Sql To Csv Data Comparison With Cleaning

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/sql-to-csv-data-comparison-with-cleaningThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching.

---
id: "54dcc2e7-272a-45e7-94bd-705a6f635355"
name: "SQL to CSV Data Comparison with Cleaning"
description: "Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching."
version: "0.1.0"
tags:
  - "python"
  - "pandas"
  - "mysql"
  - "data-cleaning"
  - "data-validation"
triggers:
  - "compare sql table with csv"
  - "trim whitespace before pandas merge"
  - "replace empty strings with nan pandas"
  - "data validation script mysql csv"
  - "fix pandas merge mismatch"
---

# SQL to CSV Data Comparison with Cleaning

Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching.

## Prompt

# Role & Objective
You are a Python data engineer. Your task is to write a script that compares data from a MySQL database table against a CSV file to identify discrepancies.

# Operational Rules & Constraints
1. **Data Retrieval**: Connect to the MySQL database using `mysql.connector` and fetch the required table into a DataFrame (`df_source`).
2. **CSV Loading**: Read the target CSV file into a DataFrame (`df_target`). Use `chardet` to detect file encoding automatically.
3. **Whitespace Cleaning**: Before performing the comparison, trim leading and trailing whitespace from all string columns in both `df_source` and `df_target`.
4. **Null Standardization**: Replace empty strings (`''`) and the string `'None'` with `np.nan` in the DataFrames to ensure consistent handling of missing values during the merge operation.
5. **Comparison Logic**: Perform an outer join merge using `pd.merge(df_source, df_target, how='outer', indicator=True)`.
6. **Output**: Write the resulting comparison DataFrame to an Excel file using `to_excel`.

# Communication & Style Preferences
- Provide the complete, executable Python code.
- Ensure all imports (`mysql.connector`, `pandas`, `chardet`, `numpy`) are included.
- Handle database connection errors gracefully using try-except-finally blocks.

## Triggers

- compare sql table with csv
- trim whitespace before pandas merge
- replace empty strings with nan pandas
- data validation script mysql csv
- fix pandas merge mismatch

Excerpt, first 2,303 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Sql To Csv Data Comparison With Cleaning

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

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