Text-to-Table Viewer

Convert structured text into interactive, searchable tables with advanced formatting

About Text-to-Table Conversion

Our text-to-table viewer transforms structured text data into interactive, sortable, and searchable tables. Perfect for analyzing logs, CSV data, tab-separated values, and any other structured text format with consistent patterns.

Key Features

  • Multiple Formats: CSV, TSV, pipe-separated, and custom delimiters
  • Auto-Detection: Automatically detects common delimiters and formats
  • Interactive Tables: Sort, filter, and search through data
  • Data Type Recognition: Identifies numbers, dates, and text columns
  • Header Detection: Automatically identifies header rows
  • Export Options: Export processed tables as CSV, JSON, or HTML

Supported Input Formats

  • CSV: Name,Age,City
  • TSV: Name Age City (tab-separated)
  • Pipe-separated: Name|Age|City
  • Space-separated: Name Age City
  • Fixed-width: Columns aligned by spaces
  • Custom delimiter: Any character as separator

Table Features

  • Column Sorting: Click headers to sort data ascending/descending
  • Global Search: Search across all columns and rows
  • Column Filtering: Individual column filters for precise data selection
  • Data Type Icons: Visual indicators for numbers, dates, and text
  • Row Highlighting: Hover effects and selection highlighting
  • Pagination: Handle large datasets with page navigation

Data Processing

  • Header Detection: Automatically identifies first row as headers
  • Data Cleaning: Trims whitespace and handles empty cells
  • Type Inference: Detects numbers, dates, booleans, and text
  • Null Handling: Properly handles empty and null values
  • Encoding Support: UTF-8 and other character encodings

Common Use Cases

  • Analyze CSV files and spreadsheet data
  • Parse log files and structured text reports
  • Convert text lists into searchable tables
  • Preview and validate data before import
  • Quick data exploration and analysis
  • Generate HTML tables from text data

Advanced Options

  • Custom Delimiters: Define any character or string as separator
  • Quote Handling: Properly parse quoted values with embedded delimiters
  • Escape Sequences: Handle escaped characters in data
  • Skip Rows: Ignore header or footer rows
  • Column Selection: Choose which columns to display
  • Data Transformation: Apply basic formatting to columns

Export Formats

  • CSV: Standard comma-separated values format
  • JSON: Structured data with column types and metadata
  • HTML Table: Complete HTML table with styling
  • TSV: Tab-separated values for Excel compatibility

Performance Tips

  • • For large datasets, consider pagination to improve performance
  • • Use consistent delimiters throughout your data
  • • Include headers in the first row for better column identification
  • • Quote text values that contain the delimiter character

Data Validation

  • Automatic detection of inconsistent row lengths
  • Identification of malformed data and parsing errors
  • Statistics on data completeness and quality
  • Warnings for potential data issues

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