pd_test_dt_bool_na: series with NaT ==========";

is_quarter_start (pd_test_3_all.cpp:25054)

        numpy::datetime64("2024-03-31"),
        numpy::datetime64("2024-12-31")
    };
    pandas::Series<numpy::datetime64> s(dates);
    pandas::DatetimeProperties<pandas::Series<numpy::datetime64>> dt(s);
    if (dt.has_nat()) throw std::runtime_error("has_nat should be false for clean series");
    auto ms = dt.is_month_start();
    if (ms[0] != true || ms[1] != false) throw std::runtime_error("is_month_start failed");
    auto me = dt.is_month_end();
    if (me[1] != true || me[0] != false) throw std::runtime_error("is_month_end failed");
    auto qs = dt.is_quarter_start();
    if (qs[0] != true || qs[1] != false) throw std::runtime_error("is_quarter_start failed");
    auto qe = dt.is_quarter_end();
    if (qe[2] != true || qe[0] != false) throw std::runtime_error("is_quarter_end failed");
    auto ys = dt.is_year_start();
    if (ys[0] != true || ys[1] != false) throw std::runtime_error("is_year_start failed");
    auto ye = dt.is_year_end();
    if (ye[3] != true || ye[0] != false) throw std::runtime_error("is_year_end failed");
    std::cout << " -> tests passed" << std::endl;
}

is_year_end (pd_test_3_all.cpp:25060)

    auto ms = dt.is_month_start();
    if (ms[0] != true || ms[1] != false) throw std::runtime_error("is_month_start failed");
    auto me = dt.is_month_end();
    if (me[1] != true || me[0] != false) throw std::runtime_error("is_month_end failed");
    auto qs = dt.is_quarter_start();
    if (qs[0] != true || qs[1] != false) throw std::runtime_error("is_quarter_start failed");
    auto qe = dt.is_quarter_end();
    if (qe[2] != true || qe[0] != false) throw std::runtime_error("is_quarter_end failed");
    auto ys = dt.is_year_start();
    if (ys[0] != true || ys[1] != false) throw std::runtime_error("is_year_start failed");
    auto ye = dt.is_year_end();
    if (ye[3] != true || ye[0] != false) throw std::runtime_error("is_year_end failed");
    std::cout << " -> tests passed" << std::endl;
}

void pd_test_dt_bool_na_with_nat() {
    std::cout << "========= pd_test_dt_bool_na: series with NaT ==========";
    std::vector<numpy::datetime64> dates = {
        numpy::datetime64("2024-01-01"),
        numpy::datetime64(),  // NaT
        numpy::datetime64("2024-12-31")

is_year_start (pd_test_1_all.cpp:1255)

        std::cout << "========= DatetimeArray: boolean properties ======================= ";

        pandas::DatetimeArray arr(std::vector<std::string>{
            "2023-01-01",   // year start, month start
            "2023-03-31",   // quarter end, month end
            "2024-02-29",   // leap year (2024 is leap year)
            "2023-12-31"    // year end, month end
        });

        // is_year_start
        auto ys = arr.is_year_start();
        if (!ys[0].has_value() || !ys[0].value()) {
            std::cout << "  [FAIL] : 2023-01-01 should be year start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: year start");
        }
        if (!ys[1].has_value() || ys[1].value()) {
            std::cout << "  [FAIL] : 2023-03-31 should not be year start" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_boolean_props failed: not year start");
        }

        // is_month_start

is_zero (pd_test_1_all.cpp:4280)

        if (!neg[1].has_value() || !neg[1].value()) {
            std::cout << "  [FAIL] : -5 hours should be negative" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: is_negative");
        }
        if (!neg[0].has_value() || neg[0].value()) {
            std::cout << "  [FAIL] : 1 day should not be negative" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: not negative");
        }

        // is_zero
        auto zero = arr.is_zero();
        if (!zero[2].has_value() || !zero[2].value()) {
            std::cout << "  [FAIL] : 0 seconds should be zero" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: is_zero");
        }

