BYearBegin#
-
class pandas::BYearBegin#
pandas C++ class.
Example#
#include <pandas/pandas.h>
using namespace pandas;
// Use BYearBegin
BYearBegin obj;
// ... operations ...
Aggregation#
Signature |
Return Type |
Location |
Example |
|---|---|---|---|
|
numpy::datetime64 |
pd_dateoffset.h:1504 |
Type Checking#
Signature |
Return Type |
Location |
Example |
|---|---|---|---|
|
bool |
pd_dateoffset.h:1490 |
|
|
bool |
pd_dateoffset.h:1541 |
Other Methods#
Signature |
Return Type |
Location |
Example |
|---|---|---|---|
|
std::string |
pd_dateoffset.h:1493 |
|
|
int |
pd_dateoffset.h:1489 |
|
|
std::string |
pd_dateoffset.h:1496 |
|
|
std::string |
pd_dateoffset.h:1497 |
|
|
int64_t |
pd_dateoffset.h:1491 |
Code Examples#
The following examples are extracted from the test suite.
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 ======================= ";
month (pd_test_1_all.cpp:1180)
1170 void pd_test_datetime_array_component_month_day() {
1171 std::cout << "========= DatetimeArray: month/day components ======================= ";
1172
1173 pandas::DatetimeArray arr(std::vector<std::string>{
1174 "2023-03-15",
1175 "2023-12-25",
1176 "NaT"
1177 });
1178
1179 // Month
1180 auto months = arr.month();
1181 auto m0 = months[0];
1182 if (!m0.has_value() || m0.value() != 3) {
1183 std::cout << " [FAIL] : month[0] should be 3" << std::endl;
1184 throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[0]");
1185 }
1186 auto m1 = months[1];
1187 if (!m1.has_value() || m1.value() != 12) {
1188 std::cout << " [FAIL] : month[1] should be 12" << std::endl;
1189 throw std::runtime_error("pd_test_datetime_array_component_month_day failed: month[1]");
1190 }
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;
repr (pd_test_1_all.cpp:10906)
10896 std::cout << " -> tests passed" << std::endl;
10897}
10898
10899void pd_test_extension_index_repr() {
10900 std::cout << "========= repr =========================";
10901
10902 pandas::CategoricalArray arr({"a", "b", "c"});
10903 // Use ExtensionIndex<CategoricalArray> directly to test base class repr
10904 pandas::ExtensionIndex<pandas::CategoricalArray> idx(arr, "test");
10905
10906 std::string repr_str = idx.repr();
10907
10908 bool passed = (!repr_str.empty() && repr_str.find("ExtensionIndex") != std::string::npos);
10909 if (!passed) {
10910 std::cout << " [FAIL] : in pd_test_extension_index_repr() : repr check failed" << std::endl;
10911 throw std::runtime_error("pd_test_extension_index_repr failed");
10912 }
10913
10914 std::cout << " -> tests passed" << std::endl;
10915}