{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import ideadata\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datetimeopen_pxhigh_pxlow_pxclose_pxvolumevaluevwaptickerexchangecd
02023-01-0309:3013.20013.23013.16013.16035467004.681679e+0713.200000001XSHE
12023-01-0309:3113.18013.18013.06013.16037255374.894731e+0713.138000001XSHE
22023-01-0309:3213.18013.18013.11013.14011225001.473833e+0713.130000001XSHE
32023-01-0309:3313.14013.17013.11013.17012846941.688369e+0713.142000001XSHE
42023-01-0309:3413.17013.20013.16013.20012184571.605823e+0713.179000001XSHE
....................................
90010682023-01-0314:561329.4971329.5341329.2991329.35590230392.350546e+0826.050988201XSHE
90010692023-01-0314:571329.4641329.6891329.3981329.64092923502.257246e+0824.291988201XSHE
90010702023-01-0314:581329.5711329.7551329.4441329.66915652355.986035e+0738.244988201XSHE
90010712023-01-0314:591329.6291329.6611328.9821328.9823672002.945644e+0780.219988201XSHE
90010722023-01-0315:001328.9561329.4111328.6761328.834213008286.605609e+0831.011988201XSHE
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" ], "text/plain": [ " date time open_px high_px low_px close_px volume \\\n", "0 2023-01-03 09:30 13.200 13.230 13.160 13.160 3546700 \n", "1 2023-01-03 09:31 13.180 13.180 13.060 13.160 3725537 \n", "2 2023-01-03 09:32 13.180 13.180 13.110 13.140 1122500 \n", "3 2023-01-03 09:33 13.140 13.170 13.110 13.170 1284694 \n", "4 2023-01-03 09:34 13.170 13.200 13.160 13.200 1218457 \n", "... ... ... ... ... ... ... ... \n", "9001068 2023-01-03 14:56 1329.497 1329.534 1329.299 1329.355 9023039 \n", "9001069 2023-01-03 14:57 1329.464 1329.689 1329.398 1329.640 9292350 \n", "9001070 2023-01-03 14:58 1329.571 1329.755 1329.444 1329.669 1565235 \n", "9001071 2023-01-03 14:59 1329.629 1329.661 1328.982 1328.982 367200 \n", "9001072 2023-01-03 15:00 1328.956 1329.411 1328.676 1328.834 21300828 \n", "\n", " value vwap ticker exchangecd \n", "0 4.681679e+07 13.200 000001 XSHE \n", "1 4.894731e+07 13.138 000001 XSHE \n", "2 1.473833e+07 13.130 000001 XSHE \n", "3 1.688369e+07 13.142 000001 XSHE \n", "4 1.605823e+07 13.179 000001 XSHE \n", "... ... ... ... ... \n", "9001068 2.350546e+08 26.050 988201 XSHE \n", "9001069 2.257246e+08 24.291 988201 XSHE \n", "9001070 5.986035e+07 38.244 988201 XSHE \n", "9001071 2.945644e+07 80.219 988201 XSHE \n", "9001072 6.605609e+08 31.011 988201 XSHE \n", "\n", "[9001073 rows x 11 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ideadata.stock.stock_data.get_all_stk_bar(\"20230103\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "ename": "AttributeError", "evalue": "module 'ideadata.stock' has no attribute 'trade_calendar'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m cal \u001b[39m=\u001b[39m ideadata\u001b[39m.\u001b[39;49mstock\u001b[39m.\u001b[39;49mtrade_calendar\u001b[39m.\u001b[39mTradeCalendar(\n\u001b[1;32m 2\u001b[0m )\n", "\u001b[0;31mAttributeError\u001b[0m: module 'ideadata.stock' has no attribute 'trade_calendar'" ] } ], "source": [ "cal = ideadata.stock.trade_calendar.TradeCalendar()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from ideadata.stock import trade_calendar" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "cal = trade_calendar.TradeCalendar()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'20230104'" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cal.get_next_trade_day('20230103')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "tcal = cal.get_trade_cal('20210101', '20230104')" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'2021-01-01'" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "next(tcal.iterrows())[1]['date']" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "df1min = ideadata.stock.stock_data.get_idea_stk_1min_data('20230103')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datetimesec_idadj_open_pxadj_close_pxadj_high_pxadj_low_pxadj_volumeact_volumeamountadj_vwapc_2_clog_c_2_c