        // NA should propagate
        if (pos[3].has_value() || neg[3].has_value() || zero[3].has_value()) {
            std::cout << "  [FAIL] : NaT should propagate to boolean props" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_boolean_props failed: NaT propagation");
        }

ceil (pd_test_1_all.cpp:4949)

                throw std::runtime_error("pd_test_arithmetic_series_round failed: round failed");
            }

            auto f = a.floor();
            passed = std::abs(f[0] - 1.0) < 0.001 && std::abs(f[2] - 3.0) < 0.001 && std::abs(f[3] - (-2.0)) < 0.001;
            if (!passed) {
                std::cout << "  [FAIL] : in pd_test_arithmetic_series_round() : floor failed" << std::endl;
                throw std::runtime_error("pd_test_arithmetic_series_round failed: floor failed");
            }

            auto c = a.ceil();
            passed = std::abs(c[0] - 2.0) < 0.001 && std::abs(c[2] - 4.0) < 0.001 && std::abs(c[3] - (-1.0)) < 0.001;
            if (!passed) {
                std::cout << "  [FAIL] : in pd_test_arithmetic_series_round() : ceil failed" << std::endl;
                throw std::runtime_error("pd_test_arithmetic_series_round failed: ceil failed");
            }

            // Round with decimals
            pandas::Series<double> b({1.234, 2.567, 3.891});
            auto r2 = b.round(2);
            passed = std::abs(r2[0] - 1.23) < 0.001 && std::abs(r2[1] - 2.57) < 0.001;

clone (pd_test_1_all.cpp:5776)

    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;
}

day (pd_test_1_all.cpp:1193)

            std::cout << "  [FAIL] : month[0] should be 3" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[0]");
        }
        auto m1 = months[1];
        if (!m1.has_value() || m1.value() != 12) {
            std::cout << "  [FAIL] : month[1] should be 12" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[1]");
        }

        // Day
        auto days = arr.day();
        auto d0 = days[0];
        if (!d0.has_value() || d0.value() != 15) {
            std::cout << "  [FAIL] : day[0] should be 15" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: day[0]");
        }
        auto d1 = days[1];
        if (!d1.has_value() || d1.value() != 25) {
            std::cout << "  [FAIL] : day[1] should be 25" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: day[1]");
        }

day_name (pd_test_1_all.cpp:8474)

void pd_test_datetime_mixin_day_name() {
    std::cout << "========= day_name ====================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond)  // 1970-01-01 = Thursday
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    std::vector<std::string> names = idx.day_name();

    bool passed = (names.size() == 1 && names[0] == "Thursday");
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_day_name() got: " << names[0] << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_day_name failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

dayofweek (pd_test_1_all.cpp:7565)

    // 1970-01-01 was a Thursday (day 3)
    std::vector<std::optional<numpy::datetime64>> values = {
        make_dt(0),                // Thursday (3)
        make_dt(NS_PER_DAY),       // Friday (4)
        make_dt(2 * NS_PER_DAY),   // Saturday (5)
        make_dt(3 * NS_PER_DAY)    // Sunday (6)
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeIndex idx(arr);

    auto dow = idx.dayofweek();

    bool passed = (dow.size() == 4);
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_index_dayofweek()" << std::endl;
        throw std::runtime_error("pd_test_datetime_index_dayofweek failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

dayofyear (pd_test_3_all.cpp:18582)

    auto seconds = s.dt().second();
    if (seconds[0] != 45 || seconds[1] != 30 || seconds[2] != 59) {
        std::cout << "  [FAIL] : second() failed" << std::endl;
        throw std::runtime_error("pd_test_dt_time_components: second() failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

// ============================================================================
// Test dt().dayofweek(), dt().dayofyear(), dt().quarter()
// ============================================================================

void pd_test_dt_derived_properties() {
    std::cout << "========= Series.dt().dayofweek/dayofyear/quarter() ======";

