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fix: fix stock_sy_hy_em
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@albertandking
albertandking committed Apr 21, 2024
1 parent b452c6d commit 9281709
Showing 1 changed file with 67 additions and 19 deletions.
86 changes: 67 additions & 19 deletions akshare/stock_feature/stock_sy_em.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
东方财富网-数据中心-特色数据-商誉-个股商誉明细: https://data.eastmoney.com/sy/list.html
东方财富网-数据中心-特色数据-商誉-行业商誉: https://data.eastmoney.com/sy/hylist.html
"""

import pandas as pd
import requests
from tqdm import tqdm
Expand Down Expand Up @@ -65,10 +66,16 @@ def stock_sy_profile_em() -> pd.DataFrame:
data_df["商誉"] = pd.to_numeric(data_df["商誉"], errors="coerce")
data_df["商誉减值"] = pd.to_numeric(data_df["商誉减值"], errors="coerce")
data_df["净资产"] = pd.to_numeric(data_df["净资产"], errors="coerce")
data_df["商誉占净资产比例"] = pd.to_numeric(data_df["商誉占净资产比例"], errors="coerce")
data_df["商誉减值占净资产比例"] = pd.to_numeric(data_df["商誉减值占净资产比例"], errors="coerce")
data_df["商誉占净资产比例"] = pd.to_numeric(
data_df["商誉占净资产比例"], errors="coerce"
)
data_df["商誉减值占净资产比例"] = pd.to_numeric(
data_df["商誉减值占净资产比例"], errors="coerce"
)
data_df["净利润规模"] = pd.to_numeric(data_df["净利润规模"], errors="coerce")
data_df["商誉减值占净利润比例"] = pd.to_numeric(data_df["商誉减值占净利润比例"], errors="coerce")
data_df["商誉减值占净利润比例"] = pd.to_numeric(
data_df["商誉减值占净利润比例"], errors="coerce"
)
data_df.sort_values(["报告期"], inplace=True, ignore_index=True)
return data_df

Expand Down Expand Up @@ -157,15 +164,27 @@ def stock_sy_yq_em(date: str = "20221231") -> pd.DataFrame:
big_df["交易市场"] = big_df["交易市场"].map(
{"shzb": "沪市主板", "kcb": "科创板", "szzb": "深市主板", "cyb": "创业板"}
)
big_df["最新商誉报告期"] = pd.to_datetime(big_df["最新商誉报告期"], errors="coerce").dt.date
big_df["最新商誉报告期"] = pd.to_datetime(
big_df["最新商誉报告期"], errors="coerce"
).dt.date
big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date
big_df["最新一期商誉"] = pd.to_numeric(big_df["最新一期商誉"], errors="coerce")
big_df["上年商誉"] = pd.to_numeric(big_df["上年商誉"], errors="coerce")
big_df["预计净利润-下限"] = pd.to_numeric(big_df["预计净利润-下限"], errors="coerce")
big_df["预计净利润-上限"] = pd.to_numeric(big_df["预计净利润-上限"], errors="coerce")
big_df["业绩变动幅度-下限"] = pd.to_numeric(big_df["业绩变动幅度-下限"], errors="coerce")
big_df["业绩变动幅度-上限"] = pd.to_numeric(big_df["业绩变动幅度-上限"], errors="coerce")
big_df["上年度同期净利润"] = pd.to_numeric(big_df["上年度同期净利润"], errors="coerce")
big_df["预计净利润-下限"] = pd.to_numeric(
big_df["预计净利润-下限"], errors="coerce"
)
big_df["预计净利润-上限"] = pd.to_numeric(
big_df["预计净利润-上限"], errors="coerce"
)
big_df["业绩变动幅度-下限"] = pd.to_numeric(
big_df["业绩变动幅度-下限"], errors="coerce"
)
big_df["业绩变动幅度-上限"] = pd.to_numeric(
big_df["业绩变动幅度-上限"], errors="coerce"
)
big_df["上年度同期净利润"] = pd.to_numeric(
big_df["上年度同期净利润"], errors="coerce"
)
return big_df


