# CSV Splitter 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 > Canonical page: https://elysiatools.com/en/tools/csv-splitter - **Category:** Data Processing - **Keywords:** csv, split, text, separator, rows, data processing, file management ## Overview The CSV Splitter is a high-performance utility designed to break down large CSV datasets into smaller, manageable chunks based on a specific row count. It allows you to maintain data integrity by preserving header rows across all segments and offers flexible output formats including JSON, Markdown, and plain tables to suit your specific workflow requirements. ## Inputs - **CSV Content** (textarea): Paste your CSV content here... Example: Name,Age,City John,25,New York Jane,30,London Bob,35,Paris - **Rows Per File** (number): Maximum number of data rows in each split file (excluding headers) - **Include Header Row** (checkbox): Add header row to each split file - **Output Format** (select) ## When to use - When you need to bypass file size limitations for uploads or email attachments. - When preparing large datasets for parallel processing or batch operations. - When you need to extract specific segments of data from a massive CSV file for easier analysis. ## How it works - Paste your CSV content into the input area. - Specify the maximum number of rows you want in each resulting file. - Choose whether to include the header row in every split segment. - Select your preferred output format and generate the segmented data. ## Use cases - Dividing massive customer databases into smaller batches for email marketing campaigns. - Splitting log files to meet the import requirements of specific database management systems. - Converting large CSV datasets into JSON format for easier integration with web applications. ## Frequently asked questions ### Can I keep the header row in every split file? Yes, by enabling the 'Include Header Row' option, the tool will automatically prepend the original header to every generated segment. ### What is the maximum number of rows I can process? The tool supports up to 100,000 rows per file, making it suitable for most standard data processing tasks. ### Does this tool support formats other than CSV? Yes, you can convert your split data into JSON, Markdown tables, or plain text tables directly through the output format settings. ### Is my data uploaded to a server? This tool processes your data locally in your browser, ensuring your sensitive information remains private and secure. ### What happens if my CSV has fewer rows than the split limit? If your total row count is less than the specified limit, the tool will return the data as a single file without splitting it. ## Related tools - [Data Crosstab Generator](https://elysiatools.com/en/tools/data-crosstab-generator): Advanced crosstab (pivot table) generator that creates powerful cross-tabulation analysis from your data. Perfect for business intelligence, statistical analysis, data exploration, and reporting. Features: - Multiple aggregation functions (sum, count, average, min, max, median) - Flexible row and column grouping - Percentage and ratio calculations - Row/column totals and grand totals - Multi-dimensional analysis - Conditional formatting support - Statistical significance testing - Custom sorting and filtering - Export-ready formatting Common Use Cases: - Sales analysis by region and product - Customer demographics analysis - Financial statement analysis - Survey response analysis - Inventory turnover analysis - Performance metrics tracking - [Data Noise Injection](https://elysiatools.com/en/tools/data-noise-injection): Inject various types of noise into text data for testing purposes. Perfect for stress testing data processing systems, testing data quality algorithms, and creating realistic test datasets. Features: - Character-level noise injection - Word-level noise injection - Numeric data noise - Formatting noise - Whitespace noise - Special character noise - Configurable intensity levels - Realistic noise patterns Common Use Cases: - Test data validation systems - Stress test parsing algorithms - Evaluate error handling - Test data cleaning algorithms - Create realistic messy data - Benchmark data processing performance - [Header Adder](https://elysiatools.com/en/tools/header-adder): Add headers to CSV data that lacks column names. Perfect for data import from databases, API responses, or numeric datasets that need proper column identification. Features: - Add custom headers to header-less data - Auto-generate intelligent headers - Support for various header naming conventions - Preview headers before applying - Multiple header format options - Support for existing data detection - Batch processing capabilities Common Use Cases: - Fix database exports without headers - Process API response data - Prepare numeric datasets for analysis - Standardize data column naming - Create proper CSV structures - Data format normalization - [Structured Log Analyzer](https://elysiatools.com/en/tools/structured-log-analyzer): Detect common log formats, extract core fields, infer field types, and export parsed logs as JSON, CSV, or SQL inserts - [BOM Character Remover](https://elysiatools.com/en/tools/data-bom-remover): Remove BOM (Byte Order Mark) characters from text and file content. Perfect for cleaning up text files that have encoding issues, fixing CSV imports, and preparing data for processing. Features: - Detect and remove UTF-8 BOM (EF BB BF) - Detect and remove UTF-16 BOM (FE FF or FF FE) - Detect and remove UTF-32 BOM (00 00 FE FF or FF FE 00 00) - Support multiple input formats - Visual BOM character display - Detailed detection report - Support for batch text processing Common Use Cases: - Fix CSV file import errors - Clean up text file encoding issues - Prepare data for JSON parsing - Fix XML parsing problems - Resolve API data encoding conflicts - Standardize text data format - [Data Cleaner](https://elysiatools.com/en/tools/data-cleaner): Clean and standardize data by fixing spelling errors, standardizing formats, removing duplicates, and filling missing values - [Data Interpolator](https://elysiatools.com/en/tools/data-interpolator): Advanced data interpolation tool that fills missing values and generates data points using various mathematical methods. Perfect for time series analysis, data completion, signal processing, and scientific computing. Features: - Multiple interpolation methods (linear, polynomial, spline, cubic) - Time series interpolation with date/time support - Forward fill and backward fill options - Nearest neighbor interpolation - Custom interpolation parameters - Missing value detection and reporting - Data point generation and densification - Support for multiple columns simultaneously - Interactive interpolation preview Common Use Cases: - Sensor data gap filling - Financial data completion - Scientific experiment data processing - Time series forecasting preparation - Image and signal processing - Statistical data imputation - [Duplicate Column Remover](https://elysiatools.com/en/tools/duplicate-column-remover): Remove duplicate columns from CSV data with flexible detection strategies. Perfect for cleaning datasets, removing redundant information, and optimizing data structure. Features: - Detect columns with identical headers - Find columns with identical data content - Support for case-sensitive/insensitive matching - Multiple removal strategies available - Preserve data integrity - Support for large datasets - Fast and efficient processing Common Use Cases: - Clean up merged datasets - Remove redundant data columns - Optimize data for analysis - Prepare data for machine learning - Reduce file size and complexity - Standardize data format ## Samples - [CSV Samples](https://elysiatools.com/en/samples/csv-samples): Sample CSV files with various data types, sizes, and complexity levels - [Windows String Processing - C# Samples](https://elysiatools.com/en/samples/windows-string-processing-csharp): Comprehensive C# string processing examples for Windows platform including string manipulation, splitting, joining, regex operations, and text analysis - [Python Samples](https://elysiatools.com/en/samples/python): Essential Python code examples and Hello World demonstrations - [Apache Arrow Samples](https://elysiatools.com/en/samples/arrow): Apache Arrow in-memory columnar format examples for high-performance data processing and analytics ## Related content - [CSV Cleanup, Reshaping, and Delivery Workflow](https://elysiatools.com/en/hubs/csv-utility): Inspect CSV structure, keep the right columns, reshape rows, compare outputs, and split final files for dependable imports or reporting.