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Dev #5516

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Jan 9, 2025
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Dev #5516

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d0c6d95
feat: add version 1.15.68
albertandking Jan 9, 2025
24edf96
docs: update date
albertandking Jan 9, 2025
d9bea0b
feat: add version 1.15.68
albertandking Jan 9, 2025
6886224
fix: fix stock_research_report_em
albertandking Jan 9, 2025
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3 changes: 2 additions & 1 deletion akshare/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2977,9 +2977,10 @@
1.15.65 fix: fix option_czce_daily interface
1.15.66 fix: fix fund_etf_dividend_sina interface
1.15.67 fix: fix stock_hold_change_cninfo interface
1.15.68 fix: fix stock_research_report_em interface
"""

__version__ = "1.15.67"
__version__ = "1.15.68"
__author__ = "AKFamily"

import sys
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64 changes: 46 additions & 18 deletions akshare/stock_feature/stock_research_report_em.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,15 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2023/8/20 20:00
Date: 2025/1/9 21:35
Desc: 东方财富网-数据中心-研究报告-个股研报
https://data.eastmoney.com/report/stock.jshtml
"""

import pandas as pd
import requests
from tqdm import tqdm

from akshare.utils.tqdm import get_tqdm


def stock_research_report_em(symbol: str = "000001") -> pd.DataFrame:
Expand Down Expand Up @@ -40,7 +42,9 @@ def stock_research_report_em(symbol: str = "000001") -> pd.DataFrame:
r = requests.get(url, params=params)
data_json = r.json()
total_page = data_json["TotalPage"]
current_year = data_json["currentYear"]
big_df = pd.DataFrame()
tqdm = get_tqdm()
for page in tqdm(range(1, total_page + 1), leave=False):
params.update(
{
Expand All @@ -53,9 +57,15 @@ def stock_research_report_em(symbol: str = "000001") -> pd.DataFrame:
r = requests.get(url, params=params)
data_json = r.json()
temp_df = pd.DataFrame(data_json["data"])
big_df = pd.concat([big_df, temp_df], axis=0, ignore_index=True)
big_df = pd.concat(objs=[big_df, temp_df], axis=0, ignore_index=True)
big_df.reset_index(inplace=True)
big_df["index"] = big_df["index"] + 1
predict_this_year_eps_title = f"{current_year}-盈利预测-收益"
predict_this_year_pe_title = f"{current_year}-盈利预测-市盈率"
predict_next_year_eps_title = f"{current_year + 1}-盈利预测-收益"
predict_next_year_pe_title = f"{current_year + 1}-盈利预测-市盈率"
predict_next_two_year_eps_title = f"{current_year + 2}-盈利预测-收益"
predict_next_two_year_pe_title = f"{current_year + 2}-盈利预测-市盈率"
big_df.rename(
columns={
"index": "序号",
Expand All @@ -68,12 +78,12 @@ def stock_research_report_em(symbol: str = "000001") -> pd.DataFrame:
"publishDate": "日期",
"infoCode": "-",
"column": "-",
"predictNextTwoYearEps": "-",
"predictNextTwoYearPe": "-",
"predictNextYearEps": "2024-盈利预测-收益",
"predictNextYearPe": "2024-盈利预测-市盈率",
"predictThisYearEps": "2023-盈利预测-收益",
"predictThisYearPe": "2023-盈利预测-市盈率",
"predictNextTwoYearEps": predict_next_two_year_eps_title,
"predictNextTwoYearPe": predict_next_two_year_pe_title,
"predictNextYearEps": predict_next_year_eps_title,
"predictNextYearPe": predict_next_year_pe_title,
"predictThisYearEps": predict_this_year_eps_title,
"predictThisYearPe": predict_this_year_pe_title,
"predictLastYearEps": "-",
"predictLastYearPe": "-",
"actualLastTwoYearEps": "-",
Expand Down Expand Up @@ -122,20 +132,38 @@ def stock_research_report_em(symbol: str = "000001") -> pd.DataFrame:
"东财评级",
"机构",
"近一月个股研报数",
"2023-盈利预测-收益",
"2023-盈利预测-市盈率",
"2024-盈利预测-收益",
"2024-盈利预测-市盈率",
predict_this_year_eps_title,
predict_this_year_pe_title,
predict_next_year_eps_title,
predict_next_year_pe_title,
predict_next_two_year_eps_title,
predict_next_two_year_pe_title,
"行业",
"日期",
]
]
big_df["日期"] = pd.to_datetime(big_df["日期"], errors="coerce").dt.date
big_df["近一月个股研报数"] = pd.to_numeric(big_df["近一月个股研报数"], errors="coerce")
big_df["2023-盈利预测-收益"] = pd.to_numeric(big_df["2023-盈利预测-收益"], errors="coerce")
big_df["2023-盈利预测-市盈率"] = pd.to_numeric(big_df["2023-盈利预测-市盈率"], errors="coerce")
big_df["2024-盈利预测-收益"] = pd.to_numeric(big_df["2024-盈利预测-收益"], errors="coerce")
big_df["2024-盈利预测-市盈率"] = pd.to_numeric(big_df["2024-盈利预测-市盈率"], errors="coerce")
big_df["近一月个股研报数"] = pd.to_numeric(
big_df["近一月个股研报数"], errors="coerce"
)
big_df[predict_this_year_eps_title] = pd.to_numeric(
big_df[predict_this_year_eps_title], errors="coerce"
)
big_df[predict_this_year_pe_title] = pd.to_numeric(
big_df[predict_this_year_pe_title], errors="coerce"
)
big_df[predict_next_year_eps_title] = pd.to_numeric(
big_df[predict_next_year_eps_title], errors="coerce"
)
big_df[predict_next_year_pe_title] = pd.to_numeric(
big_df[predict_next_year_pe_title], errors="coerce"
)
big_df[predict_next_two_year_eps_title] = pd.to_numeric(
big_df[predict_next_two_year_eps_title], errors="coerce"
)
big_df[predict_next_two_year_pe_title] = pd.to_numeric(
big_df[predict_next_two_year_pe_title], errors="coerce"
)
return big_df