    // 2020-01-01 is a Wednesday (dayofweek=2), dayofyear=1, Q1
    // 2020-07-04 is a Saturday (dayofweek=5), dayofyear=186, Q3
    pandas::Series<std::string> s({"2020-01-01", "2020-07-04"});

    auto dow = s.dt().dayofweek();

floor (pd_test_1_all.cpp:4942)

            pandas::Series<double> a({1.4, 2.5, 3.6, -1.4, -2.5});

            auto r = a.round();
            bool passed = std::abs(r[0] - 1.0) < 0.001 && std::abs(r[2] - 4.0) < 0.001;
            if (!passed) {
                std::cout << "  [FAIL] : in pd_test_arithmetic_series_round() : round failed" << std::endl;
                throw std::runtime_error("pd_test_arithmetic_series_round failed: round failed");
            }

            auto f = a.floor();
            passed = std::abs(f[0] - 1.0) < 0.001 && std::abs(f[2] - 3.0) < 0.001 && std::abs(f[3] - (-2.0)) < 0.001;
            if (!passed) {
                std::cout << "  [FAIL] : in pd_test_arithmetic_series_round() : floor failed" << std::endl;
                throw std::runtime_error("pd_test_arithmetic_series_round failed: floor failed");
            }

            auto c = a.ceil();
            passed = std::abs(c[0] - 2.0) < 0.001 && std::abs(c[2] - 4.0) < 0.001 && std::abs(c[3] - (-1.0)) < 0.001;
            if (!passed) {
                std::cout << "  [FAIL] : in pd_test_arithmetic_series_round() : ceil failed" << std::endl;

freq (pd_test_1_all.cpp:8233)

    std::cout << "========= freq property ===============================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond),
        numpy::datetime64(86400000000000LL, numpy::DateTimeUnit::Nanosecond)  // 1 day
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    // Default freq is nullopt or inferred
    auto f = idx.freq();
    std::string fs = idx.freqstr();

    bool passed = true;  // freq may or may not be set
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_freq()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_freq failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

freqstr (pd_test_1_all.cpp:2671)

        }

        pandas::PeriodDtype dtype_y("Y");
        if (dtype_y.name() != "period[Y]") {
            std::cout << "  [FAIL] : dtype_y.name() should be 'period[Y]'" << std::endl;
            throw std::runtime_error("pd_test_period_array_freq_validation failed: dtype name Y");
        }

        // Test frequency string
        pandas::PeriodArray arr(std::vector<std::string>{"2024-01-15"}, "D");
        if (arr.freqstr() != "D") {
            std::cout << "  [FAIL] : arr.freqstr() should be 'D'" << std::endl;
            throw std::runtime_error("pd_test_period_array_freq_validation failed: freqstr");
        }

        std::cout << " -> tests passed" << std::endl;
    }

    void pd_test_period_array_year_month_quarter() {
        std::cout << "========= PeriodArray: year/month/quarter components ======================= ";

hour (pd_test_1_all.cpp:7476)

    std::cout << "========= hour property ===============================";

    std::vector<std::optional<numpy::datetime64>> values = {
        make_dt(0),                    // Hour 0
        make_dt(6 * NS_PER_HOUR),      // Hour 6
        make_dt(23 * NS_PER_HOUR)      // Hour 23
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeIndex idx(arr);

    auto hours = idx.hour();

    bool passed = (hours.size() == 3);
    auto h0 = hours[0];
    auto h1 = hours[1];
    auto h2 = hours[2];
    passed = passed && h0.has_value() && *h0 == 0;
    passed = passed && h1.has_value() && *h1 == 6;
    passed = passed && h2.has_value() && *h2 == 23;

    if (!passed) {

microsecond (pd_test_timestamp_scalar.cpp:45)

      // Component constructor
      pandas::Timestamp ts1(2024, 6, 15, 14, 30, 45);
      if (ts1.year() != 2024 || ts1.month() != 6 || ts1.day() != 15 ||
          ts1.hour() != 14 || ts1.minute() != 30 || ts1.second() != 45) {
        pass = false;
        fail_msg = "Component constructor values incorrect";
      }

      // With microseconds and nanoseconds
      pandas::Timestamp ts2(2024, 1, 1, 12, 0, 0, 123456, 789);
      if (ts2.microsecond() != 123456 || ts2.nanosecond() != 789) {
        pass = false;
        fail_msg = "Microsecond/nanosecond values incorrect";
      }

