title stringclasses 1
value | text stringlengths 30 426k | id stringlengths 27 30 |
|---|---|---|
pandas/io/sql.py/read_sql_table
def read_sql_table(
table_name: str,
con,
schema: str | None = None,
index_col: str | list[str] | None = None,
coerce_float: bool = True,
parse_dates: list[str] | dict[str, str] | None = None,
columns: list[str] | None = None,
chunksize: int | None = None,... | apositive_train_query0_00000 | |
pandas/io/sql.py/read_sql_query
def read_sql_query(
sql,
con,
index_col: str | list[str] | None = None,
coerce_float: bool = True,
params: list[Any] | Mapping[str, Any] | None = None,
parse_dates: list[str] | dict[str, str] | None = None,
chunksize: int | None = None,
dtype: DtypeArg | N... | apositive_train_query0_00001 | |
setup.py/is_platform_windows
def is_platform_windows():
return sys.platform in ("win32", "cygwin") | negative_train_query0_00000 | |
setup.py/is_platform_mac
def is_platform_mac():
return sys.platform == "darwin" | negative_train_query0_00001 | |
setup.py/build_ext/render_templates
class build_ext:
def render_templates(cls, pxifiles) -> None:
for pxifile in pxifiles:
# build pxifiles first, template extension must be .pxi.in
assert pxifile.endswith(".pxi.in")
outfile = pxifile[:-3]
if (
os... | negative_train_query0_00002 | |
setup.py/build_ext/build_extensions
class build_ext:
def build_extensions(self) -> None:
# if building from c files, don't need to
# generate template output
if _CYTHON_INSTALLED:
self.render_templates(_pxifiles)
super().build_extensions() | negative_train_query0_00003 | |
setup.py/CleanCommand/initialize_options
class CleanCommand:
def initialize_options(self) -> None:
self.all = True
self._clean_me = []
self._clean_trees = []
base = pjoin("pandas", "_libs", "src")
parser = pjoin(base, "parser")
vendored = pjoin(base, "vendored")
... | negative_train_query0_00004 | |
setup.py/CleanCommand/finalize_options
class CleanCommand:
def finalize_options(self) -> None:
pass | negative_train_query0_00005 | |
setup.py/CleanCommand/run
class CleanCommand:
def run(self) -> None:
for clean_me in self._clean_me:
try:
os.unlink(clean_me)
except OSError:
pass
for clean_tree in self._clean_trees:
try:
shutil.rmtree(clean_tree)
... | negative_train_query0_00006 | |
setup.py/CheckSDist/initialize_options
class CheckSDist:
def initialize_options(self) -> None:
sdist_class.initialize_options(self) | negative_train_query0_00007 | |
setup.py/CheckSDist/run
class CheckSDist:
def run(self) -> None:
if "cython" in cmdclass:
self.run_command("cython")
else:
# If we are not running cython then
# compile the extensions correctly
pyx_files = [(self._pyxfiles, "c"), (self._cpp_pyxfiles, "cpp"... | negative_train_query0_00008 | |
setup.py/CheckingBuildExt/check_cython_extensions
class CheckingBuildExt:
def check_cython_extensions(self, extensions) -> None:
for ext in extensions:
for src in ext.sources:
if not os.path.exists(src):
print(f"{ext.name}: -> [{ext.sources}]")
... | negative_train_query0_00009 | |
setup.py/CheckingBuildExt/build_extensions
class CheckingBuildExt:
def build_extensions(self) -> None:
self.check_cython_extensions(self.extensions)
build_ext.build_extensions(self) | negative_train_query0_00010 | |
setup.py/CythonCommand/build_extension
class CythonCommand:
def build_extension(self, ext) -> None:
pass | negative_train_query0_00011 | |
setup.py/DummyBuildSrc/initialize_options
class DummyBuildSrc:
def initialize_options(self) -> None:
self.py_modules_dict = {} | negative_train_query0_00012 | |
setup.py/DummyBuildSrc/finalize_options
class DummyBuildSrc:
def finalize_options(self) -> None:
pass | negative_train_query0_00013 | |
setup.py/DummyBuildSrc/run
class DummyBuildSrc:
def run(self) -> None:
pass | negative_train_query0_00014 | |
setup.py/maybe_cythonize
def maybe_cythonize(extensions, *args, **kwargs):
"""
Render tempita templates before calling cythonize. This is skipped for
* clean
* sdist
"""
if "clean" in sys.argv or "sdist" in sys.argv:
# See https://github.com/cython/cython/issues/1495
return exte... | negative_train_query0_00015 | |
setup.py/srcpath
