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leopard-analysis/notebook/datasource/data.ipynb

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{
"cells": [
{
"cell_type": "code",
"id": "initial_id",
"metadata": {
"collapsed": true,
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"end_time": "2026-01-30T06:48:44.912513Z",
"start_time": "2026-01-30T06:48:44.785729Z"
}
},
"source": [
"import baostock as bs\n",
"import pandas as pd\n",
"\n",
"lg = bs.login()"
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"login success!\n"
]
}
],
"execution_count": 27
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T06:48:59.682551Z",
"start_time": "2026-01-30T06:48:59.515016Z"
}
},
"cell_type": "code",
"source": [
"rs = bs.query_history_k_data_plus(\n",
" \"sz.000001\",\n",
" \"date,code,open,high,low,close,preClose,volume,amount,turn,pctChg\",\n",
" start_date=\"1991-1-1\",\n",
" end_date=\"1992-1-1\",\n",
" adjustflag=\"1\",\n",
")\n",
"data_list = []\n",
"while (rs.error_code == '0') & rs.next():\n",
" data_list.append(rs.get_row_data())\n",
"\n",
"df = pd.DataFrame(data_list, columns=rs.fields)\n",
"# df[\"code\"] = df.apply(lambda row: \".\".join(row[\"code\"].split(\".\")[::-1]).upper(), axis=1)\n",
"df"
],
"id": "ed40fa92230584dc",
"outputs": [
{
"data": {
"text/plain": [
" date code open high low \\\n",
"0 1991-04-03 sz.000001 49.0000000000 49.0000000000 49.0000000000 \n",
"1 1991-04-04 sz.000001 48.7600000000 48.7600000000 48.7600000000 \n",
"2 1991-04-05 sz.000001 48.5200000000 48.5200000000 48.5200000000 \n",
"3 1991-04-08 sz.000001 48.0400000000 48.0400000000 48.0400000000 \n",
"4 1991-04-09 sz.000001 47.8000000000 47.8000000000 47.8000000000 \n",
".. ... ... ... ... ... \n",
"187 1991-12-25 sz.000001 42.5415391500 43.7820300000 42.4685691000 \n",
"188 1991-12-26 sz.000001 42.7604493000 42.7604493000 40.8632280000 \n",
"189 1991-12-27 sz.000001 40.8632280000 41.5929285000 40.8632280000 \n",
"190 1991-12-30 sz.000001 42.7604493000 42.9063894000 42.0307488000 \n",
"191 1991-12-31 sz.000001 42.0307488000 42.8334193500 42.0307488000 \n",
"\n",
" close preClose volume amount turn pctChg \n",
"0 49.0000000000 40.0000000000 100 4900.0000 0.000270 22.500000 \n",
"1 48.7600000000 49.0000000000 300 14628.0000 0.000809 -0.489799 \n",
"2 48.5200000000 48.7600000000 200 9704.0000 0.000539 -0.492202 \n",
"3 48.0400000000 48.2800000000 200 9608.0000 0.000539 -0.497100 \n",
"4 47.8000000000 48.0400000000 400 19120.0000 0.001078 -0.499587 \n",
".. ... ... ... ... ... ... \n",
"187 42.7604493000 42.3955990500 226900 6702870.0000 0.470454 0.860585 \n",
"188 40.8632280000 42.7604493000 191800 5509610.0000 0.397678 -4.436858 \n",
"189 41.5199584500 40.8632280000 210500 5935400.0000 0.436450 1.607146 \n",
"190 42.0307488000 42.6874792500 105900 3093085.0000 0.219573 -1.538462 \n",
"191 42.8334193500 42.0307488000 75900 2203915.0000 0.152534 1.909726 \n",
"\n",
"[192 rows x 11 columns]"
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" <th>code</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
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" <td>1991-04-05</td>\n",
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" <th>3</th>\n",
" <td>1991-04-08</td>\n",
" <td>sz.000001</td>\n",
" <td>48.0400000000</td>\n",
" <td>48.0400000000</td>\n",
" <td>48.0400000000</td>\n",
" <td>48.0400000000</td>\n",
" <td>48.2800000000</td>\n",
" <td>200</td>\n",
" <td>9608.0000</td>\n",
" <td>0.000539</td>\n",
" <td>-0.497100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1991-04-09</td>\n",
" <td>sz.000001</td>\n",
