numeric-extraction-and-distribution-analysis SKILL.md skillA
numeric-extraction-and-distribution-analysis 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/numeric-extraction-and-distribution-analysis@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-conditional-formatting/data-bar-formatting/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260426.f0ab496, committed Apr 26, 2026
- Size
- 4,204 bytes
- Repository stars
- 6,031
- License
- MIT
从带单位的字符串列中提取数值并清洗，生成包含直方图、饼图、条形图和累积分布图的多维度综合分布可视化图表，用于展示数据的集中趋势与分布特征。.
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
# Numeric_Extraction_and_Distribution_Analysis
## Skill Steps
Step1 从原始数据中提取目标列，清理无效和空值数据，并安全地将带单位的字符串转换为数值类型
```python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# 配置中英文字体，避免图表乱码
plt.rcParams['font.sans-serif'] = ['SimHei', 'DejaVu Sans']
plt.rcParams['axes.unicode_minus'] = False
item_col = '项目名称' # 占位示例：分类或名称列
value_col = '带单位的数值' # 占位示例：需要提取数值的原始列
numeric_col = '提取数值'
unit_str = 'g' # 占位示例：需要移除的单位字符串
def extract_numeric_value(val_str):
"""从带单位的字符串中提取数值"""
if pd.isna(val_str):
return None
try:
# 移除单位并转换为浮点数
return float(str(val_str).replace(unit_str, '').strip())
except ValueError:
return None
# 清理缺失值与异常占位符
df_clean = df.dropna(subset=[item_col, value_col]).copy()
df_clean = df_clean[df_clean[item_col] != '...']
# 应用提取函数并过滤转换失败的行
df_clean[numeric_col] = df_clean[value_col].apply(extract_numeric_value)
df_clean = df_clean.dropna(subset=[numeric_col])
```
Step2 创建基础分布直方图，并添加平均值和中位数的参考线以展示数据的集中趋势
```python
plt.figure(figsize=(12, 8))
# 绘制直方图
plt.hist(df_clean[numeric_col], bins=10, alpha=0.7, color='skyblue', edgecolor='black')
# 计算并添加平均值和中位数参考线
mean_val = df_clean[numeric_col].mean()
…Read the whole file at its exact version.
How to install
mdr add opensensenova/sensenova-skills/numeric-extraction-and-distribution-analysis@sha256:f22a438b32723360The 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_jw7d6yt3hw5gcdgw)
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Versions
The registry has recorded 1 version of this file, committed on Apr 26, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4204 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
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- pass: No link to a raw IP address
- pass: No script tag
Source
opensensenova/sensenova-skills · 6,031 stars · license MIT · pushed 2026-11-03 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_jw7d6yt3hw5gcdgw GET https://markdownregistry.com/api/v1/resolve?ref=opensensenova/sensenova-skills/numeric-extraction-and-distribution-analysis GET https://markdownregistry.com/api/v1/blob/f22a438b327233606622e70e3474c02f975248d14f4632a38ae51a1eefcd4b77
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.