PeriodDtype

class pandas::PeriodDtype

Data type class for pandas extension types.

Example

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

// Use PeriodDtype
PeriodDtype obj;
// ... operations ...

Constructors

Signature	Location	Example
explicit PeriodDtype(PeriodFrequency freq)	pd_period_dtype.h:54
explicit PeriodDtype(const std::string& freq_str)	pd_period_dtype.h:62

Iteration

Signature	Return Type	Location	Example
size_t itemsize() const override	size_t	pd_period_dtype.h:87

Other Methods

Signature	Return Type	Location	Example
PeriodFrequency freq() const	PeriodFrequency	pd_period_dtype.h:109	View
std::string freq_string() const	std::string	pd_period_dtype.h:116	View
std::string kind() const override	std::string	pd_period_dtype.h:95	View
bool matches(const std::string& dtype_name) const	bool	pd_period_dtype.h:125	View
std::string name() const override	std::string	pd_period_dtype.h:72	View
numpy::DType numpy_dtype() const override	numpy::DType	pd_period_dtype.h:80
std::string repr() const override	std::string	pd_period_dtype.h:136	View
const std::type_info& type() const override	const std::type_info&	pd_period_dtype.h:102	View
PeriodDtype with_freq(PeriodFrequency new_freq) const	PeriodDtype	pd_period_dtype.h:143
PeriodDtype with_freq(const std::string& new_freq) const	PeriodDtype	pd_period_dtype.h:150

Code Examples

The following examples are extracted from the test suite.

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;
}

freq_string (pd_test_1_all.cpp:15733)

    bool passed = (isnan_mask.size() == 2);
    if (!passed) {
        std::cout << "  [FAIL] : in pd_test_period_index_isnan() : _isnan check failed" << std::endl;
        throw std::runtime_error("pd_test_period_index_isnan failed");
    }

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

// ============================================================================
// unit() and freq_string() Tests
// ============================================================================

void pd_test_unit_freq_string() {
    std::cout << "========= unit() / freq_string() =========================";

    // PeriodIndex with monthly frequency
    numpy::NDArray<numpy::int64> data(std::vector<size_t>{1});
    data.setElementAt({0}, numpy::int64(0));

    numpy::NDArray<numpy::bool_> mask(std::vector<size_t>{1});

kind (pd_test_1_all.cpp:300)

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

        pandas::BooleanArray arr;
        if (arr.dtype().name() != "boolean") {
            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype name should be 'boolean'" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype name");
        }

        if (arr.dtype().kind() != "b") {
            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype kind should be 'b'" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype kind");
        }

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

int pd_test_boolean_array_main() {
    std::cout << "====================================== running pd_test_boolean_array ==================================== " << std::endl;

matches (pd_test_5_all.cpp:15741)

    for (size_t i = 0; i < 5; ++i) {
        // DatetimeIndex serializes individual entries via get_value_str()
        bdate_first5.push_back(idx.get_value_str(i));
    }
    std::cout << "  case_4 bdate_range first 5: ";
    for (auto& s : bdate_first5) std::cout << s << " ";
    std::cout << "\n  case_4 expected first 5:    ";
    for (auto& s : expected_visible_head) std::cout << s << " ";
    std::cout << "\n";

    // First date matches (both start at 2023-01-04)
    pandas_tests::check(contains(bdate_first5[0], "2023-01-04"),
          "case_4.first_bdate_is_2023-01-04", local_fail);

    // Second date should differ: bdate gives 2023-01-05, fixture wants 2023-01-20
    bool second_matches_expected = contains(bdate_first5[1], "2023-01-20");
    pandas_tests::check(!second_matches_expected,
          "case_4.bdate_NOT_matching_filtered_fixture", local_fail);
    // The bdate second is the next business day:
    pandas_tests::check(contains(bdate_first5[1], "2023-01-05"),
          "case_4.bdate_second_is_2023-01-05_sequential", local_fail);

name (pd_test_1_all.cpp:295)

            throw std::runtime_error("pd_test_boolean_array_reductions failed: mean");
        }

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

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

        pandas::BooleanArray arr;
        if (arr.dtype().name() != "boolean") {
            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype name should be 'boolean'" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype name");
        }

        if (arr.dtype().kind() != "b") {
            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype kind should be 'b'" << std::endl;
            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype kind");
        }

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

repr (pd_test_1_all.cpp:10906)

    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;
}

type (pd_test_3_all.cpp:15450)

/**
 * Test Series.convert_dtypes() parameter flags
 */
void pd_test_series_convert_dtypes_flags() {
    std::cout << "========= Series.convert_dtypes() flags =================";

    // Test convert_integer=false - with floats disabled too, so it becomes string/object
    pandas::Series<std::string> s({"1", "2", "3"}, "numbers");
    auto converted = s.convert_dtypes(true, true, false, true, false);  // convert_integer=false, convert_floating=false

    // Should remain object type (Series<std::string> has dtype_name()="object")
    // When integer and floating are both disabled for integer-like strings, it falls back to string type
    if (converted->dtype_name() != "object") {
        std::cout << "  [FAIL] : dtype should be object when convert_integer=false and convert_floating=false, got " << converted->dtype_name() << std::endl;
        throw std::runtime_error("pd_test_series_convert_dtypes_flags failed: convert_integer");
    }

    // Test convert_boolean=false - strings stay as object/string type
    pandas::Series<std::string> s_bool({"true", "false"}, "bools");
    auto converted_bool = s_bool.convert_dtypes(true, true, true, false, true);  // convert_boolean=false