ENH added indicator Weighted Closing Price (wcp)

README.md

@@ -23,6 +23,7 @@ All the indicators return a named Series or a DataFrame in uppercase underscore
     - __KDJ__ (kdj)
     - __Parabolic Stop and Reverse__ (psar)
     - __Psycholigical Line__ (psl)
+    - __Weighted Closing Price__ (wcp)
 * User Added Indicators:
     - __Aberration__ (aberration)
     - __BRAR__ (brar)
@@ -148,7 +149,7 @@ df.ta.adjusted = None
 |:--------:|
 | ![Example MACD](/images/SPY_MACD.png) |
 
-## _Overlap_ (24)
+## _Overlap_ (25)
 
 * _Double Exponential Moving Average_: **dema**
 * _Exponential Moving Average_: **ema**
@@ -174,6 +175,7 @@ df.ta.adjusted = None
 * _Triangular Moving Average_: **trima**
 * _Volume Weighted Average Price_: **vwap** 
 * _Volume Weighted Moving Average_: **vwma**
+* _Weighted Closing Price_: **wcp**
 * _Weighted Moving Average_: **wma**
 * _Zero Lag Moving Average_: **zlma**
 

pandas_ta/__init__.py

@@ -68,6 +68,7 @@ from .overlap.tema import tema
 from .overlap.trima import trima
 from .overlap.vwap import vwap
 from .overlap.vwma import vwma
+from .overlap.wcp import wcp
 from .overlap.wma import wma
 from .overlap.zlma import zlma
 

pandas_ta/core.py

@@ -627,6 +627,15 @@ class AnalysisIndicators(BasePandasObject):
         self._append(result, **kwargs)
         return result
 
+    def wcp(self, high=None, low=None, close=None, offset=None, **kwargs):
+        high = self._get_column(high, 'high')
+        low = self._get_column(low, 'low')
+        close = self._get_column(close, 'close')
+        from .overlap.wcp import wcp
+        result = wcp(high=high, low=low, close=close, offset=offset, **kwargs)
+        self._append(result, **kwargs)
+        return result
+
     def wma(self, close=None, length=None, offset=None, **kwargs):
         close = self._get_column(close, 'close')
         from .overlap.wma import wma

pandas_ta/overlap/wcp.py

@@ -0,0 +1,23 @@
+# -*- coding: utf-8 -*-
+from ..utils import get_offset, verify_series
+
+def wcp(high, low, close, offset=None, **kwargs):
+    """Indicator: WCP"""
+    # Validate Arguments
+    high = verify_series(high)
+    low = verify_series(low)
+    close = verify_series(close)
+    offset = get_offset(offset)
+
+    # Calculate Result
+    wcp = (high + low + 2 * close) / 4
+
+    # Offset
+    if offset != 0:
+        wcp = wcp.shift(offset)
+
+    # Name & Category
+    wcp.name = "WCP"
+    wcp.category = 'overlap'
+
+    return wcp

setup.py

@@ -6,7 +6,7 @@ long_description = "An easy to use Python 3 Pandas Extension with 95+ Technical
 setup(
     name ="pandas_ta",
     packages =['pandas_ta', 'pandas_ta.momentum', 'pandas_ta.overlap', 'pandas_ta.performance', 'pandas_ta.statistics', 'pandas_ta.trend', 'pandas_ta.volatility', 'pandas_ta.volume'],
-    version ="0.1.42b",
+    version ="0.1.43b",
     description =long_description,
     long_description =long_description,
     author ="Kevin Johnson",

tests/test_indicator_overlap.py

@@ -298,6 +298,21 @@ class TestOverlap(TestCase):
         self.assertIsInstance(result, Series)
         self.assertEqual(result.name, 'VWMA_10')
 
+    def test_wcp(self):
+        result = pandas_ta.wcp(self.high, self.low, self.close)
+        self.assertIsInstance(result, Series)
+        self.assertEqual(result.name, 'WCP')
+
+        try:
+            expected = tal.WCLPRICE(self.high, self.low, self.close)
+            pdt.assert_series_equal(result, expected, check_names=False)
+        except AssertionError as ae:
+            try:
+                corr = pandas_ta.utils.df_error_analysis(result, expected, col=CORRELATION)
+                self.assertGreater(corr, CORRELATION_THRESHOLD)
+            except Exception as ex:
+                error_analysis(result, CORRELATION, ex)
+
     def test_wma(self):
         result = pandas_ta.wma(self.close)
         self.assertIsInstance(result, Series)

tests/test_indicator_overlap_ext.py

@@ -133,6 +133,11 @@ class TestOverlapExtension(TestCase):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], 'VWMA_10')
 
+    def test_wcp_ext(self):
+        self.data.ta.wcp(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(self.data.columns[-1], 'WCP')
+
     def test_wma_ext(self):
         self.data.ta.wma(append=True)
         self.assertIsInstance(self.data, DataFrame)