Working with Data

Working with Data

Learn how to transform, clean, and analyze data in your projects.

Data Transformations

Filter

Remove rows based on conditions:

Column: sales
Condition: greater than
Value: 1000

Select Columns

Choose which columns to keep or remove

Calculate

Add new columns with formulas:

revenue = quantity * price
profit_margin = (revenue - cost) / revenue * 100

Group By

Aggregate data by categories:

Group by: region
Aggregate: SUM(sales), AVG(price)

Join

Combine data from multiple sources:

• Inner join
• Left join
• Right join
• Full outer join

Data Quality

Handle Missing Values

• Remove rows with nulls
• Fill with default value
• Forward/backward fill

Remove Duplicates

Identify and remove duplicate rows

Data Types

Convert columns to correct types:

• Text → Number
• Text → Date
• Number → Text

Next Steps

• Data Connectors
• Creating Projects