" <td>47.8000000000</td>\n",
" <td>47.8000000000</td>\n",
" <td>47.8000000000</td>\n",
" <td>47.8000000000</td>\n",
" <td>48.0400000000</td>\n",
" <td>400</td>\n",
" <td>19120.0000</td>\n",
" <td>0.001078</td>\n",
" <td>-0.499587</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
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" <tr>\n",
" <th>187</th>\n",
" <td>1991-12-25</td>\n",
" <td>sz.000001</td>\n",
" <td>42.5415391500</td>\n",
" <td>43.7820300000</td>\n",
" <td>42.4685691000</td>\n",
" <td>42.7604493000</td>\n",
" <td>42.3955990500</td>\n",
" <td>226900</td>\n",
" <td>6702870.0000</td>\n",
" <td>0.470454</td>\n",
" <td>0.860585</td>\n",
" </tr>\n",
" <tr>\n",
" <th>188</th>\n",
" <td>1991-12-26</td>\n",
" <td>sz.000001</td>\n",
" <td>42.7604493000</td>\n",
" <td>42.7604493000</td>\n",
" <td>40.8632280000</td>\n",
" <td>40.8632280000</td>\n",
" <td>42.7604493000</td>\n",
" <td>191800</td>\n",
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" <td>-4.436858</td>\n",
" </tr>\n",
" <tr>\n",
" <th>189</th>\n",
" <td>1991-12-27</td>\n",
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" <td>41.5929285000</td>\n",
" <td>40.8632280000</td>\n",
" <td>41.5199584500</td>\n",
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" <td>210500</td>\n",
" <td>5935400.0000</td>\n",
" <td>0.436450</td>\n",
" <td>1.607146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>190</th>\n",
" <td>1991-12-30</td>\n",
" <td>sz.000001</td>\n",
" <td>42.7604493000</td>\n",
" <td>42.9063894000</td>\n",
" <td>42.0307488000</td>\n",
" <td>42.0307488000</td>\n",
" <td>42.6874792500</td>\n",
" <td>105900</td>\n",
" <td>3093085.0000</td>\n",
" <td>0.219573</td>\n",
" <td>-1.538462</td>\n",
" </tr>\n",
" <tr>\n",
" <th>191</th>\n",
" <td>1991-12-31</td>\n",
" <td>sz.000001</td>\n",
" <td>42.0307488000</td>\n",
" <td>42.8334193500</td>\n",
" <td>42.0307488000</td>\n",
" <td>42.8334193500</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>192 rows × 11 columns</p>\n",
"</div>"
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},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 30
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T06:51:04.154374Z",
"start_time": "2026-01-30T06:51:04.096340Z"
}
},
"cell_type": "code",
"source": [
"for year in range(1990, 2025):\n",
" print(year)"
],
"id": "cbb28b1f4857259e",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1990\n",
"1991\n",
"1992\n",
"1993\n",
"1994\n",
"1995\n",
"1996\n",
"1997\n",
"1998\n",
"1999\n",
"2000\n",
"2001\n",
"2002\n",
"2003\n",
"2004\n",
"2005\n",
"2006\n",
"2007\n",
"2008\n",
"2009\n",
"2010\n",
"2011\n",
"2012\n",
"2013\n",
"2014\n",
"2015\n",
"2016\n",
"2017\n",
"2018\n",
"2019\n",
"2020\n",
"2021\n",
"2022\n",
"2023\n",
"2024\n"
]
}
],
"execution_count": 31
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T02:30:18.416075Z",
"start_time": "2026-01-30T02:30:18.255416Z"
}
},
"cell_type": "code",
"source": [
"rs = bs.query_stock_basic(code=\"sz.000001\")\n",
"data_list = []\n",
"while (rs.error_code == '0') & rs.next():\n",
" data_list.append(rs.get_row_data())\n",
"df = pd.DataFrame(data_list, columns=rs.fields)\n",
"df"
],
"id": "3eb9e1033b4360ed",
"outputs": [
{
"data": {
"text/plain": [
" code code_name ipoDate outDate type status\n",
"0 sz.000001 平安银行 1991-04-03 1 1"
],
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" <th>ipoDate</th>\n",
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},
"execution_count": 8,
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"execution_count": 8
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T02:17:09.614916Z",