02023-01-0309:25000001_XSHE1726.8681191726.8681191726.8681191726.86811936372.2744703016859.039822538.801726.8681190.0030400.003035
12023-01-0309:30000001_XSHE1726.8681191721.6351851730.7928191721.6351856387.942651529841.06994248.201726.953797-0.003030-0.003035
22023-01-0309:31000001_XSHE1724.2516521721.6351851724.2516521708.55285144916.3365983725537.048947305.551718.7570720.0000000.000000
32023-01-0309:32000001_XSHE1724.2516521719.0187191724.2516521715.09401813533.2403981122500.014738329.001717.710485-0.001520-0.001521
42023-01-0309:33000001_XSHE1719.0187191722.9434191722.9434191715.09401815488.7062271284694.016883686.221719.2803650.0022830.002281
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11860392023-01-0314:58689009_XSHG30.69000030.69000030.69000030.6900000.0000000.00.0030.6900000.0000000.000000
11860402023-01-0314:59689009_XSHG30.69000030.69000030.69000030.6900000.0000000.00.0030.6900000.0000000.000000
11860412023-01-0315:00689009_XSHG30.62000030.62000030.62000030.62000028901.00000028901.0884948.0030.620000-0.002281-0.002283
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datetimesec_id
02023-01-0309:25000001_XSHE
12023-01-0309:30000001_XSHE
22023-01-0309:31000001_XSHE
32023-01-0309:32000001_XSHE
42023-01-0309:33000001_XSHE
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11860372023-01-0314:56689009_XSHG
11860382023-01-0314:57689009_XSHG
11860392023-01-0314:58689009_XSHG
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adj_open_pxadj_close_pxadj_high_pxadj_low_pxadj_volumeact_volumeamountadj_vwapc_2_clog_c_2_c
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" ], "text/plain": [ " adj_open_px adj_close_px adj_high_px adj_low_px adj_volume \\\n", "0 1726.868119 1726.868119 1726.868119 1726.868119 36372.274470 \n", "1 1726.868119 1721.635185 1730.792819 1721.635185 6387.942651 \n", "2 1724.251652 1721.635185 1724.251652 1708.552851 44916.336598 \n", "3 1724.251652 1719.018719 1724.251652 1715.094018 13533.240398 \n", "4 1719.018719 1722.943419 1722.943419 1715.094018 15488.706227 \n", "... ... ... ... ... ... \n", "1186037 30.670000 30.590000 30.700000 30.590000 25519.000000 \n", "1186038 30.590000 30.690000 30.690000 30.590000 8481.000000 \n", "1186039 30.690000 30.690000 30.690000 30.690000 0.000000 \n", "1186040 30.690000 30.690000 30.690000 30.690000 0.000000 \n", "1186041 30.620000 30.620000 30.620000 30.620000 28901.000000 \n", "\n", " act_volume amount adj_vwap c_2_c log_c_2_c \n", "0 3016859.0 39822538.80 1726.868119 0.003040 0.003035 \n", "1 529841.0 6994248.20 1726.953797 -0.003030 -0.003035 \n", "2 3725537.0 48947305.55 1718.757072 0.000000 0.000000 \n", "3 1122500.0 14738329.00 1717.710485 -0.001520 -0.001521 \n", "4 1284694.0 16883686.22 1719.280365 0.002283 0.002281 \n", "... ... ... ... ... ... \n", "1186037 25519.0 783215.00 30.691000 -0.002608 -0.002612 \n", "1186038 8481.0 259898.00 30.645000 0.003269 0.003264 \n", "1186039 0.0 0.00 30.690000 0.000000 0.000000 \n", "1186040 0.0 0.00 30.690000 0.000000 0.000000 \n", "1186041 28901.0 884948.00 30.620000 -0.002281 -0.002283 \n", "\n", "[1186042 rows x 10 columns]" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1min[keys]" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1726.86811906, 1726.86811906, 1724.25165221, ..., 106.37304084,\n", " 106.19979484, 106.19979484],\n", " [ 106.19979484, 106.19979484, 106.19979484, ..., 22.04639079,\n", " 22.04639079, 22.04639079],\n", " [ 22.04639079, 21.99928312, 21.95217544, ..., 36.14247169,\n", " 36.17006136, 36.14247169],\n", " ...,\n", " [ 108.4099343 , 108.4099343 , 108.64082869, ..., 13.35883321,\n", " 13.34874345, 13.34874345],\n", " [ 13.34874345, 13.3386537 , 13.32856395, ..., 38.316403 ,\n", " 38.316403 , 38.316403 ],\n", " [ 38.316403 , 38.316403 , 38.316403 , ..., 30.69 ,\n", " 30.69 , 30.62 ]])" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1min[keys].values.reshape(242, -1, 10)[..., 0]" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1726.86811906, 1726.86811906, 1724.25165221, ..., 1801.4374242 ,\n", " 1801.4374242 , 1801.4374242 ],\n", " [2860.02063639, 2860.02063639, 2844.21941741, ..., 2877.40197728,\n", " 2877.40197728, 2880.56222107],\n", " [ 66.08426594, 66.08426594, 65.81090806, ..., 67.92943158,\n", " 67.92943158, 67.92943158],\n", " ...,\n", " [ 37.9236826 , 37.9236826 , 37.75852775, ..., 38.95590041,\n", " 38.95590041, 38.96622259],\n", " [ 41.08 , 41.08 , 41.05 , ..., 41.53 ,\n", " 41.53 , 41.54 ],\n", " [ 30.52 , 30.52 , 30.52 , ..., 30.69 ,\n", " 30.69 , 30.62 ]])" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1min[keys].values.reshape(-1, 242, 10)[..., 0]" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 1726.868119\n", "1 1726.868119\n", "2 1724.251652\n", "3 1724.251652\n", "4 1719.018719\n", " ... \n", "237 1802.745658\n", "238 1801.437424\n", "239 1801.437424\n", "240 1801.437424\n", "241 1801.437424\n", "Name: adj_open_px, Length: 242, dtype: float64" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1min['adj_open_px'].iloc[0:242]" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1726.86811906, 1726.86811906, 1724.25165221, 1724.25165221,\n", " 1719.01871852, 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1776.58098915, 1777.88922258, 1776.58098915,\n", " 1775.27275573, 1775.27275573, 1771.34805546, 1767.42335519,\n", " 1770.03982204, 1766.11512177, 1767.42335519, 1768.73158861,\n", " 1768.73158861, 1768.73158861, 1763.49865492, 1760.88218807,\n", " 1764.80688834, 1764.80688834, 1766.11512177, 1764.80688834,\n", " 1764.80688834, 1766.11512177, 1768.73158861, 1768.73158861,\n", " 1767.42335519, 1766.11512177, 1764.80688834, 1764.80688834,\n", " 1764.80688834, 1766.11512177, 1764.80688834, 1766.11512177,\n", " 1766.11512177, 1768.73158861, 1767.42335519, 1770.03982204,\n", " 1767.42335519, 1768.73158861, 1766.11512177, 1767.42335519,\n", " 1766.11512177, 1764.80688834, 1766.11512177, 1764.80688834,\n", " 1767.42335519, 1770.03982204, 1770.03982204, 1772.65628888,\n", " 1771.34805546, 1773.96452231, 1775.27275573, 1775.27275573,\n", " 1775.27275573, 1773.96452231, 1772.65628888, 1773.96452231,\n", " 1776.58098915, 1777.88922258, 1776.58098915, 1775.27275573,\n", " 1773.96452231, 1771.34805546, 1768.73158861, 1768.73158861,\n", " 1771.34805546, 1771.34805546, 1770.03982204, 1770.03982204,\n", " 1771.34805546, 1772.65628888, 1776.58098915, 1777.88922258,\n", " 1776.58098915, 1777.88922258, 1779.197456 , 1777.88922258,\n", " 1779.197456 , 1777.88922258, 1777.88922258, 1777.88922258,\n", " 1779.197456 , 1777.88922258, 1777.88922258, 1776.58098915,\n", " 