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https://github.com/wassname/pandas-ta.git
synced 2026-09-10 12:23:49 +08:00
BUG cci now correlated with talib, fixed default value
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@@ -45,6 +45,7 @@ All the indicators return a named Series or a DataFrame in uppercase underscore
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- __Aroon & Aroon Oscillator__ (aroon)
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* Fixed indicator and included oscillator in returned dataframe
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- __Bollinger Bands__ (bbands)
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- __Commodity Channel Index__ (cci)
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- __Chande Momentum Oscillator__ (cmo)
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## What is a Pandas DataFrame Extension?
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@@ -10,9 +10,8 @@ def cci(high, low, close, length=None, c=None, offset=None, **kwargs):
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high = verify_series(high)
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low = verify_series(low)
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close = verify_series(close)
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length = int(length) if length and length > 0 else 20
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length = int(length) if length and length > 0 else 14
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c = float(c) if c and c > 0 else 0.015
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min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
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offset = get_offset(offset)
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# Calculate Result
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@@ -52,7 +51,7 @@ Sources:
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Calculation:
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Default Inputs:
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length=20, c=0.015
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length=14, c=0.015
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SMA = Simple Moving Average
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MAD = Mean Absolute Deviation
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tp = typical_price = hlc3 = (high + low + close) / 3
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@@ -64,7 +63,7 @@ Args:
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high (pd.Series): Series of 'high's
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low (pd.Series): Series of 'low's
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close (pd.Series): Series of 'close's
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length (int): It's period. Default: 20
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length (int): It's period. Default: 14
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c (float): Scaling Constant. Default: 0.015
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offset (int): How many periods to offset the result. Default: 0
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@@ -6,7 +6,7 @@ long_description = "An easy to use Python 3 Pandas Extension with 100+ Technical
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setup(
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name ="pandas_ta",
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packages =['pandas_ta', 'pandas_ta.momentum', 'pandas_ta.overlap', 'pandas_ta.performance', 'pandas_ta.statistics', 'pandas_ta.trend', 'pandas_ta.volatility', 'pandas_ta.volume'],
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version ="0.1.52b",
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version ="0.1.53b",
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description =long_description,
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long_description =long_description,
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author ="Kevin Johnson",
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@@ -107,7 +107,7 @@ class TestMomentum(TestCase):
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def test_cci(self):
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result = pandas_ta.cci(self.high, self.low, self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'CCI_20_0.015')
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self.assertEqual(result.name, 'CCI_14_0.015')
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try:
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expected = tal.CCI(self.high, self.low, self.close)
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@@ -51,7 +51,7 @@ class TestMomentumExtension(TestCase):
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def test_cci_ext(self):
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self.data.ta.cci(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], 'CCI_20_0.015')
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self.assertEqual(self.data.columns[-1], 'CCI_14_0.015')
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def test_cg_ext(self):
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self.data.ta.cg(append=True)
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