BUG #458 stoch and stochf

pandas_ta/momentum/stoch.py

@@ -40,7 +40,7 @@ def stoch(high, low, close, k=None, d=None, smooth_k=None, mamode=None, talib=No
     Returns:
         pd.DataFrame: %K, %D columns.
     """
-    # Validate arguments
+    # Validate
     k = k if k and k > 0 else 14
     d = d if d and d > 0 else 3
     smooth_k = smooth_k if smooth_k and smooth_k > 0 else 3
@@ -54,7 +54,7 @@ def stoch(high, low, close, k=None, d=None, smooth_k=None, mamode=None, talib=No
 
     if high is None or low is None or close is None: return
 
-    # Calculate Result
+    # Calculate
     if Imports["talib"] and mode_tal:
         from talib import STOCH
         stoch_ = STOCH(high, low, close, k, d, tal_ma(mamode), d, tal_ma(mamode))
@@ -74,7 +74,7 @@ def stoch(high, low, close, k=None, d=None, smooth_k=None, mamode=None, talib=No
         stoch_k = stoch_k.shift(offset)
         stoch_d = stoch_d.shift(offset)
 
-    # Handle fills
+    # Fill
     if "fillna" in kwargs:
         stoch_k.fillna(kwargs["fillna"], inplace=True)
         stoch_d.fillna(kwargs["fillna"], inplace=True)
@@ -82,14 +82,14 @@ def stoch(high, low, close, k=None, d=None, smooth_k=None, mamode=None, talib=No
         stoch_k.fillna(method=kwargs["fill_method"], inplace=True)
         stoch_d.fillna(method=kwargs["fill_method"], inplace=True)
 
-    # Name and Categorize it
+    # Name and Category
     _name = "STOCH"
     _props = f"_{k}_{d}_{smooth_k}"
     stoch_k.name = f"{_name}k{_props}"
     stoch_d.name = f"{_name}d{_props}"
     stoch_k.category = stoch_d.category = "momentum"
 
-    # Prepare DataFrame to return
+    # Return DataFrame
     data = {stoch_k.name: stoch_k, stoch_d.name: stoch_d}
     df = DataFrame(data, index=close.index)
     df.name = f"{_name}{_props}"

pandas_ta/momentum/stochf.py

@@ -34,7 +34,7 @@ def stochf(high, low, close, k=None, d=None, mamode=None, talib=None, offset=Non
     Returns:
         pd.DataFrame: Fast %K, %D columns.
     """
-    # Validate arguments
+    # Validate
     k = k if k and k > 0 else 14
     d = d if d and d > 0 else 3
     _length = max(k, d)
@@ -47,7 +47,7 @@ def stochf(high, low, close, k=None, d=None, mamode=None, talib=None, offset=Non
 
     if high is None or low is None or close is None: return
 
-    # Calculate Result
+    # Calculate
     if Imports["talib"] and mode_tal:
         from talib import STOCHF
         stochf_ = STOCHF(high, low, close, k, d, tal_ma(mamode))
@@ -65,7 +65,7 @@ def stochf(high, low, close, k=None, d=None, mamode=None, talib=None, offset=Non
         stochf_k = stochf_k.shift(offset)
         stochf_d = stochf_d.shift(offset)
 
-    # Handle fills
+    # Fill
     if "fillna" in kwargs:
         stochf_k.fillna(kwargs["fillna"], inplace=True)
         stochf_d.fillna(kwargs["fillna"], inplace=True)
@@ -73,14 +73,14 @@ def stochf(high, low, close, k=None, d=None, mamode=None, talib=None, offset=Non
         stochf_k.fillna(method=kwargs["fill_method"], inplace=True)
         stochf_d.fillna(method=kwargs["fill_method"], inplace=True)
 
-    # Name and Categorize it
+    # Name and Category
     _name = "STOCHF"
     _props = f"_{k}_{d}"
     stochf_k.name = f"{_name}k{_props}"
     stochf_d.name = f"{_name}d{_props}"
     stochf_k.category = stochf_d.category = "momentum"
 
-    # Prepare DataFrame to return
+    # Return DataFrame
     data = {stochf_k.name: stochf_k, stochf_d.name: stochf_d}
     df = DataFrame(data, index=close.index)
     df.name = f"{_name}{_props}"

pandas_ta/momentum/stochrsi.py

@@ -36,7 +36,7 @@ def stochrsi(close, length=None, rsi_length=None, k=None, d=None, mamode=None, o
     Returns:
         pd.DataFrame: RSI %K, RSI %D columns.
     """
-    # Validate arguments
+    # Validate
     length = length if length and length > 0 else 14
     rsi_length = rsi_length if rsi_length and rsi_length > 0 else 14
     k = k if k and k > 0 else 3
@@ -47,7 +47,7 @@ def stochrsi(close, length=None, rsi_length=None, k=None, d=None, mamode=None, o
 
     if close is None: return
 
-    # Calculate Result
+    # Calculate
     rsi_ = rsi(close, length=rsi_length)
     lowest_rsi = rsi_.rolling(length).min()
     highest_rsi = rsi_.rolling(length).max()
@@ -63,7 +63,7 @@ def stochrsi(close, length=None, rsi_length=None, k=None, d=None, mamode=None, o
         stochrsi_k = stochrsi_k.shift(offset)
         stochrsi_d = stochrsi_d.shift(offset)
 
-    # Handle fills
+    # Fill
     if "fillna" in kwargs:
         stochrsi_k.fillna(kwargs["fillna"], inplace=True)
         stochrsi_d.fillna(kwargs["fillna"], inplace=True)
@@ -71,14 +71,14 @@ def stochrsi(close, length=None, rsi_length=None, k=None, d=None, mamode=None, o
         stochrsi_k.fillna(method=kwargs["fill_method"], inplace=True)
         stochrsi_d.fillna(method=kwargs["fill_method"], inplace=True)
 
-    # Name and Categorize it
+    # Name and Categorize
     _name = "STOCHRSI"
     _props = f"_{length}_{rsi_length}_{k}_{d}"
     stochrsi_k.name = f"{_name}k{_props}"
     stochrsi_d.name = f"{_name}d{_props}"
     stochrsi_k.category = stochrsi_d.category = "momentum"
 
-    # Prepare DataFrame to return
+    # Return DataFrame
     data = {stochrsi_k.name: stochrsi_k, stochrsi_d.name: stochrsi_d}
     df = DataFrame(data)
     df.name = f"{_name}{_props}"

setup.py

@@ -19,7 +19,7 @@ setup(
         "pandas_ta.volatility",
         "pandas_ta.volume"
     ],
-    version=".".join(("0", "3", "42b")),
+    version=".".join(("0", "3", "43b")),
     description=long_description,
     long_description=long_description,
     author="Kevin Johnson",