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test_windowing.py
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import numpy as np
import pandas as pd
from pandas import (
DataFrame,
Series,
date_range,
)
from pandas.core.window import (
Rolling,
Window,
)
from typing_extensions import assert_type
from tests import check
IDX = date_range("1/1/2000", periods=700, freq="D")
S = Series(np.random.standard_normal(700))
DF = DataFrame({"col1": S, "col2": S})
def test_rolling_basic() -> None:
check(assert_type(DF.rolling(10, win_type="gaussian"), "Window[DataFrame]"), Window)
check(assert_type(DF.rolling(10, min_periods=10), "Rolling[DataFrame]"), Rolling)
def test_rolling_basic_math() -> None:
check(assert_type(DF.rolling(10, min_periods=10).count(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).sum(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).mean(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).median(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).var(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).std(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).min(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).max(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).corr(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).cov(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).skew(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).kurt(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10, min_periods=10).sem(), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).quantile(0.5), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).rank("average"), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).rank("min"), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).rank("max"), DataFrame), DataFrame)
def test_rolling_apply() -> None:
check(assert_type(DF.rolling(10).apply(np.mean), DataFrame), DataFrame)
def _mean(df: DataFrame) -> Series:
return df.mean()
check(assert_type(DF.rolling(10).apply(_mean), DataFrame), DataFrame)
def _mean2(df: DataFrame) -> np.ndarray:
return np.mean(df, axis=0)
check(assert_type(DF.rolling(10).apply(_mean2, raw=True), DataFrame), DataFrame)
def _mean4(df: DataFrame) -> float:
return float(np.mean(df))
check(assert_type(DF.rolling(10).apply(_mean4, raw=True), DataFrame), DataFrame)
def test_rolling_aggregate() -> None:
check(assert_type(DF.rolling(10).aggregate(np.mean), DataFrame), DataFrame)
check(
assert_type(DF.rolling(10).aggregate(["mean", np.mean]), DataFrame), DataFrame
)
check(
assert_type(
DF.rolling(10).aggregate({"col1": "mean", "col2": np.mean}), DataFrame
),
DataFrame,
)
check(assert_type(DF.rolling(10).agg("sum"), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).aggregate(np.mean), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).aggregate("mean"), DataFrame), DataFrame)
def _mean(df: DataFrame) -> Series:
return df.mean()
check(assert_type(DF.rolling(10).aggregate(_mean), DataFrame), DataFrame)
check(assert_type(DF.rolling(10).aggregate([np.mean]), DataFrame), DataFrame)
check(
assert_type(DF.rolling(10).aggregate([np.mean, "mean"]), DataFrame), DataFrame
)
check(
assert_type(
DF.rolling(10).aggregate({"col1": np.mean, "col2": "mean"}), DataFrame
),
DataFrame,
)
check(
assert_type(
DF.rolling(10).aggregate({"col1": [np.mean, "mean"], "col2": "mean"}),
DataFrame,
),
DataFrame,
)
# func: np.ufunc | Callable | str | list[Callable | str, np.ufunc] | dict[Hashable, Callable | str | np.ufunc| list[Callable | str]]
check(assert_type(DF.rolling(10).agg("sum"), DataFrame), DataFrame)
def test_rolling_basic_math_series() -> None:
check(assert_type(S.rolling(10, min_periods=10).count(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).sum(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).mean(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).median(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).var(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).std(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).min(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).max(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).corr(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).cov(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).skew(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).kurt(), Series), Series)
check(assert_type(S.rolling(10, min_periods=10).sem(), Series), Series)
check(assert_type(S.rolling(10).quantile(0.5), Series), Series)
check(assert_type(S.rolling(10).rank("average"), Series), Series)
check(assert_type(S.rolling(10).rank("min"), Series), Series)
check(assert_type(S.rolling(10).rank("max"), Series), Series)
def test_rolling_apply_series() -> None:
check(assert_type(S.rolling(10).apply(np.mean), Series), Series)
def _mean(df: Series) -> float:
return df.mean()
check(assert_type(S.rolling(10).apply(_mean), Series), Series)
def _mean2(df: Series) -> np.ndarray:
return np.mean(df, axis=0)
check(assert_type(S.rolling(10).apply(_mean2, raw=True), Series), Series)
def test_rolling_aggregate_series() -> None:
check(assert_type(S.rolling(10).aggregate(np.mean), Series), Series)
check(assert_type(S.rolling(10).aggregate("mean"), Series), Series)
def _mean(s: Series) -> float:
return s.mean()
check(assert_type(S.rolling(10).aggregate(_mean), Series), Series)
check(assert_type(S.rolling(10).aggregate([np.mean]), DataFrame), DataFrame)
check(assert_type(S.rolling(10).aggregate([np.mean, "mean"]), DataFrame), DataFrame)
check(
assert_type(
S.rolling(10).aggregate({"col1": np.mean, "col2": "mean", "col3": _mean}),
DataFrame,
),
DataFrame,
)
check(assert_type(S.rolling(10).agg("sum"), Series), Series)
def test_expanding_basic_math() -> None:
check(assert_type(DF.expanding(10).count(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).sum(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).mean(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).median(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).var(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).std(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).min(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).max(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).corr(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).cov(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).skew(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).kurt(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).sem(), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).quantile(0.5), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).rank("average"), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).rank("min"), DataFrame), DataFrame)
check(assert_type(DF.expanding(10).rank("max"), DataFrame), DataFrame)
def test_expanding_apply() -> None:
check(assert_type(DF.expanding(10).apply(np.mean), DataFrame), DataFrame)
def _mean(df: DataFrame) -> Series:
return df.mean()
check(assert_type(DF.expanding(10).apply(_mean), DataFrame), DataFrame)
def _mean2(df: DataFrame) -> np.ndarray:
return np.mean(df, axis=0)
check(assert_type(DF.expanding(10).apply(_mean2, raw=True), DataFrame), DataFrame)
def _mean4(df: DataFrame) -> float:
return float(np.mean(df))
check(assert_type(DF.expanding(10).apply(_mean4, raw=True), DataFrame), DataFrame)
def test_expanding_aggregate() -> None:
check(assert_type(DF.expanding(10).aggregate(np.mean), DataFrame), DataFrame)
check(
assert_type(DF.expanding(10).aggregate(["mean", np.mean]), DataFrame), DataFrame
)
check(
assert_type(
DF.expanding(10).aggregate({"col1": "mean", "col2": np.mean}), DataFrame
),
DataFrame,
)
check(assert_type(DF.expanding(10).agg("sum"), DataFrame), DataFrame)
def test_expanding_basic_math_series() -> None:
check(assert_type(S.expanding(10).count(), Series), Series)
check(assert_type(S.expanding(10).sum(), Series), Series)
