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European Number Format Conversion
Demonstrates handling of European number formats where periods are thousands separators and commas are decimal separators (1.234,56 = 1234.56). Also shows ID column detection and preservation logic for columns containing 'ID' in the name.
Input
What you provide to the skill
fix types - data has european numbers: Customer_ID,Order_ID,Revenue,Quantity
00123,A-001,“1.234,56”,10
00456,A-002,“2.567,89”,5
Output
What the skill generates for you
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TYPE VALIDATION REPORT
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CURRENT DATA TYPES:
Customer_ID int64
Order_ID object
Revenue object
Quantity int64
dtype: object
CURRENT DATA:
Customer_ID Order_ID Revenue Quantity
0 123 A-001 1.234,56 10
1 456 A-002 2.567,89 5
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COLUMNS TO PRESERVE AS STRINGS
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Detected ID columns (preserving leading zeros):
- Customer_ID: contains 'ID', has leading zeros (00123, 00456)
- Order_ID: contains 'ID'
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CONVERTING EUROPEAN NUMBER FORMAT
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1. Converting 'Revenue' column:
Original type: object (European format with quotes)
Detected format: '1.234,56' (period=thousands, comma=decimal)
Transformations:
- Remove quotes
- Remove period (thousands separator)
- Replace comma with period (decimal separator)
New type: float64
Successful: 2 | Failed: 0
2. Converting 'Quantity' column:
Original type: int64
Already correct numeric type
No conversion needed
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FINAL DATA TYPES
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Customer_ID int64
Order_ID object
Revenue float64
Quantity int64
dtype: object
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CLEANED DATA PREVIEW
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Customer_ID Order_ID Revenue Quantity
0 123 A-001 1234.56 10
1 456 A-002 2567.89 5
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DATA SUMMARY
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Total rows: 2
Revenue range: 1234.56 to 2567.89
Revenue total: 3802.45
Total quantity: 15
Exported: /workspace/data_cleaned.csv
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CLEANED CSV CONTENT
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Customer_ID,Order_ID,Revenue,Quantity
123,A-001,1234.56,10
456,A-002,2567.89,5
About This Skill
Validate and fix data types in datasets - convert dates stored as strings, numbers with currency symbols, percentages, and booleans to proper types with error handling.
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