both performance and statistics indicators fully typed

pandas_ta/performance/drawdown.py

@@ -1,11 +1,11 @@
 # -*- coding: utf-8 -*-
 from numpy import log as nplog
 from numpy import seterr
-from pandas import DataFrame
+from pandas import DataFrame, Series
 from pandas_ta.utils import get_offset, verify_series
 
 
-def drawdown(close, offset=None, **kwargs) -> DataFrame:
+def drawdown(close: Series, offset: int = None, **kwargs) -> DataFrame:
     """Drawdown (DD)
 
     Drawdown is a peak-to-trough decline during a specific period for an investment,

pandas_ta/performance/log_return.py

@@ -1,9 +1,10 @@
 # -*- coding: utf-8 -*-
 from numpy import log as nplog
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def log_return(close, length=None, cumulative=None, offset=None, **kwargs):
+def log_return(close: Series, length: int = None, cumulative: bool = None, offset: int = None, **kwargs) -> Series:
     """Log Return
 
     Calculates the logarithmic return of a Series.

pandas_ta/performance/percent_return.py

@@ -1,8 +1,10 @@
 # -*- coding: utf-8 -*-
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def percent_return(close, length=None, cumulative=None, offset=None, **kwargs):
+def percent_return(close: Series, length: int = None, cumulative: bool = None, offset: int = None,
+                   **kwargs) -> Series:
     """Percent Return
 
     Calculates the percent return of a Series.

pandas_ta/statistics/entropy.py

@@ -1,9 +1,10 @@
 # -*- coding: utf-8 -*-
 from numpy import log as npLog
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def entropy(close, length=None, base=None, offset=None, **kwargs):
+def entropy(close: Series, length: int = None, base: float = None, offset: int = None, **kwargs) -> Series:
     """Entropy (ENTP)
 
     Introduced by Claude Shannon in 1948, entropy measures the unpredictability

pandas_ta/statistics/kurtosis.py

@@ -1,8 +1,9 @@
 # -*- coding: utf-8 -*-
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def kurtosis(close, length=None, offset=None, **kwargs):
+def kurtosis(close: Series, length: int = None, offset: int = None, **kwargs) -> Series:
     """Rolling Kurtosis
 
     Calculates the Kurtosis over a rolling period.

pandas_ta/statistics/mad.py

@@ -1,9 +1,10 @@
 # -*- coding: utf-8 -*-
 from numpy import fabs as npfabs
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def mad(close, length=None, offset=None, **kwargs):
+def mad(close: Series, length: int = None, offset: int = None, **kwargs) -> Series:
     """Rolling Mean Absolute Deviation
 
     Calculates the Mean Absolute Deviation over a rolling period.

pandas_ta/statistics/median.py

@@ -1,8 +1,9 @@
 # -*- coding: utf-8 -*-
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def median(close, length=None, offset=None, **kwargs):
+def median(close: Series, length: int = None, offset: int = None, **kwargs) -> Series:
     """Rolling Median
 
     Calculates the Median over a rolling period. Sibling of a Simple Moving Average.

pandas_ta/statistics/quantile.py

@@ -1,8 +1,9 @@
 # -*- coding: utf-8 -*-
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def quantile(close, length=None, q=None, offset=None, **kwargs):
+def quantile(close: Series, length: int = None, q: float = None, offset: int = None, **kwargs) -> Series:
     """Rolling Quantile
 
     Calculates the Quantile over a rolling period.

pandas_ta/statistics/skew.py

@@ -1,8 +1,9 @@
 # -*- coding: utf-8 -*-
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def skew(close, length=None, offset=None, **kwargs):
+def skew(close: Series, length: int = None, offset: int = None, **kwargs) -> Series:
     """Rolling Skew
 
     Calculates the Skew over a rolling period.

pandas_ta/statistics/stdev.py

@@ -3,9 +3,11 @@ from numpy import sqrt as npsqrt
 from .variance import variance
 from pandas_ta import Imports
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def stdev(close, length=None, ddof=None, talib=None, offset=None, **kwargs):
+def stdev(close: Series, length: int = None, ddof: int = None, talib: bool = None, offset: int = None,
+          **kwargs) -> Series:
     """Rolling Standard Deviation
 
     Calculates the Standard Deviation over a rolling period.

pandas_ta/statistics/tos_stdevall.py

@@ -7,7 +7,9 @@ from pandas import DataFrame, DatetimeIndex, Series
 from .stdev import stdev as stdev
 from pandas_ta.utils import get_offset, verify_series
 
-def tos_stdevall(close, length=None, stds=None, ddof=None, offset=None, **kwargs):
+
+def tos_stdevall(close: Series, length: int = None, stds: list = None, ddof: int = None, offset: int = None,
+                 **kwargs) -> DataFrame:
     """TD Ameritrade's Think or Swim Standard Deviation All (TOS_STDEV)
 
     A port of TD Ameritrade's Think or Swim Standard Deviation All indicator which

pandas_ta/statistics/variance.py

@@ -1,9 +1,11 @@
 # -*- coding: utf-8 -*-
 from pandas_ta import Imports
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def variance(close, length=None, ddof=None, talib=None, offset=None, **kwargs):
+def variance(close: Series, length: int = None, ddof: int = None, talib: bool = None, offset: int = None,
+             **kwargs) -> Series:
     """Rolling Variance
 
     Calculates the Variance over a rolling period.

pandas_ta/statistics/zscore.py

@@ -2,9 +2,10 @@
 from pandas_ta.overlap import sma
 from .stdev import stdev
 from pandas_ta.utils import get_offset, verify_series
+from pandas import Series
 
 
-def zscore(close, length=None, std=None, offset=None, **kwargs):
+def zscore(close: Series, length: int = None, std: float = None, offset: int = None, **kwargs) -> Series:
     """Rolling Z Score
 
     Calculates the Z Score over a rolling period.