Linting.

mathematical/outliers.py

@@ -45,7 +45,7 @@
 
 
 def mad_outliers(
-		dataset: Sequence[float],
+		dataset: Sequence,
 		strip_zero: bool = True,
 		threshold: int = 3,
 		) -> Tuple[List[float], List[float]]:
@@ -98,7 +98,7 @@ def mad_outliers(
 
 
 def two_stdev(
-		dataset: Sequence[float],
+		dataset: Sequence,
 		strip_zero: bool = True,
 		) -> Tuple[List[float], List[float]]:
 	"""
@@ -114,7 +114,7 @@ def two_stdev(
 
 
 def stdev_outlier(
-		dataset: Sequence[float],
+		dataset: Sequence,
 		strip_zero: bool = True,
 		rng: int = 2,
 		) -> Tuple[List[float], List[float]]:
@@ -152,7 +152,7 @@ def stdev_outlier(
 
 
 def quartile_outliers(
-		dataset: Sequence[float],
+		dataset: Sequence,
 		strip_zero: bool = True,
 		) -> Tuple[List[float], List[float]]:
 	"""
@@ -195,7 +195,7 @@ def quartile_outliers(
 
 
 def spss_outliers(
-		dataset: Sequence[float],
+		dataset: Sequence,
 		strip_zero: bool = True,
 		mode: str = "all",
 		) -> Tuple[List[float], List[float], List[float]]:

tests/test_data_frames.py

@@ -17,17 +17,21 @@
 
 # this package
 from mathematical.data_frames import (
-	df_count,
-	df_data_points,
-	df_delta,
-	df_delta_relative,
-	df_log,
-	df_log_stdev,
-	df_mean,
-	df_median,
-	df_outliers, df_percentage,
-	df_stdev, MAD, QUARTILES, STDEV2,
-	)
+		MAD,
+		QUARTILES,
+		STDEV2,
+		df_count,
+		df_data_points,
+		df_delta,
+		df_delta_relative,
+		df_log,
+		df_log_stdev,
+		df_mean,
+		df_median,
+		df_outliers,
+		df_percentage,
+		df_stdev
+		)
 
 
 @pytest.fixture()
@@ -140,4 +144,3 @@ def test_df_outliers(base_df):
 
 	df["STDEV2 Outliers"] = df.apply(df_outliers, args=[samples, STDEV2], axis=1)
 	assert list(df["STDEV2 Outliers"][0]) == [sys.maxsize]
-

tests/test_outliers.py

@@ -2,7 +2,7 @@
 from typing import Iterable
 
 # 3rd party
-import numpy
+import numpy  # type: ignore
 import pytest
 from coincidence.regressions import AdvancedDataRegressionFixture