"start_time": "2026-01-30T02:16:48.773160Z"
}
},
"cell_type": "code",
"source": [
"import adata\n",
"\n",
"adata.stock.info.all_code()"
],
"id": "93a1d7caffc916c",
"outputs": [
{
"data": {
"text/plain": [
" stock_code short_name exchange list_date\n",
"0 000001 平安银行 SZ 1991-04-03\n",
"1 000002 万科A SZ 1991-01-29\n",
"2 000003 PT金田A SZ NaN\n",
"3 000004 *ST国华 SZ 1990-12-01\n",
"4 000005 ST星源 SZ 1990-12-10\n",
"... ... ... ... ...\n",
"5759 920978 开特股份 BJ 2023-09-28\n",
"5760 920981 晶赛科技 BJ 2021-11-15\n",
"5761 920982 锦波生物 BJ 2023-07-20\n",
"5762 920985 海泰新能 BJ 2022-08-08\n",
"5763 920992 中科美菱 BJ 2022-10-18\n",
"\n",
"[5764 rows x 4 columns]"
],
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" <th>short_name</th>\n",
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" <th>2</th>\n",
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" <td>SZ</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>000004</td>\n",
" <td>*ST国华</td>\n",
" <td>SZ</td>\n",
" <td>1990-12-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>000005</td>\n",
" <td>ST星源</td>\n",
" <td>SZ</td>\n",
" <td>1990-12-10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5759</th>\n",
" <td>920978</td>\n",
" <td>开特股份</td>\n",
" <td>BJ</td>\n",
" <td>2023-09-28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5760</th>\n",
" <td>920981</td>\n",
" <td>晶赛科技</td>\n",
" <td>BJ</td>\n",
" <td>2021-11-15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5761</th>\n",
" <td>920982</td>\n",
" <td>锦波生物</td>\n",
" <td>BJ</td>\n",
" <td>2023-07-20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5762</th>\n",
" <td>920985</td>\n",
" <td>海泰新能</td>\n",
" <td>BJ</td>\n",
" <td>2022-08-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5763</th>\n",
" <td>920992</td>\n",
" <td>中科美菱</td>\n",
" <td>BJ</td>\n",
" <td>2022-10-18</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5764 rows × 4 columns</p>\n",
"</div>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 2
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T02:23:11.398502Z",
"start_time": "2026-01-30T02:23:11.257663Z"
}
},
"cell_type": "code",
"source": "adata.stock.market.get_market(stock_code='000001', start_date='2025-01-01', end_date='2025-12-31', adjust_type=0)",
"id": "c716caf5e7157b4f",
"outputs": [
{
"data": {
"text/plain": [
" stock_code trade_time trade_date open close high low \\\n",
"0 000001 2025-01-02 00:00:00 2025-01-02 11.73 11.43 11.77 11.39 \n",
"1 000001 2025-01-03 00:00:00 2025-01-03 11.44 11.38 11.54 11.36 \n",
"2 000001 2025-01-06 00:00:00 2025-01-06 11.38 11.44 11.48 11.22 \n",
"3 000001 2025-01-07 00:00:00 2025-01-07 11.42 11.51 11.53 11.37 \n",
"4 000001 2025-01-08 00:00:00 2025-01-08 11.50 11.50 11.63 11.40 \n",
".. ... ... ... ... ... ... ... \n",
"238 000001 2025-12-25 00:00:00 2025-12-25 11.54 11.56 11.62 11.52 \n",
"239 000001 2025-12-26 00:00:00 2025-12-26 11.56 11.54 11.59 11.53 \n",
"240 000001 2025-12-29 00:00:00 2025-12-29 11.54 11.56 11.62 11.50 \n",
"241 000001 2025-12-30 00:00:00 2025-12-30 11.53 11.48 11.56 11.45 \n",
"242 000001 2025-12-31 00:00:00 2025-12-31 11.48 11.41 11.49 11.40 \n",
"\n",
" volume amount change_pct change turnover_ratio pre_close \n",
"0 181959700 2.102923e+09 -2.31 -0.27 0.94 11.70 \n",
"1 115468000 1.320521e+09 -0.44 -0.05 0.60 11.43 \n",
"2 108553600 1.234306e+09 0.53 0.06 0.56 11.38 \n",
"3 74786300 8.583290e+08 0.61 0.07 0.39 11.44 \n",
"4 106238600 1.223599e+09 -0.09 -0.01 0.55 11.51 \n",
".. ... ... ... ... ... ... \n",
"238 54745500 6.337726e+08 0.17 0.02 0.28 11.54 \n",
"239 43634000 5.040793e+08 -0.17 -0.02 0.22 11.56 \n",
