FloatingDtype

class pandas::FloatingDtype

Data type class for pandas extension types.

Example

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

// Use FloatingDtype
FloatingDtype obj;
// ... operations ...

Constructors

Signature	Location	Example
FloatingDtype() = default	pd_floating_dtype.h:31

Statistics

Signature	Return Type	Location	Example
T max_value() const	T	pd_floating_dtype.h:82
T min_value() const	T	pd_floating_dtype.h:75

Iteration

Signature	Return Type	Location	Example
size_t itemsize() const override	size_t	pd_floating_dtype.h:53

Type Checking

Signature	Return Type	Location	Example
static bool is_finite(T value)	static bool	pd_floating_dtype.h:96
static bool is_inf(T value)	static bool	pd_floating_dtype.h:110
static bool is_nan(T value)	static bool	pd_floating_dtype.h:103	View

Other Methods

Signature	Return Type	Location	Example
T epsilon() const	T	pd_floating_dtype.h:89	View
std::string kind() const override	std::string	pd_floating_dtype.h:61	View
bool matches(const std::string& dtype_name) const	bool	pd_floating_dtype.h:119	View
std::string name() const override	std::string	pd_floating_dtype.h:38	View
numpy::DType numpy_dtype() const override	numpy::DType	pd_floating_dtype.h:46
const std::type_info& type() const override	const std::type_info&	pd_floating_dtype.h:68	View

Code Examples

The following examples are extracted from the test suite.

is_nan (pd_test_5_all.cpp:90959)

                        pandas::SetItemResult expected_kind,
                        int& local_fail) {
    pandas_tests::check(
        got.aligned_values.size() == expected_size,
        label + ".aligned_values_size", local_fail);
    pandas_tests::check(
        got.kind == expected_kind,
        label + ".kind", local_fail);
}

static bool is_nan(double v) {
    return v != v;
}

void case_1_positional_int64() {
    int local_fail = 0;
    auto df = make_abc_frame();
    auto s = make_labelled_series<std::int64_t>(
        {10, 20, 30}, {"a", "b", "c"});
    auto r = pandas::align_series_to_dataframe<std::int64_t>(
        s, df.index(), /*preserve_dtype=*/true);

epsilon (pd_test_5_all.cpp:107634)

    // Block I (Family 3/4 breadth): denormals + extremes.
    if (label == "float64_denorm_min") {
        const double tiny = std::numeric_limits<double>::min();
        return {tiny / 2.0, tiny / 4.0, 0.0};
    }
    if (label == "float64_smallest_normal") {
        const double tiny = std::numeric_limits<double>::min();
        return {tiny, -tiny, 0.0};
    }
    if (label == "float64_dbl_eps") {
        const double eps = std::numeric_limits<double>::epsilon();
        return {eps, -eps, 1.0};
    }
    if (label == "float64_lowest") {
        return {std::numeric_limits<double>::lowest(), 0.0,
                std::numeric_limits<double>::max()};
    }
    if (label == "float64_1e_minus_300") return {1e-300, -1e-300, 0.0};
    if (label == "float64_1e_plus_300")  return {1e300,  -1e300,  1.5e300};
    throw std::runtime_error("unknown float64 label: " + label);
}

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;

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