1777.88922258, 1776.58098915, 1777.88922258, 1783.12215627,\n", " 1783.12215627, 1783.12215627, 1785.73862312, 1787.04685654,\n", " 1789.66332339, 1788.35508997, 1787.04685654, 1787.04685654,\n", " 1788.35508997, 1790.97155681, 1792.27979024, 1792.27979024,\n", " 1792.27979024, 1790.97155681, 1789.66332339, 1792.27979024,\n", " 1792.27979024, 1793.58802366, 1790.97155681, 1792.27979024,\n", " 1792.27979024, 1792.27979024, 1792.27979024, 1790.97155681,\n", " 1790.97155681, 1793.58802366, 1794.89625708, 1793.58802366,\n", " 1792.27979024, 1793.58802366, 1793.58802366, 1794.89625708,\n", " 1796.20449051, 1796.20449051, 1796.20449051, 1797.51272393,\n", " 1798.82095735, 1798.82095735, 1798.82095735, 1798.82095735,\n", " 1798.82095735, 1800.12919078, 1801.4374242 , 1802.74565762,\n", " 1801.4374242 , 1798.82095735, 1800.12919078, 1800.12919078,\n", " 1801.4374242 , 1802.74565762, 1802.74565762, 1806.67035789,\n", " 1805.36212447, 1806.67035789, 1809.28682474, 1807.97859132,\n", " 1810.59505817, 1806.67035789, 1806.67035789, 1806.67035789,\n", " 1806.67035789, 1809.28682474, 1806.67035789, 1807.97859132,\n", " 1809.28682474, 1807.97859132, 1806.67035789, 1807.97859132,\n", " 1804.05389105, 1805.36212447, 1805.36212447, 1805.36212447,\n", " 1805.36212447, 1806.67035789, 1805.36212447, 1806.67035789,\n", " 1807.97859132, 1806.67035789, 1806.67035789, 1807.97859132,\n", " 1806.67035789, 1805.36212447, 1804.05389105, 1804.05389105,\n", " 1804.05389105, 1802.74565762, 1801.4374242 , 1801.4374242 ,\n", " 1801.4374242 , 1801.4374242 ])" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1min[keys].values.reshape(-1, 242, 10)[..., 0][0]" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "import yahooquery as yq\n", "aapl = yq.Ticker(\"AAPL\")" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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asOfDateperiodTypeEnterpriseValueEnterprisesValueEBITDARatioEnterprisesValueRevenueRatioForwardPeRatioMarketCapPbRatioPeRatioPegRatioPsRatio
symbol
AAPL2021-12-313M2.963725e+1266.40358723.91161331.64562.901645e+1245.99215331.6524063.79088.186344
AAPL2022-03-313M2.888888e+1286.06334929.69724329.06982.830003e+1239.34276128.9568823.37447.715197
AAPL2022-06-303M2.269030e+1285.33396327.35122321.55172.200560e+1232.64974422.2308942.37655.874047
AAPL2022-09-303M2.274841e+1280.24414725.23507821.83412.203381e+1237.91937922.8429752.47345.867952
AAPL2022-12-313M2.138707e+1254.08696518.25551621.27662.066942e+1240.62211821.2651392.53285.379313
AAPL2023-02-28TTM2.392068e+12NaNNaN24.93772.332313e+1241.11469125.0271652.44066.156367
AAPL2023-03-01TTMNaN18.6810266.172489NaNNaNNaNNaNNaNNaN
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" ], "text/plain": [ " asOfDate periodType EnterpriseValue EnterprisesValueEBITDARatio \\\n", "symbol \n", "AAPL 2021-12-31 3M 2.963725e+12 66.403587 \n", "AAPL 2022-03-31 3M 2.888888e+12 86.063349 \n", "AAPL 2022-06-30 3M 2.269030e+12 85.333963 \n", "AAPL 2022-09-30 3M 2.274841e+12 80.244147 \n", "AAPL 2022-12-31 3M 2.138707e+12 54.086965 \n", "AAPL 2023-02-28 TTM 2.392068e+12 NaN \n", "AAPL 2023-03-01 TTM NaN 18.681026 \n", "\n", " EnterprisesValueRevenueRatio ForwardPeRatio MarketCap PbRatio \\\n", "symbol \n", "AAPL 23.911613 31.6456 2.901645e+12 45.992153 \n", "AAPL 29.697243 29.0698 2.830003e+12 39.342761 \n", "AAPL 27.351223 21.5517 2.200560e+12 32.649744 \n", "AAPL 25.235078 21.8341 2.203381e+12 37.919379 \n", "AAPL 18.255516 21.2766 2.066942e+12 40.622118 \n", "AAPL NaN 24.9377 2.332313e+12 