Expand Down Expand Up @@ -253,11 +272,19 @@ def stock_sy_jz_em(date: str = "20230331") -> pd.DataFrame:
big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date
big_df["商誉"] = pd.to_numeric(big_df["商誉"], errors="coerce")
big_df["商誉减值"] = pd.to_numeric(big_df["商誉减值"], errors="coerce")
big_df["商誉占净资产比例"] = pd.to_numeric(big_df["商誉占净资产比例"], errors="coerce")
big_df["商誉减值占净资产比例"] = pd.to_numeric(big_df["商誉减值占净资产比例"], errors="coerce")
big_df["商誉占净资产比例"] = pd.to_numeric(
big_df["商誉占净资产比例"], errors="coerce"
)
big_df["商誉减值占净资产比例"] = pd.to_numeric(
big_df["商誉减值占净资产比例"], errors="coerce"
)
big_df["净利润"] = pd.to_numeric(big_df["净利润"], errors="coerce")
big_df["商誉减值占净利润比例"] = pd.to_numeric(big_df["商誉减值占净利润比例"], errors="coerce")
big_df["商誉减值占净利润比例"] = pd.to_numeric(big_df["商誉减值占净利润比例"], errors="coerce")
big_df["商誉减值占净利润比例"] = pd.to_numeric(
big_df["商誉减值占净利润比例"], errors="coerce"
)
big_df["商誉减值占净利润比例"] = pd.to_numeric(
big_df["商誉减值占净利润比例"], errors="coerce"
)
return big_df


Expand Down Expand Up @@ -325,14 +352,27 @@ def stock_sy_em(date: str = "20231231") -> pd.DataFrame:
inplace=True,
)
big_df = big_df[
["序号", "股票代码", "股票简称", "商誉", "商誉占净资产比例", "净利润", "净利润同比", "上年商誉", "公告日期", "交易市场"]
[
"序号",
"股票代码",
"股票简称",
"商誉",
"商誉占净资产比例",
"净利润",
"净利润同比",
"上年商誉",
"公告日期",
"交易市场",
]
]
big_df["交易市场"] = big_df["交易市场"].map(
{"shzb": "沪市主板", "kcb": "科创板", "szzb": "深市主板", "cyb": "创业板"}
)
big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date
big_df["商誉"] = pd.to_numeric(big_df["商誉"], errors="coerce")
big_df["商誉占净资产比例"] = pd.to_numeric(big_df["商誉占净资产比例"], errors="coerce")
big_df["商誉占净资产比例"] = pd.to_numeric(
big_df["商誉占净资产比例"], errors="coerce"
)
big_df["净利润"] = pd.to_numeric(big_df["净利润"], errors="coerce")
big_df["净利润同比"] = pd.to_numeric(big_df["净利润同比"], errors="coerce")
big_df["上年商誉"] = pd.to_numeric(big_df["上年商誉"], errors="coerce")
Expand Down Expand Up @@ -370,7 +410,6 @@ def stock_sy_hy_em(date: str = "20231231") -> pd.DataFrame:
temp_df = pd.DataFrame(data_json["result"]["data"])
big_df = pd.concat([big_df, temp_df], ignore_index=True)
big_df.reset_index(inplace=True, drop=True)
big_df.columns
big_df.rename(
columns={
"REPORT_DATE": "数据日期",
Expand All @@ -388,12 +427,21 @@ def stock_sy_hy_em(date: str = "20231231") -> pd.DataFrame:
inplace=True,
)
big_df = big_df[
["行业名称", "公司家数", "商誉规模", "净资产", "商誉规模占净资产规模比例", "净利润规模"]
[
"行业名称",
"公司家数",
"商誉规模",
"净资产",
"商誉规模占净资产规模比例",
"净利润规模",
]
]
big_df["公司家数"] = pd.to_numeric(big_df["公司家数"], errors="coerce")
big_df["商誉规模"] = pd.to_numeric(big_df["商誉规模"], errors="coerce")
big_df["净资产"] = pd.to_numeric(big_df["净资产"], errors="coerce")
big_df["商誉规模占净资产规模比例"] = pd.to_numeric(big_df["商誉规模占净资产规模比例"], errors="coerce")
big_df["商誉规模占净资产规模比例"] = pd.to_numeric(
big_df["商誉规模占净资产规模比例"], errors="coerce"
)
big_df["净利润规模"] = pd.to_numeric(big_df["净利润规模"], errors="coerce")
return big_df

Expand All @@ -405,7 +453,7 @@ def stock_sy_hy_em(date: str = "20231231") -> pd.DataFrame:
stock_sy_yq_em_df = stock_sy_yq_em(date="20221231")
print(stock_sy_yq_em_df)

stock_sy_jz_em_df = stock_sy_jz_em(date="20230331")
stock_sy_jz_em_df = stock_sy_jz_em(date="20230630")
print(stock_sy_jz_em_df)

stock_sy_em_df = stock_sy_em(date="20231231")
Expand Down

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