      // String constructor - ISO format
      pandas::Timestamp ts3("2024-06-15T14:30:45");
      if (ts3.year() != 2024 || ts3.month() != 6 || ts3.day() != 15) {
        pass = false;
        fail_msg = "String constructor parse failed";
      }

month (pd_test_1_all.cpp:1180)

    void pd_test_datetime_array_component_month_day() {
        std::cout << "========= DatetimeArray: month/day components ======================= ";

        pandas::DatetimeArray arr(std::vector<std::string>{
            "2023-03-15",
            "2023-12-25",
            "NaT"
        });

        // Month
        auto months = arr.month();
        auto m0 = months[0];
        if (!m0.has_value() || m0.value() != 3) {
            std::cout << "  [FAIL] : month[0] should be 3" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[0]");
        }
        auto m1 = months[1];
        if (!m1.has_value() || m1.value() != 12) {
            std::cout << "  [FAIL] : month[1] should be 12" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[1]");
        }

month_name (pd_test_1_all.cpp:8454)

void pd_test_datetime_mixin_month_name() {
    std::cout << "========= month_name ==================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond)  // 1970-01-01 = January
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    std::vector<std::string> names = idx.month_name();

    bool passed = (names.size() == 1 && names[0] == "January");
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_month_name() got: " << names[0] << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_month_name failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

nanosecond (pd_test_timestamp_scalar.cpp:45)

      // Component constructor
      pandas::Timestamp ts1(2024, 6, 15, 14, 30, 45);
      if (ts1.year() != 2024 || ts1.month() != 6 || ts1.day() != 15 ||
          ts1.hour() != 14 || ts1.minute() != 30 || ts1.second() != 45) {
        pass = false;
        fail_msg = "Component constructor values incorrect";
      }

      // With microseconds and nanoseconds
      pandas::Timestamp ts2(2024, 1, 1, 12, 0, 0, 123456, 789);
      if (ts2.microsecond() != 123456 || ts2.nanosecond() != 789) {
        pass = false;
        fail_msg = "Microsecond/nanosecond values incorrect";
      }

      // String constructor - ISO format
      pandas::Timestamp ts3("2024-06-15T14:30:45");
      if (ts3.year() != 2024 || ts3.month() != 6 || ts3.day() != 15) {
        pass = false;
        fail_msg = "String constructor parse failed";
      }

normalize (pd_test_1_all.cpp:8723)

void pd_test_datetime_mixin_normalize() {
    std::cout << "========= normalize ===================================";

    // Create datetime with time component
    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(86400000000000LL + 3600000000000LL, numpy::DateTimeUnit::Nanosecond)  // 1 day + 1 hour
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    pandas::DatetimeMixinIndex normalized = idx.normalize();

    bool passed = (normalized.size() == 1);
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_normalize()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_normalize failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

quarter (pd_test_1_all.cpp:1218)

    void pd_test_datetime_array_quarter() {
        std::cout << "========= DatetimeArray: quarter ======================= ";

        pandas::DatetimeArray arr(std::vector<std::string>{
            "2023-01-15",  // Q1
            "2023-05-20",  // Q2
            "2023-09-10",  // Q3
            "2023-11-25"   // Q4
        });

        auto quarters = arr.quarter();

        auto q0 = quarters[0];
        if (!q0.has_value() || q0.value() != 1) {
            std::cout << "  [FAIL] : quarter[0] should be 1" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_quarter failed: quarter[0]");
        }
        auto q1 = quarters[1];
        if (!q1.has_value() || q1.value() != 2) {
            std::cout << "  [FAIL] : quarter[1] should be 2" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_quarter failed: quarter[1]");

result (pd_test_1_all.cpp:15406)

    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) {

result (pd_test_1_all.cpp:15406)

    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) {

result (pd_test_1_all.cpp:15406)

    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) {

round (pd_test_1_all.cpp:1688)

