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Dev #3990

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Jul 19, 2023
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Dev #3990

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23ad030
fix issue #3979 (https://github.com/akfamily/akshare/issues/3979) (#3…
JiangJamm Jul 19, 2023
4197f0b
add version
albertandking Jul 19, 2023
1bcd4a8
fix macro_cnbs
albertandking Jul 19, 2023
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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 @@ -2475,9 +2475,10 @@
1.10.58 fix: fix fund_etf_hist_em interface
1.10.59 add: add fund_announcement_personnel_em interface
1.10.60 add: add macro_usa_cpi_yoy interface
1.10.61 fix: fix macro_cnbs interface
"""

__version__ = "1.10.60"
__version__ = "1.10.61"
__author__ = "AKFamily"

import sys
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24 changes: 22 additions & 2 deletions akshare/economic/marco_cnbs.py
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@@ -1,7 +1,7 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2023/3/22 20:22
Date: 2023/7/19 18:20
Desc: 国家金融与发展实验室-中国宏观杠杆率数据
http://114.115.232.154:8080/
"""
Expand All @@ -19,9 +19,26 @@ def macro_cnbs() -> pd.DataFrame:
temp_df = pd.read_excel(
url, sheet_name="Data", header=0, skiprows=1, engine="openpyxl"
)

temp_df["Period"] = pd.to_datetime(temp_df["Period"]).dt.strftime("%Y-%m")
temp_df.dropna(axis=1, inplace=True)
temp_df.columns = [

temp_df.rename(
columns={
"Period": "年份",
"Household": "居民部门",
"Non-financial corporations": "非金融企业部门",
"Central government ": "中央政府",
"Local government": "地方政府",
"General government": "政府部门",
"Non financial sector": "实体经济部门",
"Financial sector(asset side)": "金融部门资产方",
"Financial sector(liability side)": "金融部门负债方",
},
inplace=True,
)

column_order = [
"年份",
"居民部门",
"非金融企业部门",
Expand All @@ -32,6 +49,8 @@ def macro_cnbs() -> pd.DataFrame:
"金融部门资产方",
"金融部门负债方",
]
temp_df = temp_df.reindex(columns=column_order)

temp_df["居民部门"] = pd.to_numeric(temp_df["居民部门"], errors="coerce")
temp_df["非金融企业部门"] = pd.to_numeric(temp_df["非金融企业部门"], errors="coerce")
temp_df["政府部门"] = pd.to_numeric(temp_df["政府部门"], errors="coerce")
Expand All @@ -40,6 +59,7 @@ def macro_cnbs() -> pd.DataFrame:
temp_df["实体经济部门"] = pd.to_numeric(temp_df["实体经济部门"], errors="coerce")
temp_df["金融部门资产方"] = pd.to_numeric(temp_df["金融部门资产方"], errors="coerce")
temp_df["金融部门负债方"] = pd.to_numeric(temp_df["金融部门负债方"], errors="coerce")

return temp_df


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6 changes: 6 additions & 0 deletions docs/changelog.md
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Expand Up @@ -63,6 +63,10 @@

## 更新说明详情

1.10.61 fix: fix macro_cnbs interface

1. 修复 macro_cnbs 接口

1.10.60 add: add macro_usa_cpi_yoy interface

1. 新增 macro_usa_cpi_yoy 接口
Expand Down Expand Up @@ -2654,6 +2658,8 @@

## 版本更新说明

1.10.61 fix: fix macro_cnbs interface

1.10.60 add: add macro_usa_cpi_yoy interface

1.10.59 add: add fund_announcement_personnel_em interface
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25 changes: 13 additions & 12 deletions docs/data/macro/macro.md
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Expand Up @@ -44,18 +44,19 @@ print(macro_cnbs_df)
数据示例

```
年份 居民部门 非金融企业部门 ... 实体经济部门 金融部门资产方 金融部门负债方
0 1993-12 8.311222 91.658000 ... 107.791459 8.896441 7.128428
1 1994-12 7.808230 82.411703 ... 98.354271 9.808787 6.796868
2 1995-12 8.240004 80.950106 ... 97.850373 10.009081 7.006151
3 1996-03 8.403456 81.711651 ... 99.241521 10.183896 7.186300
4 1996-06 8.581114 82.051373 ... 99.679459 10.379730 7.380510
.. ... ... ... ... ... ... ...
93 2018-09 52.575456 155.641011 ... 245.227043 61.350917 60.645733
94 2018-12 53.198837 153.553140 ... 243.702122 60.638348 60.936158
95 2019-03 54.277928 156.881879 ... 248.828108 60.542178 59.417322
96 2019-06 55.304291 155.743313 ... 249.533412 58.736094 58.727086
97 2019-09 56.314848 155.618498 ... 251.147265 55.820243 59.358625
年份 居民部门 非金融企业部门 政府部门 中央政府 地方政府 实体经济部门 金融部门资产方 金融部门负债方
0 1992-12 7.5 90.0 8.3 4.4 3.9 105.8 7.8 7.2
1 1993-03 7.5 91.1 8.1 4.2 3.9 106.7 7.8 7.3
2 1993-06 7.4 91.1 8.2 4.4 3.8 106.7 7.7 7.3
3 1993-09 7.3 90.2 8.3 4.6 3.7 105.8 7.7 7.3
4 1993-12 7.0 87.8 7.8 4.2 3.6 102.6 8.9 7.1
.. ... ... ... ... ... ... ... ... ...
117 2022-03 61.8 158.2 47.3 19.9 27.4 267.3 49.2 62.6
118 2022-06 62.0 160.3 49.6 20.2 29.4 271.9 50.0 63.9
119 2022-09 62.1 160.9 49.8 20.9 28.9 272.7 49.3 63.9
120 2022-12 61.9 160.9 50.4 21.4 29.0 273.1 50.0 64.4
121 2023-03 63.3 167.0 51.5 21.4 30.1 281.8 52.7 65.6
[122 rows x 9 columns]
```

#### 国民经济运行状况
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