"240 64829500 7.490830e+08 0.17 0.02 0.33 11.54 \n",
"241 58258400 6.694093e+08 -0.69 -0.08 0.30 11.56 \n",
"242 59062000 6.754574e+08 -0.61 -0.07 0.30 11.48 \n",
"\n",
"[243 rows x 13 columns]"
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" <th>turnover_ratio</th>\n",
" <th>pre_close</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>000001</td>\n",
" <td>2025-01-02 00:00:00</td>\n",
" <td>2025-01-02</td>\n",
" <td>11.73</td>\n",
" <td>11.43</td>\n",
" <td>11.77</td>\n",
" <td>11.39</td>\n",
" <td>181959700</td>\n",
" <td>2.102923e+09</td>\n",
" <td>-2.31</td>\n",
" <td>-0.27</td>\n",
" <td>0.94</td>\n",
" <td>11.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>000001</td>\n",
" <td>2025-01-03 00:00:00</td>\n",
" <td>2025-01-03</td>\n",
" <td>11.44</td>\n",
" <td>11.38</td>\n",
" <td>11.54</td>\n",
" <td>11.36</td>\n",
" <td>115468000</td>\n",
" <td>1.320521e+09</td>\n",
" <td>-0.44</td>\n",
" <td>-0.05</td>\n",
" <td>0.60</td>\n",
" <td>11.43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>000001</td>\n",
" <td>2025-01-06 00:00:00</td>\n",
" <td>2025-01-06</td>\n",
" <td>11.38</td>\n",
" <td>11.44</td>\n",
" <td>11.48</td>\n",
" <td>11.22</td>\n",
" <td>108553600</td>\n",
" <td>1.234306e+09</td>\n",
" <td>0.53</td>\n",
" <td>0.06</td>\n",
" <td>0.56</td>\n",
" <td>11.38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>000001</td>\n",
" <td>2025-01-07 00:00:00</td>\n",
" <td>2025-01-07</td>\n",
" <td>11.42</td>\n",
" <td>11.51</td>\n",
" <td>11.53</td>\n",
" <td>11.37</td>\n",
" <td>74786300</td>\n",
" <td>8.583290e+08</td>\n",
" <td>0.61</td>\n",
" <td>0.07</td>\n",
" <td>0.39</td>\n",
" <td>11.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>000001</td>\n",
" <td>2025-01-08 00:00:00</td>\n",
" <td>2025-01-08</td>\n",
" <td>11.50</td>\n",
" <td>11.50</td>\n",
" <td>11.63</td>\n",
" <td>11.40</td>\n",
" <td>106238600</td>\n",
" <td>1.223599e+09</td>\n",
" <td>-0.09</td>\n",
" <td>-0.01</td>\n",
" <td>0.55</td>\n",
" <td>11.51</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>000001</td>\n",
" <td>2025-12-25 00:00:00</td>\n",
" <td>2025-12-25</td>\n",
" <td>11.54</td>\n",
" <td>11.56</td>\n",
" <td>11.62</td>\n",
" <td>11.52</td>\n",
" <td>54745500</td>\n",
" <td>6.337726e+08</td>\n",
" <td>0.17</td>\n",
" <td>0.02</td>\n",
" <td>0.28</td>\n",
" <td>11.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>239</th>\n",
" <td>000001</td>\n",
" <td>2025-12-26 00:00:00</td>\n",
" <td>2025-12-26</td>\n",
" <td>11.56</td>\n",
" <td>11.54</td>\n",
" <td>11.59</td>\n",
" <td>11.53</td>\n",
" <td>43634000</td>\n",
" <td>5.040793e+08</td>\n",
" <td>-0.17</td>\n",
" <td>-0.02</td>\n",
" <td>0.22</td>\n",
" <td>11.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>240</th>\n",
" <td>000001</td>\n",
" <td>2025-12-29 00:00:00</td>\n",
" <td>2025-12-29</td>\n",
" <td>11.54</td>\n",
" <td>11.56</td>\n",
" <td>11.62</td>\n",
" <td>11.50</td>\n",
" <td>64829500</td>\n",
" <td>7.490830e+08</td>\n",
" <td>0.17</td>\n",
" <td>0.02</td>\n",
" <td>0.33</td>\n",
" <td>11.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>241</th>\n",
" <td>000001</td>\n",
" <td>2025-12-30 00:00:00</td>\n",
" <td>2025-12-30</td>\n",
" <td>11.53</td>\n",
" <td>11.48</td>\n",
" <td>11.56</td>\n",
" <td>11.45</td>\n",
" <td>58258400</td>\n",
" <td>6.694093e+08</td>\n",
" <td>-0.69</td>\n",
" <td>-0.08</td>\n",
" <td>0.30</td>\n",
" <td>11.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>242</th>\n",
" <td>000001</td>\n",
" <td>2025-12-31 00:00:00</td>\n",
" <td>2025-12-31</td>\n",
" <td>11.48</td>\n",
" <td>11.41</td>\n",
