diff --git a/asv_bench/benchmarks/algorithms.py b/asv_bench/benchmarks/algorithms.py index 192f19c36b47d..6ab8e4f14e979 100644 --- a/asv_bench/benchmarks/algorithms.py +++ b/asv_bench/benchmarks/algorithms.py @@ -50,9 +50,9 @@ def setup(self, unique, sort, dtype): "float": pd.Index(np.random.randn(N), dtype="float64"), "object_str": string_index, "object": pd.Index(np.arange(N), dtype="object"), - "datetime64[ns]": pd.date_range("2011-01-01", freq="H", periods=N), + "datetime64[ns]": pd.date_range("2011-01-01", freq="h", periods=N), "datetime64[ns, tz]": pd.date_range( - "2011-01-01", freq="H", periods=N, tz="Asia/Tokyo" + "2011-01-01", freq="h", periods=N, tz="Asia/Tokyo" ), "Int64": pd.array(np.arange(N), dtype="Int64"), "boolean": pd.array(np.random.randint(0, 2, N), dtype="boolean"), @@ -93,9 +93,9 @@ def setup(self, unique, keep, dtype): "uint": pd.Index(np.arange(N), dtype="uint64"), "float": pd.Index(np.random.randn(N), dtype="float64"), "string": tm.makeStringIndex(N), - "datetime64[ns]": pd.date_range("2011-01-01", freq="H", periods=N), + "datetime64[ns]": pd.date_range("2011-01-01", freq="h", periods=N), "datetime64[ns, tz]": pd.date_range( - "2011-01-01", freq="H", periods=N, tz="Asia/Tokyo" + "2011-01-01", freq="h", periods=N, tz="Asia/Tokyo" ), "timestamp[ms][pyarrow]": pd.Index( np.arange(N), dtype=pd.ArrowDtype(pa.timestamp("ms")) diff --git a/asv_bench/benchmarks/arithmetic.py b/asv_bench/benchmarks/arithmetic.py index 49543c166d047..d70ad144a3455 100644 --- a/asv_bench/benchmarks/arithmetic.py +++ b/asv_bench/benchmarks/arithmetic.py @@ -491,7 +491,7 @@ class BinaryOpsMultiIndex: param_names = ["func"] def setup(self, func): - array = date_range("20200101 00:00", "20200102 0:00", freq="S") + array = date_range("20200101 00:00", "20200102 0:00", freq="s") level_0_names = [str(i) for i in range(30)] index = pd.MultiIndex.from_product([level_0_names, array]) diff --git a/asv_bench/benchmarks/frame_methods.py b/asv_bench/benchmarks/frame_methods.py index e56fbf1d8c32f..c4ab73553cf1a 100644 --- a/asv_bench/benchmarks/frame_methods.py +++ b/asv_bench/benchmarks/frame_methods.py @@ -439,9 +439,9 @@ def setup(self, inplace, dtype): N, M = 10000, 100 if dtype in ("datetime64[ns]", "datetime64[ns, tz]", "timedelta64[ns]"): data = { - "datetime64[ns]": date_range("2011-01-01", freq="H", periods=N), + "datetime64[ns]": date_range("2011-01-01", freq="h", periods=N), "datetime64[ns, tz]": date_range( - "2011-01-01", freq="H", periods=N, tz="Asia/Tokyo" + "2011-01-01", freq="h", periods=N, tz="Asia/Tokyo" ), "timedelta64[ns]": timedelta_range(start="1 day", periods=N, freq="1D"), } @@ -649,7 +649,7 @@ def time_series_nunique_nan(self): class Duplicated: def setup(self): n = 1 << 20 - t = date_range("2015-01-01", freq="S", periods=(n // 64)) + t = date_range("2015-01-01", freq="s", periods=(n // 64)) xs = np.random.randn(n // 64).round(2) self.df = DataFrame( { diff --git a/asv_bench/benchmarks/gil.py b/asv_bench/benchmarks/gil.py index 4993ffd2c47d0..fb4523f78ccb5 100644 --- a/asv_bench/benchmarks/gil.py +++ b/asv_bench/benchmarks/gil.py @@ -212,7 +212,7 @@ def run(dti): def