def srcpath(name=None, suffix=".pyx", subdir="src"):
return pjoin("pandas", subdir, name + suffix) | negative_train_query0_00016 | |
generate_pxi.py/process_tempita
def process_tempita(pxifile, outfile) -> None:
with open(pxifile, encoding="utf-8") as f:
tmpl = f.read()
pyxcontent = Tempita.sub(tmpl)
with open(outfile, "w", encoding="utf-8") as f:
f.write(pyxcontent) | negative_train_query0_00017 | |
generate_pxi.py/main
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("infile", type=str, help="Path to the input file")
parser.add_argument("-o", "--outdir", type=str, help="Path to the output directory")
args = parser.parse_args()
if not args.infile.endswith(".in"):
... | negative_train_query0_00018 | |
generate_version.py/write_version_info
def write_version_info(path) -> None:
version = None
git_version = None
try:
import _version_meson
version = _version_meson.__version__
git_version = _version_meson.__git_version__
except ImportError:
version = versioneer.get_versi... | negative_train_query0_00019 | |
generate_version.py/main
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument(
"-o",
"--outfile",
type=str,
help="Path to write version info to",
required=False,
)
parser.add_argument(
"--print",
default=False,
action=... | negative_train_query0_00020 | |
asv_bench/benchmarks/indexing_engines.py/_get_numeric_engines
def _get_numeric_engines():
engine_names = [
("Int64Engine", np.int64),
("Int32Engine", np.int32),
("Int16Engine", np.int16),
("Int8Engine", np.int8),
("UInt64Engine", np.uint64),
("UInt32Engine", np.uint32... | negative_train_query0_00021 | |
asv_bench/benchmarks/indexing_engines.py/_get_masked_engines
def _get_masked_engines():
engine_names = [
("MaskedInt64Engine", "Int64"),
("MaskedInt32Engine", "Int32"),
("MaskedInt16Engine", "Int16"),
("MaskedInt8Engine", "Int8"),
("MaskedUInt64Engine", "UInt64"),
("M... | negative_train_query0_00022 | |
asv_bench/benchmarks/indexing_engines.py/NumericEngineIndexing/setup
class NumericEngineIndexing:
def setup(self, engine_and_dtype, index_type, unique, N):
engine, dtype = engine_and_dtype
if index_type == "monotonic_incr":
if unique:
arr = np.arange(N * 3, dtype=dtype)
... | negative_train_query0_00023 | |
asv_bench/benchmarks/indexing_engines.py/NumericEngineIndexing/time_get_loc
class NumericEngineIndexing:
def time_get_loc(self, engine_and_dtype, index_type, unique, N):
self.data.get_loc(self.key_early) | negative_train_query0_00024 | |
asv_bench/benchmarks/indexing_engines.py/NumericEngineIndexing/time_get_loc_near_middle
class NumericEngineIndexing:
def time_get_loc_near_middle(self, engine_and_dtype, index_type, unique, N):
# searchsorted performance may be different near the middle of a range
# vs near an endpoint
self.dat... | negative_train_query0_00025 | |
asv_bench/benchmarks/indexing_engines.py/MaskedNumericEngineIndexing/setup
class MaskedNumericEngineIndexing:
def setup(self, engine_and_dtype, index_type, unique, N):
engine, dtype = engine_and_dtype
dtype = dtype.lower()
if index_type == "monotonic_incr":
if unique:
... | negative_train_query0_00026 | |
asv_bench/benchmarks/indexing_engines.py/MaskedNumericEngineIndexing/time_get_loc
class MaskedNumericEngineIndexing:
def time_get_loc(self, engine_and_dtype, index_type, unique, N):
self.data.get_loc(self.key_early) | negative_train_query0_00027 | |
asv_bench/benchmarks/indexing_engines.py/MaskedNumericEngineIndexing/time_get_loc_near_middle
class MaskedNumericEngineIndexing:
def time_get_loc_near_middle(self, engine_and_dtype, index_type, unique, N):
# searchsorted performance may be different near the middle of a range
# vs near an endpoint
... | negative_train_query0_00028 | |
asv_bench/benchmarks/indexing_engines.py/ObjectEngineIndexing/setup
class ObjectEngineIndexing:
def setup(self, index_type):
N = 10**5
values = list("a" * N + "b" * N + "c" * N)
arr = {
"monotonic_incr": np.array(values, dtype=object),
"monotonic_decr": np.array(list(reve... | negative_train_query0_00029 | |
asv_bench/benchmarks/indexing_engines.py/ObjectEngineIndexing/time_get_loc
class ObjectEngineIndexing:
