pandas-analysis

pandas-analysis is a skill for Kiro from ihatesea69/kiro-kit. It costs 28 tokens per session (296 once invoked), scanned A, original, MIT.

A guide to cleaning, combining, and analysing table-shaped data with pandas, a Python library for working with datasets. It covers grouping, joining, time series, and exploratory analysis.

In plain words
What is it for?
Use it to clean columns, filter rows, calculate grouped summaries, merge datasets, analyse time-based data, and build repeatable data-processing pipelines.
Why use it?
It helps turn messy or separate datasets into reliable results while making missing values and incorrect assumptions visible.

Skill for Kiro

Written for Kiro: installed under .kiro/.

Good fit Use it to clean columns, filter rows, calculate grouped summaries, merge datasets, analyse time-based data, and build repeatable data-processing pipelines.

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Install with agentmods
npx agentmods add skills/ihatesea69/kiro-kit/pandas-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ihatesea69/kiro-kit --skill pandas-analysis
Clone the repo
git clone --depth 1 https://github.com/ihatesea69/kiro-kit

Made for: Kiro.

Wrote this? Show the measurements

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agentmods badge for pandas-analysis

README.md
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Your own site
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agentmods 80×15 button for pandas-analysis

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Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 296 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00296
Opus 5 $0.00014 $0.00148
Sonnet 5 $0.00006 $0.00059
Haiku 4.5 $0.00003 $0.00030

Measured 6d ago against content hash 4e67cf203b40, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

pandas-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.kiro/skills/pandas-analysis/SKILL.md · 50 lines

What it actually says

Pandas Analysis

Activate this skill when working with tabular data using pandas.

When to Use

  • Cleaning and preprocessing datasets
  • Performing groupby aggregations
  • Merging and joining multiple DataFrames
  • Time series manipulation
  • Exploratory data analysis

Patterns

import pandas as pd

# Method chaining for clean pipelines
result = (
    df.pipe(clean_column_names)
    .query("revenue > 0")
    .assign(margin=lambda x: x.revenue - x.cost)
    .groupby("category")
    .agg(total_margin=("margin", "sum"), count=("margin", "size"))
    .sort_values("total_margin", ascending=False)
)

Performance Tips

  • Use category dtype for low-cardinality strings
  • Prefer vectorized operations over apply()
  • Use read_csv(usecols=...) to load only needed columns
  • Consider pyarrow backend for large datasets
  • Use query() over boolean indexing for readability

Rules

  • Always inspect data shape and dtypes first
  • Handle missing values explicitly (never ignore NaN)
  • Validate assumptions about uniqueness and cardinality
  • Use .copy() to avoid SettingWithCopyWarning
  • Document data transformations with comments
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 50 lines · 28 tokens per session scan A 4e67cf203b40

Subscribe to this mod's changes

pandas-analysis is a skill published in the GitHub repository ihatesea69/kiro-kit (18 stars, last pushed 21d ago), licensed MIT. It adds 28 tokens to every session and 296 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.