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Pandas

Powerful data table manipulation using pandas-style operations - filter, transform, merge, and convert tabular data.

Overview​

The Pandas package provides advanced data table manipulation capabilities inspired by Python's pandas library. Use it when you need to work with structured tabular data, perform complex queries, merge datasets, or convert between data formats.

Key Features​

  • Data Import - Load data from CSV, Excel, JSON, HTML, PDF
  • Data Export - Save data tables to CSV and other formats
  • Table Operations - Add/remove rows and columns
  • Data Transformation - Query, sort, replace, deduplicate
  • Table Merging - Combine multiple data tables

Available Nodes​

  • CSV to DataTable - Import CSV file into data table
  • Excel to DataTable - Import Excel file into data table
  • JSON to DataTable - Convert JSON to data table
  • HTML to DataTable - Extract tables from HTML
  • PDF to DataTable - Extract tables from PDF
  • DataTable to CSV - Export data table to CSV file
  • Add Row - Add a new row to data table
  • Remove Row - Remove a row from data table
  • Add Column - Add a new column to data table
  • Remove Column - Remove a column from data table
  • Get Column - Get all values from a column
  • Query - Filter data table with SQL-like syntax
  • Sort - Sort data table by columns
  • Replace - Replace values in data table
  • Remove Duplicates - Remove duplicate rows
  • Convert Type - Convert column data types
  • Merge Tables - Combine multiple tables
  • Append Table - Append rows from another table

When to Use This Package​

  • Data Processing: Transform and clean datasets
  • Report Building: Aggregate and summarize data
  • Data Integration: Merge data from multiple sources
  • Format Conversion: Convert between CSV, Excel, JSON
  • Data Analysis: Query and filter large datasets

Typical Workflow​

  1. CSV/Excel/JSON to DataTable to load data
  2. Query to filter relevant rows
  3. Sort to order the data
  4. Remove Duplicates to clean data
  5. Add/Remove Columns to reshape
  6. DataTable to CSV to export results

Query Syntax​

Use pandas query syntax to filter data:

  • column > 100 - Numeric comparison
  • status == 'active' - String equality
  • date >= '2024-01-01' - Date comparison
  • Combine with and, or, not