    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");
        }

second (pd_test_1_all.cpp:7534)

    std::cout << "========= second property =============================";

    std::vector<std::optional<numpy::datetime64>> values = {
        make_dt(0),                    // Second 0
        make_dt(30 * NS_PER_SEC),      // Second 30
        make_dt(59 * NS_PER_SEC)       // Second 59
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeIndex idx(arr);

    auto seconds = idx.second();

    bool passed = (seconds.size() == 3);
    auto s0 = seconds[0];
    auto s1 = seconds[1];
    auto s2 = seconds[2];
    passed = passed && s0.has_value() && *s0 == 0;
    passed = passed && s1.has_value() && *s1 == 30;
    passed = passed && s2.has_value() && *s2 == 59;

    if (!passed) {

set_freq (pd_test_1_all.cpp:8254)

void pd_test_datetime_mixin_set_freq() {
    std::cout << "========= set_freq ====================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond)
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    idx.set_freq("D");
    auto f = idx.freq();

    bool passed = (f.has_value() && *f == "D");
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_set_freq()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_set_freq failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

snap (pd_test_1_all.cpp:8364)

void pd_test_datetime_mixin_snap() {
    std::cout << "========= snap ========================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(1000000000123456789LL, numpy::DateTimeUnit::Nanosecond)
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    pandas::DatetimeMixinIndex snapped = idx.snap("s");

    bool passed = (snapped.size() == 1);
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_snap()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_snap failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

strftime (pd_test_1_all.cpp:8434)

void pd_test_datetime_mixin_strftime() {
    std::cout << "========= strftime ====================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond),  // 1970-01-01
        numpy::datetime64(86400000000000LL, numpy::DateTimeUnit::Nanosecond)  // 1970-01-02
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    std::vector<std::string> formatted = idx.strftime("%Y-%m-%d");

    bool passed = (formatted.size() == 2 && !formatted[0].empty() && !formatted[1].empty());
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_strftime()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_strftime failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

td_days (pd_test_1_all.cpp:8603)

void pd_test_timedelta_mixin_days() {
    std::cout << "========= days component (Timedelta) ==================";

    std::vector<std::optional<numpy::timedelta64>> values = {
        numpy::timedelta64(172800000000000LL, numpy::DateTimeUnit::Nanosecond)  // 2 days
    };
    pandas::TimedeltaArray arr(values);
    pandas::TimedeltaMixinIndex idx(arr);

    pandas::IntegerArray<numpy::int64> days = idx.td_days();

    bool passed = (days.size() == 1 && days[0].has_value() && *days[0] == 2);
    if (!passed) {
        int64_t got = days[0].has_value() ? *days[0] : -1;
        std::cout << "  [FAIL] : in pd_test_timedelta_mixin_days() expected 2, got " << got << std::endl;
        throw std::runtime_error("pd_test_timedelta_mixin_days failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

total_seconds (pd_test_1_all.cpp:4224)

    void pd_test_timedelta_array_total_seconds() {
        std::cout << "========= TimedeltaArray: total_seconds ======================= ";

        pandas::TimedeltaArray arr({
            std::optional<numpy::timedelta64>(numpy::timedelta64(1, numpy::DateTimeUnit::Day)),
            std::optional<numpy::timedelta64>(numpy::timedelta64(1, numpy::DateTimeUnit::Hour)),
            std::nullopt
        });

        auto total = arr.total_seconds();

        auto t0 = total[0];
        if (!t0.has_value() || std::abs(t0.value() - 86400.0) > 0.001) {
            std::cout << "  [FAIL] : total_seconds[0] should be 86400" << std::endl;
            throw std::runtime_error("pd_test_timedelta_array_total_seconds failed: total_seconds[0]");
        }

        auto t1 = total[1];
        if (!t1.has_value() || std::abs(t1.value() - 3600.0) > 0.001) {
            std::cout << "  [FAIL] : total_seconds[1] should be 3600" << std::endl;

type_id (pd_test_3_all.cpp:25592)

// ------------------- 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)

tz (pd_test_2_all.cpp:17914)

            pandas::DataFrame df(data);
            df.set_index(std::make_unique<pandas::DatetimeIndex>(tz_aware_idx));

            // Verify the index is timezone-aware
            const pandas::DatetimeIndex* original_idx = dynamic_cast<const pandas::DatetimeIndex*>(&df.index());
            if (!original_idx) {
                std::cout << "  [FAIL] : in pd_test_tz_convert_basic() : index is not DatetimeIndex" << std::endl;
                throw std::runtime_error("pd_test_tz_convert_basic failed: index is not DatetimeIndex");
            }

            std::string original_tz = original_idx->tz();
            if (original_tz.empty()) {
                std::cout << "  [FAIL] : in pd_test_tz_convert_basic() : original index is not timezone-aware" << std::endl;
                throw std::runtime_error("pd_test_tz_convert_basic failed: original index is not timezone-aware");
            }

