csv-analyzerlisted

# CSV Analyzer This Skill analyzes CSV files and provides comprehensive summaries with statistical insights and visualizations, using your built-in tools — no bundled scripts required. ## When to Use This Skill Use this Skill whenever the user: - Uploads or references a CSV file - Asks to summarize, analyze, or visualize tabular data - Requests insights from CSV data - Wants to understand data structure and quality ## How It Works ### Default behavior By default, run the analysis directly — don't make the user pick from a menu of options first. Read the file, inspect its structure, and present a complete summary with relevant charts. The one exception: if the data is genuinely ambiguous (e.g., unclear what a column means, multiple plausible date formats, or it's unclear whether a value is the metric of interest), ask a single short clarifying question, then proceed. This keeps the skill fast while staying consistent with muselab's "ask when ambiguous" stance. ### How to run the analysis Use the built-in tools directly — there is no separate script to call: - Use **Read** to peek at the first rows and understand the columns. - Use **Bash** to run inline Python (pandas, and matplotlib/seaborn if available) for stats and charts. A typical inline analysis looks like: ```bash python3 - <<'PY' import pandas as pd df = pd.read_csv("data.csv") print(df.shape) print(df.dtypes) print(df.describe(include="all")) print(df.isna().sum()) PY ``` For charts, save figures to PNG f