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https://github.com/wassname/pandas-ta.git
synced 2026-09-10 12:23:49 +08:00
ENH strategy col_names support ENH classic linreg util TST strategies update
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@@ -45,7 +45,7 @@
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"Numpy v1.18.3\n",
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"Pandas v1.1.0\n",
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"mplfinance v0.12.6a3\n",
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"Pandas TA v0.2.08b\n"
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"Pandas TA v0.2.12b\n"
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]
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}
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],
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@@ -91,7 +91,7 @@
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" # All Data: 0, Last Four Years: 0.25, Last Two Years: 0.5, This Year: 1, Last Half Year: 2, Last Quarter: 4\n",
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" yearly_divisor = {\"all\": 0, \"10y\": 0.1, \"5y\": 0.2, \"4y\": 0.25, \"3y\": 1./3, \"2y\": 0.5, \"1y\": 1, \"6mo\": 2, \"3mo\": 4}\n",
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" yd = yearly_divisor[tf] if tf in yearly_divisor.keys() else 0\n",
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" return int(ta.TRADING_DAYS_PER_YEAR / yd) if yd > 0 else df.shape[0]"
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" return int(ta.RATE[\"TRADING_DAYS_PER_YEAR\"] / yd) if yd > 0 else df.shape[0]"
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]
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},
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{
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@@ -112,13 +112,13 @@
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"text": [
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"[!] Loading All: SPY, QQQ, AAPL, TSLA\n",
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"[i] Loaded['D']: SPY_D.csv\n",
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"[i] Runtime: 812.7898 ms (0.8128 s)\n",
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"[i] Runtime: 1812.7836 ms (1.8128 s)\n",
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"[i] Loaded['D']: QQQ_D.csv\n",
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"[i] Runtime: 818.7984 ms (0.8188 s)\n",
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"[i] Runtime: 1747.0058 ms (1.7470 s)\n",
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"[i] Loaded['D']: AAPL_D.csv\n",
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"[i] Runtime: 1227.1223 ms (1.2271 s)\n",
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"[i] Runtime: 1105.7967 ms (1.1058 s)\n",
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"[i] Loaded['D']: TSLA_D.csv\n",
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"[i] Runtime: 1858.9133 ms (1.8589 s)\n"
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"[i] Runtime: 906.7782 ms (0.9068 s)\n"
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]
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}
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],
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@@ -353,7 +353,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.axes._subplots.AxesSubplot at 0x11196a5b0>"
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"<matplotlib.axes._subplots.AxesSubplot at 0x11a0cc880>"
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]
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},
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"execution_count": 9,
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@@ -396,7 +396,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.axes._subplots.AxesSubplot at 0x11d8d3fd0>"
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"<matplotlib.axes._subplots.AxesSubplot at 0x11a779940>"
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]
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},
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"execution_count": 10,
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@@ -441,7 +441,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.axes._subplots.AxesSubplot at 0x11d9e70d0>"
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"<matplotlib.axes._subplots.AxesSubplot at 0x10e090670>"
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]
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},
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"execution_count": 11,
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