            // Convert to Asia/Shanghai timezone
            pandas::DataFrame df_shanghai = df.tz_convert("Asia/Shanghai");

            // Verify result has a DatetimeIndex
            const pandas::DatetimeIndex* converted_idx = dynamic_cast<const pandas::DatetimeIndex*>(&df_shanghai.index());

tz_aware (pd_test_1_all.cpp:8745)

    std::cout << "========= tz_localize =================================";

    std::vector<std::optional<numpy::datetime64>> values = {
        numpy::datetime64(0LL, numpy::DateTimeUnit::Nanosecond)
    };
    pandas::DatetimeArray arr(values);
    pandas::DatetimeMixinIndex idx(arr);

    pandas::DatetimeMixinIndex localized = idx.tz_localize("UTC");

    bool passed = (localized.size() == 1 && localized.tz_aware());
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_datetime_mixin_tz_localize()" << std::endl;
        throw std::runtime_error("pd_test_datetime_mixin_tz_localize failed");
    }

    std::cout << " -> tests passed" << std::endl;
}

// ============================================================================
// Conversion Method Tests

week (pd_test_timestamp_scalar.cpp:406)

      // 2024-06-15 is a Saturday
      pandas::Timestamp ts(2024, 6, 15);

      if (ts.dayofweek() != 5) { pass = false; fail_msg = "2024-06-15 should be Saturday (5)"; }
      if (ts.day_of_week() != 5) { pass = false; fail_msg = "day_of_week alias"; }
      if (ts.dayofyear() != 167) { pass = false; fail_msg = "2024-06-15 should be day 167"; }
      if (ts.day_of_year() != 167) { pass = false; fail_msg = "day_of_year alias"; }
      if (ts.quarter() != 2) { pass = false; fail_msg = "June is Q2"; }
      if (ts.days_in_month() != 30) { pass = false; fail_msg = "June has 30 days"; }

      int week = ts.week();
      if (week < 1 || week > 53) { pass = false; fail_msg = "week should be 1-53"; }

      if (!pass) {
        std::cout << "  [FAIL] : in np_test_timestamp_derived() : " << fail_msg;
        throw std::runtime_error("np_test_timestamp_derived failed: " + fail_msg);
      }

      std::cout << " -> tests passed" << std::endl;
    }

weekday (pd_test_3_all.cpp:1471)

            std::cout << "  [FAIL] date_range 10-arg form: expected size 10, got "
                      << idx.size() << std::endl;
            throw std::runtime_error("date_range 10-arg form regressed");
        }
    }

    std::cout << " -> tests passed" << std::endl;
}

void pd_test_3_all_period_weekday() {
    std::cout << "========= PeriodArray.weekday() ======================";

    // Create a PeriodArray with some dates
    std::vector<std::optional<numpy::int64>> ordinals = {0, 1, 2, 3, 4};  // Days from epoch
    pandas::PeriodArray arr(ordinals, "D");

    pandas::IntegerArray<numpy::int32> weekdays = arr.weekday();

    if (weekdays.size() != 5) {
        std::cout << "  [FAIL] : in pd_test_3_all_period_weekday() : size should be 5" << std::endl;
        throw std::runtime_error("pd_test_3_all_period_weekday failed: size");

year (pd_test_1_all.cpp:1147)

    void pd_test_datetime_array_component_year() {
        std::cout << "========= DatetimeArray: year component ======================= ";

        pandas::DatetimeArray arr(std::vector<std::string>{
            "2020-01-15",
            "NaT",
            "2025-06-20"
        });

        auto years = arr.year();

        auto y0 = years[0];
        if (!y0.has_value() || y0.value() != 2020) {
            std::cout << "  [FAIL] : year[0] should be 2020" << std::endl;
            throw std::runtime_error("pd_test_datetime_array_component_year failed: year[0]");
        }

        auto y1 = years[1];
        if (y1.has_value()) {
            std::cout << "  [FAIL] : year[1] should be NA (NaT)" << std::endl;