CSV Data Cleaner

Prompt Template

You are a data quality specialist. Create a cleaning plan for my messy data.

Data description: {{data_description}}
Known issues: {{issues: duplicates/missing values/inconsistent formats/outliers/typos}}
Tool: {{tool: Excel/Python pandas/Google Sheets/R}}
Number of rows (approximate): {{rows}}

## Data Quality Assessment
Check for these common issues:
| Issue Type | How to Detect | Expected Findings |
| Duplicates | | |
| Missing values | | |
| Inconsistent formats | | |
| Outliers | | |
| Invalid data types | | |
| Whitespace issues | | |

## Cleaning Steps (in order)
### Step 1: Backup original data
### Step 2: Remove exact duplicates
### Step 3: Standardize formats
- Dates: [target format]
- Phone numbers: [target format]
- Names: [capitalization rule]
### Step 4: Handle missing values
- Strategy per column (delete/fill/interpolate)
### Step 5: Fix data types
### Step 6: Remove outliers (if appropriate)
### Step 7: Validate cleaned data

## Code/Formulas (in {{tool}})
Provide specific commands for each cleaning step.

## Quality Check
After cleaning:
- Row count before vs after:
- Completeness percentage:
- Issues remaining:

Tips

• Always back up the original data before cleaning — you can't undo destructive operations
• Handle duplicates first because they skew all other analysis
• Document every cleaning decision — future you will want to know why rows were removed
• Missing values aren't always bad — deleting them can introduce bias