Data Processing

Merge multiple CSV files into a single file with options for header handling and deduplication

Data Processing

Filter CSV data by column values with multiple conditions and operators. Supports 12 filter operators including equals, contains, greater_than, less_than, and empty value checks. Additional Filters examples: [{"column": "age", "operator": "greater_than", "value": "25"}] [{"column": "status", "operator": "equals", "value": "active"}, {"column": "score", "operator": "greater_equal", "value": "80"}] [{"column": "name", "operator": "contains", "value": "john"}, {"column": "email", "operator": "is_not_empty"}]

Data Processing

Sort CSV data by one or multiple columns with ascending/descending order options

Data Processing

Transform and process CSV data with column operations, calculations, and data type conversions. Supports renaming columns, adding calculated columns, removing columns, converting data types, calculating values, and filtering rows. Operation examples: • Rename column: [{"type": "rename", "column": "old_name", "new_name": "new_name"}] • Add calculated column: [{"type": "add_column", "new_column": "total", "formula": "price * quantity"}] • Remove column: [{"type": "remove_column", "remove_column": "column_to_remove"}] • Convert data type: [{"type": "convert_type", "convert_column": "age", "target_type": "number"}] • Calculate values: [{"type": "calculate", "target_column": "total", "expression": "price * tax + shipping"}] • Filter rows: [{"type": "filter_values", "filter_column": "status", "operator": "equals", "value": "active"}]

Data Processing

Split CSV content by specified number of rows per file. Perfect for processing large datasets, dividing data for analysis, batch processing, and managing file size limits. Features: - Split CSV by row count - Support multiple output formats - Preserve header row in each split - Flexible output format options - Support for large datasets - Fast and efficient processing Common Use Cases: - Split large CSV files for processing - Divide data for parallel processing - Create manageable data chunks - Export data in different formats - Prepare data for batch operations - Manage file size limitations

Data Processing

Calculate the coefficient of variation (CV) for numerical columns to measure relative variability

Data Analysis

Calculate confidence intervals for population means using Z or T distributions