check(assert_type(S.expanding(10).mean(), Series), Series)
check(assert_type(S.expanding(10).median(), Series), Series)
check(assert_type(S.expanding(10).var(), Series), Series)
check(assert_type(S.expanding(10).std(), Series), Series)
check(assert_type(S.expanding(10).min(), Series), Series)
check(assert_type(S.expanding(10).max(), Series), Series)
check(assert_type(S.expanding(10).corr(), Series), Series)
check(assert_type(S.expanding(10).cov(), Series), Series)
check(assert_type(S.expanding(10).skew(), Series), Series)
check(assert_type(S.expanding(10).kurt(), Series), Series)
check(assert_type(S.expanding(10).sem(), Series), Series)
check(assert_type(S.expanding(10).quantile(0.5), Series), Series)
check(assert_type(S.expanding(10).rank("average"), Series), Series)
check(assert_type(S.expanding(10).rank("min"), Series), Series)
check(assert_type(S.expanding(10).rank("max"), Series), Series)
def test_expanding_apply_series() -> None:
check(assert_type(S.expanding(10).apply(np.mean), Series), Series)
def _mean(df: Series) -> float:
return df.mean()
check(assert_type(S.expanding(10).apply(_mean), Series), Series)
def _mean2(df: Series) -> np.ndarray:
return np.mean(df, axis=0)
check(assert_type(S.expanding(10).apply(_mean2, raw=True), Series), Series)
def test_expanding_aggregate_series() -> None:
check(assert_type(S.expanding(10).aggregate(np.mean), Series), Series)
check(
assert_type(S.expanding(10).aggregate(["mean", np.mean]), DataFrame), DataFrame
)
check(
assert_type(
S.expanding(10).aggregate({"col1": "mean", "col2": np.mean}), DataFrame
),
DataFrame,
)
check(assert_type(S.expanding(10).agg("sum"), Series), Series)
def test_ewm_basic_math() -> None:
check(assert_type(DF.ewm(span=10).sum(), DataFrame), DataFrame)
check(assert_type(DF.ewm(span=10).mean(), DataFrame), DataFrame)
check(assert_type(DF.ewm(span=10).var(), DataFrame), DataFrame)
check(assert_type(DF.ewm(span=10).std(), DataFrame), DataFrame)
check(assert_type(DF.ewm(span=10).corr(), DataFrame), DataFrame)
check(assert_type(DF.ewm(span=10).cov(), DataFrame), DataFrame)
def test_ewm_aggregate() -> None:
check(assert_type(DF.ewm(span=10).aggregate(np.mean), DataFrame), DataFrame)
check(
assert_type(DF.ewm(span=10).aggregate(["mean", np.mean]), DataFrame), DataFrame
)
check(
assert_type(
DF.ewm(span=10).aggregate({"col1": "mean", "col2": np.mean}), DataFrame
),
DataFrame,
)
check(assert_type(DF.ewm(span=10).agg("sum"), DataFrame), DataFrame)
def test_ewm_basic_math_series() -> None:
check(assert_type(S.ewm(span=10).sum(), Series), Series)
check(assert_type(S.ewm(span=10).mean(), Series), Series)
check(assert_type(S.ewm(span=10).var(), Series), Series)
check(assert_type(S.ewm(span=10).std(), Series), Series)
check(assert_type(S.ewm(span=10).corr(), Series), Series)
check(assert_type(S.ewm(span=10).cov(), Series), Series)
def test_ewm_aggregate_series() -> None:
check(assert_type(S.ewm(span=10).aggregate(np.mean), Series), Series)
check(
assert_type(S.ewm(span=10).aggregate(["mean", np.mean]), DataFrame), DataFrame
)
check(
assert_type(
S.ewm(span=10).aggregate({"col1": "mean", "col2": np.mean}), DataFrame
),
DataFrame,
)
check(assert_type(S.ewm(span=10).agg("sum"), Series), Series)
def test_rolling_step_method() -> None:
check(
assert_type(DF.rolling(10, step=5, method="single"), "Rolling[DataFrame]"),
Rolling,
)
check(assert_type(DF.rolling(10, method="table"), "Rolling[DataFrame]"), Rolling)
def test_rolling_window() -> None:
df_time = pd.DataFrame(
{"B": [0, 1, 2, np.nan, 4]},
index=[
pd.Timestamp("20130101 09:00:00"),
pd.Timestamp("20130101 09:00:02"),
pd.Timestamp("20130101 09:00:03"),
pd.Timestamp("20130101 09:00:05"),
pd.Timestamp("20130101 09:00:06"),
],
)
indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=2)
check(
assert_type(df_time.rolling(window=indexer, min_periods=1).sum(), DataFrame),
DataFrame,
)
s = df_time.iloc[:, 0]
check(
assert_type(s.rolling(window=indexer, min_periods=1).sum(), Series),
Series,
)