" <td>11.49</td>\n",
" <td>11.40</td>\n",
" <td>59062000</td>\n",
" <td>6.754574e+08</td>\n",
" <td>-0.61</td>\n",
" <td>-0.07</td>\n",
" <td>0.30</td>\n",
" <td>11.48</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>243 rows × 13 columns</p>\n",
"</div>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 6
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-01-30T07:20:29.946256Z",
"start_time": "2026-01-30T07:20:29.785116Z"
}
},
"cell_type": "code",
"source": [
"import akshare as ak\n",
"\n",
"ak.stock_individual_info_em(symbol='600000')"
],
"id": "f7667bf80cc8c02",
"outputs": [
{
"data": {
"text/plain": [
" item value\n",
"0 最新 10.04\n",
"1 股票代码 600000\n",
"2 股票简称 浦发银行\n",
"3 总股本 33305838300.0\n",
"4 流通股 33305838300.0\n",
"5 总市值 334390616532.0\n",
"6 流通市值 334390616532.0\n",
"7 行业 银行\n",
"8 上市时间 19991110"
],
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" <td>浦发银行</td>\n",
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" <td>总股本</td>\n",
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" <th>8</th>\n",
" <td>上市时间</td>\n",
" <td>19991110</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
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],
"execution_count": 38
},
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}
},
"cell_type": "code",
"source": "ak.stock_individual_basic_info_xq(symbol='SH600005')",
"id": "d58638d8a8b269e7",
"outputs": [
{
"data": {
"text/plain": [
" item \\\n",
"0 org_id \n",
"1 org_name_cn \n",
"2 org_short_name_cn \n",
"3 org_name_en \n",
"4 org_short_name_en \n",
"5 main_operation_business \n",
"6 operating_scope \n",
"7 district_encode \n",
"8 org_cn_introduction \n",
"9 legal_representative \n",
"10 general_manager \n",
"11 secretary \n",
"12 established_date \n",
"13 reg_asset \n",
"14 staff_num \n",
"15 telephone \n",
"16 postcode \n",
"17 fax \n",
"18 email \n",
"19 org_website \n",
"20 reg_address_cn \n",
"21 reg_address_en \n",
"22 office_address_cn \n",
"23 office_address_en \n",
"24 currency_encode \n",
"25 currency \n",
"26 listed_date \n",
"27 provincial_name \n",
"28 actual_controller \n",
"29 classi_name \n",
"30 pre_name_cn \n",
"31 chairman \n",
"32 executives_nums \n",
"33 actual_issue_vol \n",
"34 issue_price \n",
"35 actual_rc_net_amt \n",
"36 pe_after_issuing \n",
"37 online_success_rate_of_issue \n",
"38 affiliate_industry \n",
"\n",
" value \n",
"0 02600005 \n",
"1 武汉钢铁股份有限公司 \n",
"2 武钢股份 \n",
"3 Wuhan Iron And Steel Company Limited \n",
"4 WISCO,Ltd. \n",
"5 冶金产品及副产品、钢铁延伸产品制造及冶金产品的技术开发 \n",
"6   冶金产品及副产品、钢铁延伸产品制造;冶金产品的技术开发;钢铁及副产品的销售;货物进出口、... \n",
"7 420107 \n",
"8 武汉钢铁股份有限公司是由武汉钢铁集团公司控股的、国内第二大钢铁上市公司.是一家主要经营钢铁生... \n",
"9 马国强 \n",
"10 邹继新 \n",
"11 李海涛 \n",
"12 878832000000 \n",
"13 10093780000.0 \n",
"14 27328 \n",
"15 86-27-86217195 \n",
"16 430083 \n",
"17 86-27-86217296 \n",
"18 wiscl@wisco.com.cn \n",
"19 www.wisco.com.cn \n",
"20 湖北省武汉市青山区厂前街(青山区股份公司机关) \n",
"21 None \n",
"22 湖北省武汉市青山区厂前武钢2号门 \n",
"23 None \n",
"24 019001 \n",
"25 CNY \n",
"26 933609600000 \n",
"27 湖北省 \n",
"28 国务院国有资产监督管理委员会 (52.76%) \n",
"29 央企国资控股 \n",
"30 None \n",
"31 邹继新 \n",
"32 5 \n",
"33 320000000.0 \n",
"34 4.3 \n",
"35 1349051600.0 \n",
"36 14.1 \n",
"37 4.923 \n",
"38 None "
],
"text/html": [
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" <th>value</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>org_id</td>\n",
" <td>02600005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>org_name_cn</td>\n",
" <td>武汉钢铁股份有限公司</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>org_short_name_cn</td>\n",
" <td>武钢股份</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>org_name_en</td>\n",
