large-excel-analysis-and-formatting SKILL.md skillA
large-excel-analysis-and-formatting from opensensenova/sensenova-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add opensensenova/sensenova-skills/large-excel-analysis-and-formatting@git:20260426.f0ab496Pins git:20260426.f0ab496 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- opensensenova/sensenova-skills
- Path
skills/sn-da-excel-workflow/capability/excel-reading/large-excel-reading/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260426.f0ab496, committed Apr 26, 2026
- Size
- 3,990 bytes
- Repository stars
- 6,031
- License
- MIT
用于处理多Sheet大型Excel文件，支持大文件Parquet格式转换提速，并使用openpyxl生成带条件高亮和自定义样式的格式化Excel报告及下载链接。.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
## Skill Steps
Step1 读取Excel文件，统计所有Sheet的总行数。若数据量过大（如≥1万行），则转换为Parquet格式以显著提升后续读取和分析效率。
```python
import pandas as pd
file_path = "input.xlsx"
xls = pd.ExcelFile(file_path)
total_rows = 0
# 统计所有 sheet 的总行数
for name in xls.sheet_names:
df_temp = pd.read_excel(file_path, sheet_name=name, header=None)
total_rows += len(df_temp)
print(f"总行数: {total_rows}")
# 大文件处理：超过阈值转换为 Parquet 提升效率
if total_rows >= 10000:
parquet_path = "/mnt/data/temp.parquet"
# 此处以读取第一个sheet为例，实际可根据需求合并多个sheet
df = pd.read_excel(file_path, sheet_name=0)
df.to_parquet(engine='pyarrow', path=parquet_path)
df = pd.read_parquet(parquet_path)
else:
df = pd.read_excel(file_path, sheet_name=0)
```
Step2 提取目标数据进行分组汇总分析，并识别出最大值及其对应的分类项。
```python
# 占位示例：根据实际数据集替换列名
group_col = '分类列名' # 如 '控股类型'
target_col = '目标数值列' # 如 '建筑业总产值'
# 假设 df 已清洗并包含所需列，进行汇总分析
summary = df.groupby(group_col)[target_col].sum().reset_index()
# 识别最大值及其对应的分类
max_idx = summary[target_col].idxmax()
max_type = summary.loc[max_idx, group_col]
print(f"最高产值类型: {max_type}")
```
Step3 使用 openpyxl 将分析结果写入新的Excel文件，配置表头样式、边框、列宽，并对满足特定条件（如最大值）的行进行绿色高亮标注，最后生成下载链接。
```python
from openpyxl import Workbook
…Read the whole file at its exact version.
How to install
mdr add opensensenova/sensenova-skills/large-excel-analysis-and-formatting@sha256:28d0d70c66556cf7The line at the top of this page pins the label git:20260426.f0ab496, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_v2ohshkm3vhhge77)
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Versions
The registry has recorded 1 version of this file, committed on Apr 26, 2026.
Audit of the latest version
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- pass: No zero-width or bidi control characters
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Source
opensensenova/sensenova-skills · 6,031 stars · license MIT · pushed 2026-11-03 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_v2ohshkm3vhhge77 GET https://markdownregistry.com/api/v1/resolve?ref=opensensenova/sensenova-skills/large-excel-analysis-and-formatting GET https://markdownregistry.com/api/v1/blob/28d0d70c66556cf7f1cf152a8b6b0abb05468124e5b54f8f46b9ec3d5f98f3bf
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.