time_datetime_to_period(self): @test_parallel(num_threads=2) def run(dti): - dti.to_period("S") + dti.to_period("s") run(self.dti) diff --git a/asv_bench/benchmarks/groupby.py b/asv_bench/benchmarks/groupby.py index 54c240e84243a..d36d88e7b6b42 100644 --- a/asv_bench/benchmarks/groupby.py +++ b/asv_bench/benchmarks/groupby.py @@ -238,7 +238,7 @@ def time_series_nth(self, dtype): class DateAttributes: def setup(self): - rng = date_range("1/1/2000", "12/31/2005", freq="H") + rng = date_range("1/1/2000", "12/31/2005", freq="h") self.year, self.month, self.day = rng.year, rng.month, rng.day self.ts = Series(np.random.randn(len(rng)), index=rng) diff --git a/asv_bench/benchmarks/indexing.py b/asv_bench/benchmarks/indexing.py index 84d95a23bd446..d8b1bf327294a 100644 --- a/asv_bench/benchmarks/indexing.py +++ b/asv_bench/benchmarks/indexing.py @@ -232,7 +232,7 @@ def setup(self, index): N = 100000 indexes = { "int": Index(np.arange(N), dtype=np.int64), - "datetime": date_range("2011-01-01", freq="S", periods=N), + "datetime": date_range("2011-01-01", freq="s", periods=N), } index = indexes[index] self.s = Series(np.random.rand(N), index=index) @@ -465,7 +465,7 @@ def time_loc_row(self, unique_cols): class AssignTimeseriesIndex: def setup(self): N = 100000 - idx = date_range("1/1/2000", periods=N, freq="H") + idx = date_range("1/1/2000", periods=N, freq="h") self.df = DataFrame(np.random.randn(N, 1), columns=["A"], index=idx) def time_frame_assign_timeseries_index(self): diff --git a/asv_bench/benchmarks/inference.py b/asv_bench/benchmarks/inference.py index 476ff14dcc92a..805b0c807452c 100644 --- a/asv_bench/benchmarks/inference.py +++ b/asv_bench/benchmarks/inference.py @@ -164,7 +164,7 @@ def time_unique_date_strings(self, cache, count): class ToDatetimeISO8601: def setup(self): - rng = date_range(start="1/1/2000", periods=20000, freq="H") + rng = date_range(start="1/1/2000", periods=20000, freq="h") self.strings = rng.strftime("%Y-%m-%d %H:%M:%S").tolist() self.strings_nosep = rng.strftime("%Y%m%d %H:%M:%S").tolist() self.strings_tz_space = [ @@ -276,7 +276,7 @@ def time_dup_string_tzoffset_dates(self, cache): # GH 43901 class ToDatetimeInferDatetimeFormat: def setup(self): - rng = date_range(start="1/1/2000", periods=100000, freq="H") + rng = date_range(start="1/1/2000", periods=100000, freq="h") self.strings = rng.strftime("%Y-%m-%d %H:%M:%S").tolist() def time_infer_datetime_format(self): diff --git a/asv_bench/benchmarks/io/csv.py b/asv_bench/benchmarks/io/csv.py index c5e3e80571e30..1826291034dee 100644 --- a/asv_bench/benchmarks/io/csv.py +++ b/asv_bench/benchmarks/io/csv.py @@ -89,7 +89,7 @@ class ToCSVDatetimeIndex(BaseIO): fname = "__test__.csv" def setup(self): - rng = date_range("2000", periods=100_000, freq="S") + rng = date_range("2000", periods=100_000, freq="s") self.data = DataFrame({"a": 1}, index=rng) def time_frame_date_formatting_index(self): @@ -102,7 +102,7 @@ def time_frame_date_no_format_index(self): class ToCSVPeriod(BaseIO): fname = "__test__.csv" - params = ([1000, 10000], ["D", "H"]) + params = ([1000, 10000], ["D", "h"]) param_names = ["nobs", "freq"] def