def time_get_loc(self, index_type):
self.data.get_loc("b") | negative_train_query0_00030 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/setup_cache
class DatetimeAccessor:
def setup_cache(self):
N = 100000
series = Series(timedelta_range("1 days", periods=N, freq="h"))
return series | negative_train_query0_00031 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/time_dt_accessor
class DatetimeAccessor:
def time_dt_accessor(self, series):
series.dt | negative_train_query0_00032 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/time_timedelta_days
class DatetimeAccessor:
def time_timedelta_days(self, series):
series.dt.days | negative_train_query0_00033 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/time_timedelta_seconds
class DatetimeAccessor:
def time_timedelta_seconds(self, series):
series.dt.seconds | negative_train_query0_00034 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/time_timedelta_microseconds
class DatetimeAccessor:
def time_timedelta_microseconds(self, series):
series.dt.microseconds | negative_train_query0_00035 | |
asv_bench/benchmarks/timedelta.py/DatetimeAccessor/time_timedelta_nanoseconds
class DatetimeAccessor:
def time_timedelta_nanoseconds(self, series):
series.dt.nanoseconds | negative_train_query0_00036 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/setup
class TimedeltaIndexing:
def setup(self):
self.index = timedelta_range(start="1985", periods=1000, freq="D")
self.index2 = timedelta_range(start="1986", periods=1000, freq="D")
self.series = Series(range(1000), index=self.index)
s... | negative_train_query0_00037 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_get_loc
class TimedeltaIndexing:
def time_get_loc(self):
self.index.get_loc(self.timedelta) | negative_train_query0_00038 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_shallow_copy
class TimedeltaIndexing:
def time_shallow_copy(self):
self.index._view() | negative_train_query0_00039 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_series_loc
class TimedeltaIndexing:
def time_series_loc(self):
self.series.loc[self.timedelta] | negative_train_query0_00040 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_align
class TimedeltaIndexing:
def time_align(self):
DataFrame({"a": self.series, "b": self.series[:500]}) | negative_train_query0_00041 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_intersection
class TimedeltaIndexing:
def time_intersection(self):
self.index.intersection(self.index2) | negative_train_query0_00042 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_union
class TimedeltaIndexing:
def time_union(self):
self.index.union(self.index2) | negative_train_query0_00043 | |
asv_bench/benchmarks/timedelta.py/TimedeltaIndexing/time_unique
class TimedeltaIndexing:
def time_unique(self):
self.index.unique() | negative_train_query0_00044 | |
asv_bench/benchmarks/strings.py/Dtypes/setup
class Dtypes:
def setup(self, dtype):
try:
self.s = Series(
Index([f"i-{i}" for i in range(10000)], dtype=object)._values,
dtype=dtype,
)
except ImportError as err:
raise NotImplementedError ... | negative_train_query0_00045 | |
asv_bench/benchmarks/strings.py/Construction/setup
class Construction:
def setup(self, pd_type, dtype):
series_arr = np.array(
[str(i) * 10 for i in range(100_000)], dtype=self.dtype_mapping[dtype]
)
if pd_type == "series":
self.arr = series_arr
elif pd_type == "f... | negative_train_query0_00046 | |
asv_bench/benchmarks/strings.py/Construction/time_construction
class Construction:
def time_construction(self, pd_type, dtype):
self.pd_mapping[pd_type](self.arr, dtype=dtype) | negative_train_query0_00047 | |
asv_bench/benchmarks/strings.py/Construction/peakmem_construction
class Construction:
def peakmem_construction(self, pd_type, dtype):
self.pd_mapping[pd_type](self.arr, dtype=dtype) | negative_train_query0_00048 | |
asv_bench/benchmarks/strings.py/Methods/time_center
class Methods:
def time_center(self, dtype):
self.s.str.center(100) | negative_train_query0_00049 | |
asv_bench/benchmarks/strings.py/Methods/time_count
class Methods:
def time_count(self, dtype):
