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finance/材料准备/ta-lib.ipynb

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"source": [
"import pandas as pd\n",
"\n",
"# source_df = \\\n",
"# pd.read_csv(\"C:\\\\Users\\\\lanyuanxiaoyao\\\\SynologyDrive\\\\data\\\\Tushare\\\\日线行情 1990-2024\\\\分组行情\\\\000001.SZ.csv\") \\\n",
"source_df = pd.read_csv(\"/Users/lanyuanxiaoyao/SynologyDrive/data/Tushare/日线行情 1990-2024/分组行情/600519.SH.csv\") \\\n",
" [[\"trade_date\", \"vol\", \"open_qfq\", \"close_qfq\", \"high_qfq\", \"low_qfq\", \"macd\", \"macd_dif\", \"macd_dea\"]]\n",
"df = pd.DataFrame()\n",
"df[[\"date\", \"volume\", \"open\", \"close\", \"high\", \"low\", \"macd\", \"macd_dif\", \"macd_dea\"]] = \\\n",
" source_df[[\"trade_date\", \"vol\", \"open_qfq\", \"close_qfq\", \"high_qfq\", \"low_qfq\", \"macd\", \"macd_dif\", \"macd_dea\"]]\n",
"df[\"datetime\"] = pd.to_datetime(df[\"date\"], format=\"%Y%m%d\")\n",
"df[\"datetime_text\"] = df[\"datetime\"].apply(lambda x: x.strftime(\"%Y%m%d\"))\n",
"df.sort_values(by='datetime', inplace=True)\n",
"df"
],
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" date volume open close high low \\\n",
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"... ... ... ... ... ... ... \n",
"2182 20241225 17123.39 1538.80000 1530.00000 1538.80000 1526.10000 \n",
"2183 20241226 18286.51 1534.00000 1527.79000 1538.78000 1523.00000 \n",
"2184 20241227 20759.32 1528.90000 1528.97000 1536.00000 1519.50000 \n",
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"2186 20241231 39354.45 1525.40000 1524.00000 1545.00000 1522.01000 \n",
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"2189 0.025 0.018 0.006 2001-08-29 20010829 \n",
"2190 0.037 0.029 0.010 2001-08-30 20010830 \n",
"2191 0.042 0.036 0.016 2001-08-31 20010831 \n",
"... ... ... ... ... ... \n",
"2182 5.430 5.063 2.348 2024-12-25 20241225 \n",
"2183 4.192 4.968 2.872 2024-12-26 20241226 \n",
"2184 3.295 4.931 3.283 2024-12-27 20241227 \n",
"2185 1.993 4.529 3.533 2024-12-30 20241230 \n",
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" <th>volume</th>\n",
" <th>open</th>\n",
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"cell_type": "code",
"source": [
"import talib\n",
"\n",
"dif, dea, hist = talib.MACD(df[\"close\"], fastperiod=12, slowperiod=26, signalperiod=9)\n",
"\n",
"# 将结果添加到数据框\n",
"df['DIF'] = dif\n",
"df['DEA'] = dea\n",
"df['MACD'] = hist\n",
"\n",
"#根据close列计算macd值\n",
"talib.SMA(df[\"close\"], timeperiod=26, step=10)\n",
"\n",
"df"
],
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" date volume open close high low \\\n",
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"2188 20010828 129647.79 4.29568 4.52525 4.54244 4.24902 \n",
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"2190 20010830 48013.06 4.45405 4.55472 4.60505 4.41967 \n",
"2191 20010831 23231.48 4.56086 4.54367 4.61856 4.51789 \n",
"... ... ... ... ... ... ... \n",
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"2186 20241231 39354.45 1525.40000 1524.00000 1545.00000 1522.01000 \n",
"\n",
" macd macd_dif macd_dea datetime datetime_text DIF DEA \\\n",
"2187 0.000 0.000 0.000 2001-08-27 20010827 NaN NaN \n",
"2188 0.021 0.013 0.003 2001-08-28 20010828 NaN NaN \n",
"2189 0.025 0.018 0.006 2001-08-29 20010829 NaN NaN \n",
"2190 0.037 0.029 0.010 2001-08-30 20010830 NaN NaN \n",
"2191 0.042 0.036 0.016 2001-08-31 20010831 NaN NaN \n",
"... ... ... ... ... ... ... ... \n",
"2182 5.430 5.063 2.348 2024-12-25 20241225 5.062711 2.347629 \n",
"2183 4.192 4.968 2.872 2024-12-26 20241226 4.967756 2.871654 \n",
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"2186 0.880 4.083 3.643 2024-12-31 20241231 4.082931 3.642682 \n",
"\n",
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"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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