setup(self, nobs, freq): @@ -110,7 +110,7 @@ def setup(self, nobs, freq): self.data = DataFrame(rng) if freq == "D": self.default_fmt = "%Y-%m-%d" - elif freq == "H": + elif freq == "h": self.default_fmt = "%Y-%m-%d %H:00" def time_frame_period_formatting_default(self, nobs, freq): @@ -130,7 +130,7 @@ def time_frame_period_formatting(self, nobs, freq): class ToCSVPeriodIndex(BaseIO): fname = "__test__.csv" - params = ([1000, 10000], ["D", "H"]) + params = ([1000, 10000], ["D", "h"]) param_names = ["nobs", "freq"] def setup(self, nobs, freq): @@ -138,7 +138,7 @@ def setup(self, nobs, freq): self.data = DataFrame({"a": 1}, index=rng) if freq == "D": self.default_fmt = "%Y-%m-%d" - elif freq == "H": + elif freq == "h": self.default_fmt = "%Y-%m-%d %H:00" def time_frame_period_formatting_index(self, nobs, freq): @@ -253,7 +253,7 @@ class ReadCSVConcatDatetime(StringIORewind): iso8601 = "%Y-%m-%d %H:%M:%S" def setup(self): - rng = date_range("1/1/2000", periods=50000, freq="S") + rng = date_range("1/1/2000", periods=50000, freq="s") self.StringIO_input = StringIO("\n".join(rng.strftime(self.iso8601).tolist())) def time_read_csv(self): diff --git a/asv_bench/benchmarks/io/excel.py b/asv_bench/benchmarks/io/excel.py index c77c6b6f5727c..f8d81b0f6a699 100644 --- a/asv_bench/benchmarks/io/excel.py +++ b/asv_bench/benchmarks/io/excel.py @@ -25,7 +25,7 @@ def _generate_dataframe(): df = DataFrame( np.random.randn(N, C), columns=[f"float{i}" for i in range(C)], - index=date_range("20000101", periods=N, freq="H"), + index=date_range("20000101", periods=N, freq="h"), ) df["object"] = tm.makeStringIndex(N) return df diff --git a/asv_bench/benchmarks/io/hdf.py b/asv_bench/benchmarks/io/hdf.py index f3e417e717609..195aaa158e178 100644 --- a/asv_bench/benchmarks/io/hdf.py +++ b/asv_bench/benchmarks/io/hdf.py @@ -122,7 +122,7 @@ def setup(self, format): self.df = DataFrame( np.random.randn(N, C), columns=[f"float{i}" for i in range(C)], - index=date_range("20000101", periods=N, freq="H"), + index=date_range("20000101", periods=N, freq="h"), ) self.df["object"] = tm.makeStringIndex(N) self.df.to_hdf(self.fname, "df", format=format) diff --git a/asv_bench/benchmarks/io/json.py b/asv_bench/benchmarks/io/json.py index bebf6ee993aba..8a2e3fa87eb37 100644 --- a/asv_bench/benchmarks/io/json.py +++ b/asv_bench/benchmarks/io/json.py @@ -26,7 +26,7 @@ def setup(self, orient, index): N = 100000 indexes = { "int": np.arange(N), - "datetime": date_range("20000101", periods=N, freq="H"), + "datetime": date_range("20000101", periods=N, freq="h"), } df = DataFrame( np.random.randn(N, 5), @@ -48,7 +48,7 @@ def setup(self, index): N = 100000 indexes = { "int": np.arange(N), - "datetime": date_range("20000101", periods=N, freq="H"), + "datetime": date_range("20000101", periods=N, freq="h"), } df = DataFrame( np.random.randn(N, 5), @@ -108,7 +108,7 @@ class ToJSON(BaseIO): def setup(self, orient, frame): N = 10**5 ncols = 5 - index = date_range("20000101", periods=N, freq="H") + index = date_range("20000101", periods=N, freq="h") timedeltas = timedelta_range(start=1, periods=N, freq="s") datetimes = date_range(start=1, periods=N, freq="s") ints = np.random.randint(100000000, size=N) @@ -191,7 +191,7 @@ class ToJSONISO(BaseIO): def setup(self, orient): N = 10**5 - index = date_range("20000101", periods=N, freq="H") + index = date_range("20000101", periods=N, freq="h") timedeltas = timedelta_range(start=1, periods=N, freq="s") datetimes = date_range(start=1, periods=N, freq="s") self.df = DataFrame( @@ -214,7 +214,7 @@ class ToJSONLines(BaseIO): def setup(self): N = 10**5 ncols = 5 - index = date_range("20000101", periods=N, freq="H") + index = date_range("20000101", periods=N, freq="h") timedeltas = timedelta_range(start=1, periods=N, freq="s") datetimes = date_range(start=1, periods=N, freq="s") ints = np.random.randint(100000000, size=N) diff --git a/asv_bench/benchmarks/io/pickle.py b/asv_bench/benchmarks/io/pickle.py index c71cdcdcc5c59..54631d9236887 100644 --- a/asv_bench/benchmarks/io/pickle.py +++ b/asv_bench/benchmarks/io/pickle.py @@ -20,7 +20,7 @@ def setup(self): self.df = DataFrame( np.random.randn(N, C), columns=[f"float{i}" for i in range(C)], - index=date_range("20000101", periods=N, freq="H"), + index=date_range("20000101", periods=N, freq="h"), ) self.df["object"] = tm.makeStringIndex(N) self.df.to_pickle(self.fname) diff --git a/asv_bench/benchmarks/io/stata.py b/asv_bench/benchmarks/io/stata.py index 300b9c778f1f8..750bcf4ccee5c 100644 --- a/asv_bench/benchmarks/io/stata.py +++ b/asv_bench/benchmarks/io/stata.py @@ -23,7 +23,7 @@ def setup(self, convert_dates): self.df = DataFrame( np.random.randn(N, C), columns=[f"float{i}" for i in range(C)], - index=date_range("20000101", periods=N, freq="H"), + index=date_range("20000101", periods=N, freq="h"), ) self.df["object"] = tm.makeStringIndex(self.N) self.df["int8_"] = np.random.randint( diff --git a/asv_bench/benchmarks/join_merge.py b/asv_bench/benchmarks/join_merge.py index 04ac47a892a22..23824c2c748df 100644 --- a/asv_bench/benchmarks/join_merge.py +++ b/asv_bench/benchmarks/join_merge.py @@ -213,7 +213,7 @@ class JoinNonUnique: # GH 6329 def setup(self): date_index = date_range("01-Jan-2013", "23-Jan-2013", freq="min") - daily_dates = date_index.to_period("D").to_timestamp("S", "S") + daily_dates = date_index.to_period("D").to_timestamp("s", "s") self.fracofday = date_index.values - daily_dates.values self.fracofday = self.fracofday.astype("timedelta64[ns]") self.fracofday = self.fracofday.astype(np.float64) / 86_400_000_000_000 diff --git a/asv_bench/benchmarks/period.py b/asv_bench/benchmarks/period.py index 501fe198d41d8..ccd86cae06d58 100644 --- a/asv_bench/benchmarks/period.py +++ b/asv_bench/benchmarks/period.py @@ -45,7 +45,7 @@ def time_from_ints_daily(self, freq, is_offset): class DataFramePeriodColumn: def setup(self): - self.rng = period_range(start="1/1/1990", freq="S", periods=20000) + self.rng = period_range(start="1/1/1990", freq="s", periods=20000) self.df = DataFrame(index=range(len(self.rng))) def time_setitem_period_column(self): diff --git a/asv_bench/benchmarks/series_methods.py b/asv_bench/benchmarks/series_methods.py index f52f7a4bef37a..459d562828f88 100644 --- a/asv_bench/benchmarks/series_methods.py +++ b/asv_bench/benchmarks/series_methods.py @@ -64,7 +64,7 @@ def setup(self, dtype): N = 10**6 data = { "int": np.random.randint(1, 10, N), - "datetime": date_range("2000-01-01", freq="S", periods=N), + "datetime": date_range("2000-01-01", freq="s", periods=N), } self.s = Series(data[dtype]) if dtype == "datetime": @@ -92,7 +92,7 @@ class Fillna: def setup(self, dtype): N = 10**6 if dtype == "datetime64[ns]": - data = date_range("2000-01-01", freq="S", periods=N) + data = date_range("2000-01-01", freq="s", periods=N) na_value = NaT elif dtype in ("float64", "Float64"): data = np.random.randn(N) diff --git a/asv_bench/benchmarks/strftime.py b/asv_bench/benchmarks/strftime.py index 39cc82e1bdf79..47f25b331ab9b 100644 --- a/asv_bench/benchmarks/strftime.py +++ b/asv_bench/benchmarks/strftime.py @@ -53,7 +53,7 @@ def time_frame_datetime_formatting_custom(self, nobs): class PeriodStrftime: timeout = 1500 - params = ([1000, 10000], ["D", "H"]) + params = ([1000, 10000], ["D", "h"]) param_names = ["nobs", "freq"] def setup(self, nobs, freq): @@ -67,7 +67,7 @@ def setup(self, nobs, freq): self.data.set_index("i", inplace=True) if freq == "D": self.default_fmt = "%Y-%m-%d" - elif freq == "H": + elif freq == "h": self.default_fmt = "%Y-%m-%d %H:00" def time_frame_period_to_str(self, nobs, freq): diff --git a/asv_bench/benchmarks/timeseries.py b/asv_bench/benchmarks/timeseries.py index 8c78a9c1723df..8e1deb99a66a4 100644 --- a/asv_bench/benchmarks/timeseries.py +++ b/asv_bench/benchmarks/timeseries.py @@ -27,7 +27,7 @@ def setup(self, index_type): N = 100000 dtidxes = { "dst": date_range( - start="10/29/2000 1:00:00", end="10/29/2000 1:59:59", freq="S" + start="10/29/2000 1:00:00", end="10/29/2000 1:59:59", freq="s" ), "repeated": date_range(start="2000", periods=N / 10, freq="s").repeat(10), "tz_aware": date_range(start="2000", periods=N, freq="s", tz="US/Eastern"), @@ -72,13 +72,13 @@ class TzLocalize: def setup(self, tz): dst_rng = date_range( - start="10/29/2000 1:00:00", end="10/29/2000 1:59:59", freq="S" + start="10/29/2000 1:00:00", end="10/29/2000 1:59:59", freq="s" ) - self.index = date_range(start="10/29/2000", end="10/29/2000 00:59:59", freq="S") + self.index = date_range(start="10/29/2000", end="10/29/2000 00:59:59", freq="s") self.index = self.index.append(dst_rng) self.index = self.index.append(dst_rng) self.index = self.index.append( - date_range(start="10/29/2000 2:00:00", end="10/29/2000 3:00:00", freq="S") + date_range(start="10/29/2000 2:00:00", end="10/29/2000 3:00:00", freq="s") ) def time_infer_dst(self, tz): @@ -90,7 +90,7 @@ class ResetIndex: param_names = "tz" def setup(self, tz): - idx = date_range(start="1/1/2000", periods=1000, freq="H", tz=tz) + idx = date_range(start="1/1/2000", periods=1000, freq="h", tz=tz) self.df = DataFrame(np.random.randn(1000, 2), index=idx) def time_reset_datetimeindex(self, tz): @@ -255,7 +255,7 @@ def time_get_slice(self, monotonic): class Lookup: def setup(self): N = 1500000 - rng = date_range(start="1/1/2000", periods=N, freq="S") + rng = date_range(start="1/1/2000", periods=N, freq="s") self.ts = Series(1, index=rng) self.lookup_val = rng[N // 2]