41.114691 \n", "AAPL 6.172489 NaN NaN NaN \n", "\n", " PeRatio PegRatio PsRatio \n", "symbol \n", "AAPL 31.652406 3.7908 8.186344 \n", "AAPL 28.956882 3.3744 7.715197 \n", "AAPL 22.230894 2.3765 5.874047 \n", "AAPL 22.842975 2.4734 5.867952 \n", "AAPL 21.265139 2.5328 5.379313 \n", "AAPL 25.027165 2.4406 6.156367 \n", "AAPL NaN NaN NaN " ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "aapl.valuation_measures" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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asOfDateOrdinarySharesNumber
symbol
AAPL2019-09-301.777294e+10
AAPL2020-09-301.697676e+10
AAPL2021-09-301.642679e+10
AAPL2022-09-301.594342e+10
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" ], "text/plain": [ " asOfDate OrdinarySharesNumber\n", "symbol \n", "AAPL 2019-09-30 1.777294e+10\n", "AAPL 2020-09-30 1.697676e+10\n", "AAPL 2021-09-30 1.642679e+10\n", "AAPL 2022-09-30 1.594342e+10" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "aapl.balance_sheet()[['asOfDate', 'OrdinarySharesNumber']]" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.4" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "1.6e10 * 150 / 1e12" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "aapl = yq.Ticker(\"AAPL\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import yahooquery as yq" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.frame.DataFrame" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(aapl.history(adj_ohlc=True))" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Utilities—Regulated Electric\n", "Utilities\n" ] } ], "source": [ "ticker_symbol = '0N9G.IL'\n", "# yq.Ticker(ticker_symbol).asset_profile\n", "print(yq.Ticker(ticker_symbol).asset_profile[ticker_symbol]['industry'])\n", "print(yq.Ticker(ticker_symbol).asset_profile[ticker_symbol]['sector'])" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import yahooquery as yq\n", "pdd = yq.Ticker(\"9999.HK\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'9999.HK': {'address1': 'NetEase Building',\n", " 'address2': 'No. 599 Wangshang Road Binjiang District',\n", " 'city': 'Hangzhou',\n", " 'zip': '310052',\n", " 'country': 'China',\n", " 'phone': '86 57 1898 53378',\n", " 'website': 'https://netease.gcs-web.com',\n", " 'industry': 'Electronic Gaming & Multimedia',\n", " 'sector': 'Communication Services',\n", " 'longBusinessSummary': \"NetEase, Inc. provides online services focusing on diverse content, community, communication, and commerce in the Peoples' Republic of China and internationally. The company operates in three segments: Online Game Services, Youdao, Cloud Music, and Innovative Businesses and Others. It develops and operates PC and mobile games, as well as offers games licensed from other game developers. The company's products and services include Youdao Dictionary, an online knowledge tool; Youdao Translation, a tool specifically designed to support translation needs of business and leisure travelers; U-Dictionary, an online dictionary and translation app; Youdao Kids' Dictionary, a smart and fun tool; smart devices, such as Youdao Dictionary Pen, Youdao Listening Pod, Youdao Smart Lamp, Youdao Pocket Translator, and Youdao Super Dictionary; online courses; interactive learning apps; enterprise services, such as Youdao Smart Learning Terminal, a device that automates paper-based homework processing and provides learning diagnosis through artificial intelligence technology at schools; and Youdao Smart Cloud, a cloud-based platform