CSV Transformations Reference List of available CSV transform operations, with descriptions and example tables.
A comprehensive reference for all built-in CSV transforms. Transform your data with powerful operations for cleaning, reshaping, and analyzing CSV files.
Each transformation includes:
What it does - Clear description of the operationHow it works - Step-by-step explanationBefore & after examples - Visual representation with sample data
Rename Columns
Change one or more column headers.Prod → ProductName, UnitPrice → Price.
Remove Columns
Drop unwanted columns entirely.InternalNotes.
OrderID Prod Qty UnitPrice InternalNotes 1001 Widget A 5 12.50 Check stock levels 1002 Widget B 2 15.00 Discontinued soon 1003 Widget C 3 10.00 Promo item
OrderID ProductName Qty Price 1001 Widget A 5 12.50 1002 Widget B 2 15.00 1003 Widget C 3 10.00
Delete rows matching a condition.Quantity < 3.
OrderID ProductName Quantity Price 1001 Widget A 5 12.50 1002 Widget B 2 15.00 1003 Widget C 3 10.00 1004 Widget D 1 8.00
OrderID ProductName Quantity Price 1001 Widget A 5 12.50 1003 Widget C 3 10.00
Strip out a target word or phrase from cell text.
ID Description 1 Invoice #1234 Draft 2 Payment pending (Draft) 3 Final Report 4 Test Record (Test)
ID Description 1 Invoice #1234 2 Payment pending () 3 Final Report 4 Test Record (Test)
Find and replace substrings in cells.TempUser → Temporary.
UserID Status U001 TempUser U002 Active U003 TempUser U004 Inactive
UserID Status U001 Temporary U002 Active U003 Temporary U004 Inactive
Keep only the first row per group of columns.Email + LastName.
Apply multiple steps in sequence.
OrderID Prod Qty UnitPrice Notes 1001 Widget A 5 12.50 Promo (Draft) 1002 Widget B 2 15.00 Private Note
OrderID ProductName Qty Price 1001 Widget A 5 12.50 1002 Widget B 2 15.00
Strip quotes, symbols, commas, percent signs → parse as numbers.
Quantity Price Sales Percent "5"12.50$1,200.00"50%""2"15.00$800.50"25%"
Quantity Price Sales Percent 5 12.50 1200.00 50 2 15.00 800.50 25
Group by columns and compute metrics (sum, mean, median, min, max, count).
Category Sold NetSales A 10 100 A 5 50 B 20 200
Category Sold NetSales A 15 150 B 20 200
Chaining transforms lets you build complex workflows in one go—each step's output feeds the next. Combine multiple operations to achieve powerful data transformations.
Data Cleaning - Remove duplicates → Remove specific words → Convert to numbersColumn Management - Rename columns → Remove unwanted columns → ReorderAnalysis Prep - Remove rows by condition → Aggregate data → Remove duplicatesText Processing - Replace text → Remove specific words → Rename columns
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