" <td>Wuhan Iron And Steel Company Limited</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>org_short_name_en</td>\n",
" <td>WISCO,Ltd.</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>main_operation_business</td>\n",
" <td>冶金产品及副产品、钢铁延伸产品制造及冶金产品的技术开发</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>operating_scope</td>\n",
" <td>冶金产品及副产品、钢铁延伸产品制造;冶金产品的技术开发;钢铁及副产品的销售;货物进出口、...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>district_encode</td>\n",
" <td>420107</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>org_cn_introduction</td>\n",
" <td>武汉钢铁股份有限公司是由武汉钢铁集团公司控股的、国内第二大钢铁上市公司.是一家主要经营钢铁生...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>legal_representative</td>\n",
" <td>马国强</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>general_manager</td>\n",
" <td>邹继新</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>secretary</td>\n",
" <td>李海涛</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>established_date</td>\n",
" <td>878832000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>reg_asset</td>\n",
" <td>10093780000.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>staff_num</td>\n",
" <td>27328</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>telephone</td>\n",
" <td>86-27-86217195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>postcode</td>\n",
" <td>430083</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>fax</td>\n",
" <td>86-27-86217296</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>email</td>\n",
" <td>wiscl@wisco.com.cn</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>org_website</td>\n",
" <td>www.wisco.com.cn</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>reg_address_cn</td>\n",
" <td>湖北省武汉市青山区厂前街(青山区股份公司机关)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>reg_address_en</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>office_address_cn</td>\n",
" <td>湖北省武汉市青山区厂前武钢2号门</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>office_address_en</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>currency_encode</td>\n",
" <td>019001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>currency</td>\n",
" <td>CNY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>listed_date</td>\n",
" <td>933609600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>provincial_name</td>\n",
" <td>湖北省</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>actual_controller</td>\n",
" <td>国务院国有资产监督管理委员会 (52.76%)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>classi_name</td>\n",
" <td>央企国资控股</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>pre_name_cn</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>chairman</td>\n",
" <td>邹继新</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>executives_nums</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>actual_issue_vol</td>\n",
" <td>320000000.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>issue_price</td>\n",
" <td>4.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>actual_rc_net_amt</td>\n",
" <td>1349051600.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>pe_after_issuing</td>\n",
" <td>14.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>online_success_rate_of_issue</td>\n",
" <td>4.923</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>affiliate_industry</td>\n",
" <td>None</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 41
},
{
"metadata": {},
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"execution_count": null,
"source": "",
"id": "f624320cab54d22"
}
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