Expand Down
6 changes: 6 additions & 0 deletions docs/changelog.md
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Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,10 @@

## 更新说明详情

1.15.68 fix: fix stock_research_report_em interface

1. 修复 stock_research_report_em 接口

1.15.67 fix: fix stock_hold_change_cninfo interface

1. 修复 stock_hold_change_cninfo 接口
Expand Down Expand Up @@ -4957,6 +4961,8 @@

## 版本更新说明

1.15.68 fix: fix stock_research_report_em interface

1.15.67 fix: fix stock_hold_change_cninfo interface

1.15.66 fix: fix fund_etf_dividend_sina interface
Expand Down
32 changes: 17 additions & 15 deletions docs/data/stock/stock.md
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Expand Up @@ -10278,7 +10278,7 @@ print(stock_zdhtmx_em_df)
数据示例

```
序号 股票代码 股票简称 ... 最新财务报表的营业收入 签署日期 公告日期
序号 股票代码 股票简称 ... 最新财务报表的营业收入 签署日期 公告日期
0 1 688516 奥特维 ... NaN NaN 2023-08-18
1 2 688132 邦彦技术 ... NaN NaN 2023-08-18
2 3 831526 凯华材料 ... 5.101723e+07 NaN 2023-08-17
Expand Down Expand Up @@ -10320,10 +10320,12 @@ print(stock_zdhtmx_em_df)
| 东财评级 | object | - |
| 机构 | object | - |
| 近一月个股研报数 | int64 | - |
| 2023-盈利预测-收益 | float64 | - |
| 2023-盈利预测-市盈率 | float64 | - |
| 2024-盈利预测-收益 | float64 | - |
| 2024-盈利预测-市盈率 | float64 | - |
| 2025-盈利预测-收益 | float64 | - |
| 2025-盈利预测-市盈率 | float64 | - |
| 2026-盈利预测-收益 | float64 | - |
| 2026-盈利预测-市盈率 | float64 | - |
| 行业 | object | - |
| 日期 | object | - |

Expand All @@ -10339,19 +10341,19 @@ print(stock_research_report_em_df)
数据示例

```
序号 股票代码 股票简称 ... 2024-盈利预测-市盈率 行业 日期
0 1 000001 平安银行 ... 4.13 银行 2023-04-29
1 2 000001 平安银行 ... 3.80 银行 2023-04-26
2 3 000001 平安银行 ... 4.13 银行 2023-04-25
3 4 000001 平安银行 ... 3.51 银行 2023-04-25
4 5 000001 平安银行 ... 3.89 银行 2023-04-25
序号 股票代码 股票简称 ... 2026-盈利预测-市盈率 行业 日期
0 1 000001 平安银行 ... 4.54 银行 2024-10-22
1 2 000001 平安银行 ... 4.54 银行 2024-10-22
2 3 000001 平安银行 ... 4.90 银行 2024-10-20
3 4 000001 平安银行 ... NaN 银行 2024-10-19
4 5 000001 平安银行 ... 3.90 银行 2024-08-30
.. ... ... ... ... ... .. ...
296 297 000001 平安银行 ... NaN 银行 2017-03-22
297 298 000001 平安银行 ... NaN 银行 2017-03-20
298 299 000001 平安银行 ... NaN 银行 2017-03-17
299 300 000001 平安银行 ... NaN 银行 2017-03-07
300 301 000001 平安银行 ... NaN 银行 2017-02-03
[301 rows x 13 columns]
271 272 000001 平安银行 ... NaN 银行 2017-03-22
272 273 000001 平安银行 ... NaN 银行 2017-03-20
273 274 000001 平安银行 ... NaN 银行 2017-03-17
274 275 000001 平安银行 ... NaN 银行 2017-03-07
275 276 000001 平安银行 ... NaN 银行 2017-02-03
[276 rows x 15 columns]
```

#### 沪深京 A 股公告
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2 changes: 1 addition & 1 deletion docs/introduction.md
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Expand Up @@ -6,7 +6,7 @@
**风险提示**：[AKShare](https://github.com/akfamily/akshare) 开源财经数据接口库所采集的数据皆来自公开的数据源，不涉及任何个人隐私数据和非公开数据。
同时本项目提供的数据接口及相关数据仅用于学术研究，任何个人、机构及团体使用本项目的数据接口及相关数据请注意商业风险。

1. 本文档更新时间：**2025-01-08**；
1. 本文档更新时间：**2025-01-09**；
2. 如有 [AKShare](https://github.com/akfamily/akshare) 库、文档及数据的相关问题，请在 [AKShare Issues](https://github.com/akfamily/akshare/issues) 中提 Issues；
3. 欢迎关注 **数据科学实战** 微信公众号；<div><img src="https://jfds-1252952517.cos.ap-chengdu.myqcloud.com/akshare/readme/qrcode/ds.png"></div>
4. **知识星球【数据科学实战】** 2025 全新改版，聚焦于量化投资内容，欢迎加入 **知识星球【数据科学实战】** 高质量社区，里面有丰富的视频课程、问答、文章、书籍及代码等内容：
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