that allows third-party app developers, smart device brands and manufacturers to access advanced optical character recognition capabilities and neural machine translation engine. Its products and services also include NetEase Cloud Music, a music streaming platform; Yanxuan, an e-commerce platform, which sells private label products, including consumer electronics, food, apparel, homeware, kitchenware, and other general merchandise; NetEase Media, an internet media platform; NetEase Mail, an email service; NetEase CC Live streaming, a live streaming platform with a focus on game broadcasting; and NetEase Pay, a payment platform. The company was formerly known as NetEase.com, Inc. and changed its name to NetEase, Inc. in March 2012. NetEase, Inc. was founded in 1997 and is headquartered in Hangzhou, the People's Republic of China.\",\n", " 'companyOfficers': [{'maxAge': 1,\n", " 'name': 'Mr. Lei Ding',\n", " 'age': 50,\n", " 'title': 'Founder, CEO & Director',\n", " 'yearBorn': 1972,\n", " 'fiscalYear': 2009,\n", " 'totalPay': 0,\n", " 'exercisedValue': 0,\n", " 'unexercisedValue': 0},\n", " {'maxAge': 1,\n", " 'name': 'Mr. Zhaoxuan Yang',\n", " 'age': 38,\n", " 'title': 'Chief Financial Officer',\n", " 'yearBorn': 1984,\n", " 'exercisedValue': 0,\n", " 'unexercisedValue': 0},\n", " {'maxAge': 1,\n", " 'name': 'Ms. Margaret Shi',\n", " 'title': 'IR Director',\n", " 'exercisedValue': 0,\n", " 'unexercisedValue': 0},\n", " {'maxAge': 1,\n", " 'name': 'Mr. Feng Zhou',\n", " 'age': 44,\n", " 'title': 'Sr. VP of Search Operations',\n", " 'yearBorn': 1978,\n", " 'exercisedValue': 0,\n", " 'unexercisedValue': 0}],\n", " 'auditRisk': 2,\n", " 'boardRisk': 10,\n", " 'compensationRisk': 8,\n", " 'shareHolderRightsRisk': 2,\n", " 'overallRisk': 8,\n", " 'governanceEpochDate': '2023-03-01 08:00:00',\n", " 'compensationAsOfEpochDate': '2009-12-31 08:00:00',\n", " 'maxAge': 86400}}" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pdd.asset_profile" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index([2023-01-03, 2023-01-04, 2023-01-05, 2023-01-06, 2023-01-09, 2023-01-10,\n", " 2023-01-11, 2023-01-12, 2023-01-13, 2023-01-16, 2023-01-17, 2023-01-18,\n", " 2023-01-19, 2023-01-20, 2023-01-26, 2023-01-27, 2023-01-30, 2023-01-31,\n", " 2023-02-01, 2023-02-02, 2023-02-03, 2023-02-06, 2023-02-07, 2023-02-08,\n", " 2023-02-09, 2023-02-10, 2023-02-13, 2023-02-14, 2023-02-15, 2023-02-16,\n", " 2023-02-17, 2023-02-20, 2023-02-21, 2023-02-22, 2023-02-23, 2023-02-24,\n", " 2023-02-27, 2023-02-28, 2023-03-01, 2023-03-02, 2023-03-03, 2023-03-06,\n", " 2023-03-07],\n", " dtype='object', name='date')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pdd.history()['open'].index.get_level_values(1)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'9999.HK': '1m data not available for startTime=1672502400 and endTime=1673107200. The requested range must be within the last 30 days.'}" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pdd.history(interval='1m', period='7d', start='2023-01-01', end='2023-01-08')" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'9999.HK': '1h data not available for startTime=1591839000 and endTime=1678161432. The requested range must be within the last 730 days.'}" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pdd.history(interval='1h', period='max')" ] } ], "metadata": { "kernelspec": { "display_name": "qlib_py38", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.13" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }