skills/tushare-data-1.0.5/references/数据接口/宏观经济/国际宏观/美国利率/国债收益率曲线利率.md
wangyitong a65adcc2e5 Initial commit: merged, deduplicated, and vetted skill collection
Sources: extracted from two upstream archives (skill-repo, skills-main),
merged with the following policy:

- 15 broken symlinks (pointing to /Users/jameslee/.cc-switch/skills or
  ../../.agents/skills on a foreign machine) discarded
- 3 real name collisions with identical content (ai-pair, ifind-http-api,
  zhipu-websearch) kept as one copy
- Functional overlaps deduped keeping the strongest variant:
  - docx family: kept docx (official, full toolchain) + docx-cn
    (GB/T 9704 Chinese official-document constants),
    dropped docx_writer (no scripts, name collided with docx)
  - humanizer family: kept humanizer-zh (6 zh reference docs),
    dropped humanizer (en, redundant for CN workflow)
- Skills that only ran in a foreign environment removed:
  ablemind-ops, app-publish, hlb-design-system, openclaw-adj-skill,
  claude-driver
- alphapai excluded from this public repo because its SKILL.md hard-coded
  live credentials

Result: 25 skills, 572 files, ~7.5 MB.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-13 14:47:12 +08:00

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## 国债收益率曲线利率(日频)
----
接口us_tycr
描述:获取美国每日国债收益率曲线利率
限量单次最大可获取2000条数据
权限用户积累120积分可以使用积分越高频次越高。具体请参阅[积分获取办法](https://tushare.pro/document/1?doc_id=13)
<br>
<br>
**输入参数**
名称 | 类型 | 必选 | 描述
---- | ----- | ---- | ----
date | str | N | 日期 YYYYMMDD格式下同
start_date | str | N | 开始日期
end_date | str | N | 结束日期
fields | str | N | 指定输出字段e.g. fields='m1,y1'
<br>
<br>
**输出参数**
名称 | 类型 | 默认显示 | 描述
--- | ---- | ---- | ----
date | str | Y | 日期
m1 | float | Y | 1月期
m2 | float | Y | 2月期
m3 | float | Y | 3月期
m4 | float | Y | 4月期数据从20221019开始
m6 | float | Y | 6月期
y1 | float | Y | 1年期
y2 | float | Y | 2年期
y3 | float | Y | 3年期
y5 | float | Y | 5年期
y7 | float | Y | 7年期
y10 | float | Y | 10年期
y20 | float | Y | 20年期
y30 | float | Y | 30年期
<br>
<br>
**接口调用**
```python
pro = ts.pro_api()
df = pro.us_tycr(start_date='20180101', end_date='20200327')
#获取1月期和1年期数据
df = pro.us_tycr(start_date='20180101', end_date='20200327', fields='m1,y1')
```
<br>
**数据样例**
date m1 m2 m3 m6 y1 y2 y3 y5 y7 y10 y20 y30
0 20200327 0.01 0.03 0.03 0.02 0.11 0.25 0.30 0.41 0.60 0.72 1.09 1.29
1 20200326 0.01 0.01 0.00 0.04 0.13 0.30 0.36 0.51 0.72 0.83 1.20 1.42
2 20200325 0.00 0.00 0.00 0.07 0.19 0.34 0.41 0.56 0.77 0.88 1.23 1.45
3 20200324 0.01 0.01 0.01 0.09 0.25 0.38 0.44 0.52 0.75 0.84 1.19 1.39
4 20200323 0.01 0.04 0.02 0.08 0.17 0.28 0.31 0.38 0.63 0.76 1.12 1.33
... ... ... ... ... ... ... ... ... ... ... ... ... ...
1995 20120405 0.07 None 0.08 0.14 0.19 0.35 0.50 1.01 1.56 2.19 2.97 3.32
1996 20120404 0.08 None 0.08 0.14 0.19 0.35 0.53 1.05 1.62 2.25 3.02 3.37
1997 20120403 0.07 None 0.08 0.15 0.20 0.36 0.56 1.10 1.68 2.30 3.07 3.41
1998 20120402 0.05 None 0.08 0.14 0.18 0.33 0.50 1.03 1.60 2.22 3.00 3.35
1999 20120330 0.05 None 0.07 0.15 0.19 0.33 0.51 1.04 1.61 2.23 3.00 3.35