skills/tushare-data-1.0.5/references/数据接口/指数专题/指数月线行情.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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## 指数月线行情
----
接口index_monthly
描述:获取指数月线行情,每月更新一次
限量单次最大1000行记录,可多次获取,总量不限制
积分用户需要至少600积分才可以调取积分越多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
---- | ----- | ---- | ----
ts_code | str | N | TS代码
trade_date | str | N | 交易日期
start_date | str | N | 开始日期
end_date | str | N | 结束日期
<br>
<br>
**输出参数**
名称 | 类型 | 默认显示 | 描述
--- | ---- | ---- | ----
ts_code | str | Y | TS指数代码
trade_date | str | Y | 交易日
close | float | Y | 收盘点位
open | float | Y | 开盘点位
high | float | Y | 最高点位
low | float | Y | 最低点位
pre_close | float | Y | 昨日收盘点
change | float | Y | 涨跌点位
pct_chg | float | Y | 涨跌幅
vol | float | 成交量(手)
amount | float | 成交额(千元)
<br>
<br>
**接口用法**
```python
pro = ts.pro_api()
df = pro.index_monthly(ts_code='000001.SH', start_date='20180101', end_date='20190330', fields='ts_code,trade_date,open,high,low,close,vol,amount')
```
或者
```python
df = pro.index_monthly(trade_date='20190329', fields='ts_code,trade_date,open,high,low,close,vol,amount')
```
<br>
<br>
**数据样例**
ts_code trade_date close open high low \
0 000001.SH 20190329 3090.758 2954.402 3129.940 2930.835
1 000001.SH 20190228 2940.954 2597.778 2997.488 2590.554
2 000001.SH 20190131 2584.572 2497.881 2630.318 2440.907
3 000001.SH 20181228 2493.896 2647.132 2666.078 2462.845
4 000001.SH 20181130 2588.188 2617.033 2703.512 2555.322
5 000001.SH 20181031 2602.783 2768.208 2771.938 2449.197
6 000001.SH 20180928 2821.350 2716.404 2827.341 2644.296
7 000001.SH 20180831 2725.250 2882.506 2897.400 2653.112
8 000001.SH 20180731 2876.401 2841.580 2915.297 2691.021
9 000001.SH 20180629 2847.418 3084.754 3128.715 2782.381
10 000001.SH 20180531 3095.474 3087.409 3219.740 3041.000
11 000001.SH 20180427 3082.232 3169.779 3220.845 3041.625
12 000001.SH 20180330 3168.897 3235.089 3333.875 3091.458
13 000001.SH 20180228 3259.408 3478.670 3495.093 3062.743
14 000001.SH 20180131 3480.833 3314.031 3587.032 3314.031
vol amount
0 8.691925e+11 8.300906e+12
1 4.421808e+11 3.816145e+12
2 3.385641e+11 2.804232e+12
3 2.575119e+11 2.236021e+12
4 4.052823e+11 3.352502e+12
5 2.740242e+11 2.449081e+12
6 2.148359e+11 2.152910e+12
7 2.821389e+11 2.872973e+12
8 3.049095e+11 3.259243e+12
9 2.623979e+11 3.100450e+12
10 2.979289e+11 3.810441e+12
11 2.698985e+11 3.372116e+12
12 3.704084e+11 4.396937e+12
13 2.888959e+11 3.262255e+12
14 4.797771e+11 5.772056e+12