Milli#

class pandas::Milli#

pandas C++ class.

Example#

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

// Use Milli
Milli obj;
// ... operations ...

Constructors#

Signature

Location

Example

Milli(int n = 1, bool normalize = false) : DateOffset(n, normalize)

pd_dateoffset.h:855

View

Aggregation#

Signature

Return Type

Location

Example

numpy::datetime64 apply(const numpy::datetime64& dt) const override

numpy::datetime64

pd_dateoffset.h:861

View

Type Checking#

Signature

Return Type

Location

Example

bool is_on_offset(const numpy::datetime64& dt) const override

bool

pd_dateoffset.h:867

View

Other Methods#

Signature

Return Type

Location

Example

std::string freqstr() const override

std::string

pd_dateoffset.h:857

View

std::string name() const override

std::string

pd_dateoffset.h:858

View

int64_t total_nanoseconds() const override { return static_cast<int64_t>(n_) \* 1000000LL

int64_t

pd_dateoffset.h:859

Code Examples#

The following examples are extracted from the test suite.

Milli (pd_test_5_all.cpp:124141)
124131    }
124132
124133    if (subclass == "Day")                   return pandas::Day(n).repr();
124134    if (subclass == "BusinessDay")           return pandas::BusinessDay(n).repr();
124135    if (subclass == "Hour")                  return pandas::Hour(n).repr();
124136    if (subclass == "Minute")                return pandas::Minute(n).repr();
124137    if (subclass == "Second")                return pandas::Second(n).repr();
124138    if (subclass == "Week")                  return pandas::Week(n).repr();
124139    if (subclass == "MonthEnd")              return pandas::MonthEnd(n).repr();
124140    if (subclass == "MonthBegin")            return pandas::MonthBegin(n).repr();
124141    if (subclass == "Milli")                 return pandas::Milli(n).repr();
124142    if (subclass == "Micro")                 return pandas::Micro(n).repr();
124143    if (subclass == "Nano")                  return pandas::Nano(n).repr();
124144    if (subclass == "BusinessMonthEnd")      return pandas::BusinessMonthEnd(n).repr();
124145    if (subclass == "BusinessMonthBegin")    return pandas::BusinessMonthBegin(n).repr();
124146    if (subclass == "BusinessHour")          return pandas::BusinessHour(n).repr();
124147    if (subclass == "CustomBusinessDay")     return pandas::CustomBusinessDay(n).repr();
124148    if (subclass == "CustomBusinessHour")    return pandas::CustomBusinessHour(n).repr();
124149    if (subclass == "YearEnd")               return pandas::YearEnd(n, false, anchor_value).repr();
124150    if (subclass == "YearBegin")             return pandas::YearBegin(n, false, anchor_value).repr();
124151    if (subclass == "QuarterEnd")            return pandas::QuarterEnd(n, false, anchor_value).repr();
apply (pd_test_1_all.cpp:11244)
11234        void pd_test_func_apply_dataframe_apply_axis0() {
11235            std::cout << "========= DataFrame apply axis=0 ======================";
11236
11237            std::map<std::string, std::vector<double>> data = {
11238                {"A", {1.0, 2.0, 3.0}},
11239                {"B", {4.0, 5.0, 6.0}}
11240            };
11241            pandas::DataFrame df(data);
11242
11243            // apply axis=0 applies function to each column
11244            auto result = df.apply([](const std::vector<double>& col) {
11245                return std::accumulate(col.begin(), col.end(), 0.0);
11246            }, 0);
11247
11248            bool passed = true;
11249
11250            // Plan F·dtype: axis=0 reduce now returns a single "result" column
11251            // with the original column names ("A", "B") as the row index.
11252            // Sum of A: 1+2+3=6, Sum of B: 4+5+6=15
11253            const auto& result_col = result["result"];
11254            double sum_a = std::stod(result_col.get_value_str(0));
is_on_offset (pd_test_3_all.cpp:18263)
18253void pd_test_business_day_offset() {
18254    std::cout << "========= BusinessDay offset ===========================";
18255
18256    pandas::BusinessDay offset(1);
18257    if (offset.freqstr() != "B") {
18258        std::cout << "  [FAIL] : BusinessDay freqstr() failed" << std::endl;
18259        throw std::runtime_error("pd_test_business_day_offset: freqstr() failed");
18260    }
18261
18262    // Test is_on_offset (Friday = weekday)
18263    numpy::datetime64 friday("2020-01-17");  // Friday
18264    if (!offset.is_on_offset(friday)) {
18265        std::cout << "  [FAIL] : BusinessDay is_on_offset(Friday) failed" << std::endl;
18266        throw std::runtime_error("pd_test_business_day_offset: is_on_offset(Friday) failed");
18267    }
18268
18269    // Test is_on_offset (Saturday = weekend)
18270    numpy::datetime64 saturday("2020-01-18");  // Saturday
18271    if (offset.is_on_offset(saturday)) {
18272        std::cout << "  [FAIL] : BusinessDay is_on_offset(Saturday) should be false" << std::endl;
freqstr (pd_test_1_all.cpp:2671)
2661        }
2662
2663        pandas::PeriodDtype dtype_y("Y");
2664        if (dtype_y.name() != "period[Y]") {
2665            std::cout << "  [FAIL] : dtype_y.name() should be 'period[Y]'" << std::endl;
2666            throw std::runtime_error("pd_test_period_array_freq_validation failed: dtype name Y");
2667        }
2668
2669        // Test frequency string
2670        pandas::PeriodArray arr(std::vector<std::string>{"2024-01-15"}, "D");
2671        if (arr.freqstr() != "D") {
2672            std::cout << "  [FAIL] : arr.freqstr() should be 'D'" << std::endl;
2673            throw std::runtime_error("pd_test_period_array_freq_validation failed: freqstr");
2674        }
2675
2676        std::cout << " -> tests passed" << std::endl;
2677    }
2678
2679    void pd_test_period_array_year_month_quarter() {
2680        std::cout << "========= PeriodArray: year/month/quarter components ======================= ";
name (pd_test_1_all.cpp:295)
285            throw std::runtime_error("pd_test_boolean_array_reductions failed: mean");
286        }
287
288        std::cout << " -> tests passed" << std::endl;
289    }
290
291    void pd_test_boolean_array_dtype() {
292        std::cout << "========= BooleanArray: dtype ======================= ";
293
294        pandas::BooleanArray arr;
295        if (arr.dtype().name() != "boolean") {
296            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype name should be 'boolean'" << std::endl;
297            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype name");
298        }
299
300        if (arr.dtype().kind() != "b") {
301            std::cout << "  [FAIL] : in pd_test_boolean_array_dtype() : dtype kind should be 'b'" << std::endl;
302            throw std::runtime_error("pd_test_boolean_array_dtype failed: dtype kind");
303        }
304
305        std::cout << " -> tests passed" << std::endl;