self.s.str.count("A") | negative_train_query0_00050 | |
asv_bench/benchmarks/strings.py/Methods/time_endswith
class Methods:
def time_endswith(self, dtype):
self.s.str.endswith("A") | negative_train_query0_00051 | |
asv_bench/benchmarks/strings.py/Methods/time_extract
class Methods:
def time_extract(self, dtype):
with warnings.catch_warnings(record=True):
self.s.str.extract("(\\w*)A(\\w*)") | negative_train_query0_00052 | |
asv_bench/benchmarks/strings.py/Methods/time_findall
class Methods:
def time_findall(self, dtype):
self.s.str.findall("[A-Z]+") | negative_train_query0_00053 | |
asv_bench/benchmarks/strings.py/Methods/time_find
class Methods:
def time_find(self, dtype):
self.s.str.find("[A-Z]+") | negative_train_query0_00054 | |
asv_bench/benchmarks/strings.py/Methods/time_rfind
class Methods:
def time_rfind(self, dtype):
self.s.str.rfind("[A-Z]+") | negative_train_query0_00055 | |
asv_bench/benchmarks/strings.py/Methods/time_fullmatch
class Methods:
def time_fullmatch(self, dtype):
self.s.str.fullmatch("A") | negative_train_query0_00056 | |
asv_bench/benchmarks/strings.py/Methods/time_get
class Methods:
def time_get(self, dtype):
self.s.str.get(0) | negative_train_query0_00057 | |
asv_bench/benchmarks/strings.py/Methods/time_len
class Methods:
def time_len(self, dtype):
self.s.str.len() | negative_train_query0_00058 | |
asv_bench/benchmarks/strings.py/Methods/time_join
class Methods:
def time_join(self, dtype):
self.s.str.join(" ") | negative_train_query0_00059 | |
asv_bench/benchmarks/strings.py/Methods/time_match
class Methods:
def time_match(self, dtype):
self.s.str.match("A") | negative_train_query0_00060 | |
asv_bench/benchmarks/strings.py/Methods/time_normalize
class Methods:
def time_normalize(self, dtype):
self.s.str.normalize("NFC") | negative_train_query0_00061 | |
asv_bench/benchmarks/strings.py/Methods/time_pad
class Methods:
def time_pad(self, dtype):
self.s.str.pad(100, side="both") | negative_train_query0_00062 | |
asv_bench/benchmarks/strings.py/Methods/time_partition
class Methods:
def time_partition(self, dtype):
self.s.str.partition("A") | negative_train_query0_00063 | |
asv_bench/benchmarks/strings.py/Methods/time_rpartition
class Methods:
def time_rpartition(self, dtype):
self.s.str.rpartition("A") | negative_train_query0_00064 | |
asv_bench/benchmarks/strings.py/Methods/time_replace
class Methods:
def time_replace(self, dtype):
self.s.str.replace("A", "\x01\x01") | negative_train_query0_00065 | |
asv_bench/benchmarks/strings.py/Methods/time_translate
class Methods:
def time_translate(self, dtype):
self.s.str.translate({"A": "\x01\x01"}) | negative_train_query0_00066 | |
asv_bench/benchmarks/strings.py/Methods/time_slice
class Methods:
def time_slice(self, dtype):
self.s.str.slice(5, 15, 2) | negative_train_query0_00067 | |
asv_bench/benchmarks/strings.py/Methods/time_startswith
class Methods:
def time_startswith(self, dtype):
self.s.str.startswith("A") | negative_train_query0_00068 | |
asv_bench/benchmarks/strings.py/Methods/time_strip
class Methods:
def time_strip(self, dtype):
self.s.str.strip("A") | negative_train_query0_00069 | |
asv_bench/benchmarks/strings.py/Methods/time_rstrip
class Methods:
def time_rstrip(self, dtype):
self.s.str.rstrip("A") | negative_train_query0_00070 | |
asv_bench/benchmarks/strings.py/Methods/time_lstrip
class Methods:
def time_lstrip(self, dtype):
self.s.str.lstrip("A") | negative_train_query0_00071 | |
asv_bench/benchmarks/strings.py/Methods/time_title
class Methods:
def time_title(self, dtype):
self.s.str.title() | negative_train_query0_00072 | |
asv_bench/benchmarks/strings.py/Methods/time_upper
class Methods:
def time_upper(self, dtype):
self.s.str.upper() | negative_train_query0_00073 | |
asv_bench/benchmarks/strings.py/Methods/time_lower
class Methods:
def time_lower(self, dtype):
self.s.str.lower() | negative_train_query0_00074 | |
asv_bench/benchmarks/strings.py/Methods/time_wrap
class Methods:
def time_wrap(self, dtype):
self.s.str.wrap(10) | negative_train_query0_00075 | |
asv_bench/benchmarks/strings.py/Methods/time_zfill
class Methods:
def time_zfill(self, dtype):
self.s.str.zfill(10) | negative_train_query0_00076 | |
asv_bench/benchmarks/strings.py/Methods/time_isalnum
class Methods:
def time_isalnum(self, dtype):
self.s.str.isalnum() | negative_train_query0_00077 | |
asv_bench/benchmarks/strings.py/Methods/time_isalpha
class Methods:
def time_isalpha(self, dtype):
self.s.str.isalpha() | negative_train_query0_00078 | |
asv_bench/benchmarks/strings.py/Methods/time_isdecimal
class Methods:
def time_isdecimal(self, dtype):
self.s.str.isdecimal() | negative_train_query0_00079 | |
asv_bench/benchmarks/strings.py/Methods/time_isdigit
class Methods:
def time_isdigit(self, dtype):
self.s.str.isdigit() | negative_train_query0_00080 | |
asv_bench/benchmarks/strings.py/Methods/time_islower
class Methods:
def time_islower(self, dtype):
self.s.str.islower() | negative_train_query0_00081 | |
asv_bench/benchmarks/strings.py/Methods/time_isnumeric
class Methods:
def time_isnumeric(self, dtype):
self.s.str.isnumeric() | negative_train_query0_00082 | |
asv_bench/benchmarks/strings.py/Methods/time_isspace
class Methods:
def time_isspace(self, dtype):
self.s.str.isspace() | negative_train_query0_00083 | |
asv_bench/benchmarks/strings.py/Methods/time_istitle
class Methods:
def time_istitle(self, dtype):
self.s.str.istitle() | negative_train_query0_00084 | |
asv_bench/benchmarks/strings.py/Methods/time_isupper
class Methods:
def time_isupper(self, dtype):
self.s.str.isupper() | negative_train_query0_00085 | |
asv_bench/benchmarks/strings.py/Repeat/setup
class Repeat:
def setup(self, repeats):
N = 10**5
self.s = Series(Index([f"i-{i}" for i in range(N)], dtype=object))
repeat = {"int": 1, "array": np.random.randint(1, 3, N)}
self.values = repeat[repeats] | negative_train_query0_00086 | |
asv_bench/benchmarks/strings.py/Repeat/time_repeat
class Repeat:
def time_repeat(self, repeats):
self.s.str.repeat(self.values) | negative_train_query0_00087 | |
asv_bench/benchmarks/strings.py/Cat/setup
class Cat:
def setup(self, other_cols, sep, na_rep, na_frac):
N = 10**5
mask_gen = lambda: np.random.choice([True, False], N, p=[1 - na_frac, na_frac])
self.s = Series(Index([f"i-{i}" for i in range(N)], dtype=object)).where(
mask_gen()
... | negative_train_query0_00088 | |
asv_bench/benchmarks/strings.py/Cat/time_cat
class Cat:
def time_cat(self, other_cols, sep, na_rep, na_frac):
# before the concatenation (one caller + other_cols columns), the total
# expected fraction of rows containing any NaN is:
# reduce(lambda t, _: t + (1 - t) * na_frac, range(other_cols +... | negative_train_query0_00089 | |
asv_bench/benchmarks/strings.py/Contains/setup
class Contains:
def setup(self, dtype, regex):
super().setup(dtype) | negative_train_query0_00090 | |
asv_bench/benchmarks/strings.py/Contains/time_contains
class Contains:
def time_contains(self, dtype, regex):
self.s.str.contains("A", regex=regex) | negative_train_query0_00091 | |
asv_bench/benchmarks/strings.py/Split/setup
class Split:
def setup(self, dtype, expand):
super().setup(dtype)
self.s = self.s.str.join("--") | negative_train_query0_00092 | |
asv_bench/benchmarks/strings.py/Split/time_split
class Split:
def time_split(self, dtype, expand):
self.s.str.split("--", expand=expand) | negative_train_query0_00093 | |
asv_bench/benchmarks/strings.py/Split/time_rsplit
class Split:
def time_rsplit(self, dtype, expand):
self.s.str.rsplit("--", expand=expand) | negative_train_query0_00094 | |
asv_bench/benchmarks/strings.py/Extract/setup
class Extract:
def setup(self, dtype, expand):
super().setup(dtype) | negative_train_query0_00095 | |
asv_bench/benchmarks/strings.py/Extract/time_extract_single_group
class Extract:
def time_extract_single_group(self, dtype, expand):
with warnings.catch_warnings(record=True):
self.s.str.extract("(\\w*)A", expand=expand) | negative_train_query0_00096 | |
asv_bench/benchmarks/strings.py/Dummies/setup
class Dummies:
def setup(self, dtype):
super().setup(dtype)
N = len(self.s) // 5
self.s = self.s[:N].str.join("|") | negative_train_query0_00097 |
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