Convert Text to CSV / JSON
Transform structured text and lists into CSV and JSON formats with intelligent parsing
Input Text Data
Converted Output
About Text to CSV/JSON Conversion
Our intelligent text converter transforms structured text, lists, and data into standard CSV and JSON formats. Perfect for data migration, API integration, spreadsheet import, and converting unstructured data into machine-readable formats.
Key Features
- Smart Detection: Automatically detects data structure and patterns
- Multiple Input Formats: Handles lists, tables, key-value pairs, and more
- Flexible Parsing: Configurable delimiters and field detection
- Data Validation: Ensures proper CSV and JSON formatting
- Preview Mode: See converted data before download
- Batch Processing: Handle large datasets efficiently
Supported Input Formats
- Delimited Text:
Name, Age, City - Key-Value Pairs:
name: John, age: 30 - Line Lists: Each line becomes a record
- Structured Lists:
• Item 1,- Item 2 - Table Data: Aligned columns of data
- Mixed Format: Combined structured content
CSV Output Features
- Header Generation: Automatic or custom column headers
- Proper Escaping: Handles commas, quotes, and special characters
- UTF-8 Support: Full Unicode character support
- Excel Compatible: Standard CSV format for spreadsheet import
- Custom Delimiters: Alternative separators (semicolon, tab, pipe)
- Quote Handling: Proper quoting of text fields
JSON Output Features
- Object Arrays: Each record as a JSON object
- Nested Structure: Support for hierarchical data
- Data Types: Automatic type inference (string, number, boolean)
- Pretty Formatting: Readable indented JSON output
- Schema Validation: Valid JSON syntax guaranteed
- Metadata Inclusion: Optional metadata and timestamps
Conversion Options
- Field Detection: Smart recognition of data fields
- Data Cleaning: Trim whitespace and normalize values
- Type Conversion: Convert strings to appropriate data types
- Empty Handling: Options for null and empty field treatment
- Custom Mapping: Define field names and types manually
- Batch Settings: Apply same settings to multiple conversions
Common Use Cases
- Convert contact lists for CRM import
- Transform survey data for analysis
- Prepare data for API consumption
- Convert text reports to structured data
- Import data into databases and spreadsheets
- Generate configuration files and data feeds
Data Processing Examples
Input Text:
John Doe, 30, New York
Jane Smith, 25, Los Angeles
Bob Johnson, 35, Chicago
Jane Smith, 25, Los Angeles
Bob Johnson, 35, Chicago
CSV Output:
Name,Age,City
"John Doe",30,"New York"
"Jane Smith",25,"Los Angeles"
"Bob Johnson",35,"Chicago"
"John Doe",30,"New York"
"Jane Smith",25,"Los Angeles"
"Bob Johnson",35,"Chicago"
JSON Output:
[
{"Name":"John Doe","Age":30,"City":"New York"},
{"Name":"Jane Smith","Age":25,"City":"Los Angeles"},
{"Name":"Bob Johnson","Age":35,"City":"Chicago"}
]
{"Name":"John Doe","Age":30,"City":"New York"},
{"Name":"Jane Smith","Age":25,"City":"Los Angeles"},
{"Name":"Bob Johnson","Age":35,"City":"Chicago"}
]
Quality Assurance
- Syntax Validation: Ensures valid CSV and JSON output
- Data Integrity: Preserves original data accuracy
- Error Detection: Identifies parsing issues and inconsistencies
- Preview Verification: Review output before final conversion
- Format Testing: Validates compatibility with target systems
Advanced Options
- Custom field separators and line endings
- Data type specification and conversion
- Conditional formatting and filtering
- Template-based conversion for consistent output
- Batch processing with progress tracking
Best Practices
- • Use consistent delimiters throughout your input data
- • Include headers when possible for better field identification
- • Preview output to verify correct parsing before download
- • Consider data types when generating JSON for APIs
- • Test converted files with target applications