Data Processing

Drop last N items from array using lodash _.dropRight

Data Processing

Drop items from array while predicate is true using lodash _.dropWhile

Data Processing

Extract and validate .env style KEY=VALUE configurations with detection of duplicate keys and suspicious spaces/quotes

Data Processing

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

Data Analysis

Comprehensive data distribution analysis with normality tests, outlier detection, and goodness-of-fit assessments

Data Analysis

Detect class imbalance in CSV or JSON datasets, compare resampling strategies, and preview a balanced output dataset

Data Analysis

Profile CSV or JSON datasets for missing values, duplicate rows, format drift, type inference, and numeric outliers

Data Processing

Vertically append and merge multiple data tables with intelligent column matching

Data Processing

Advanced boundary value processing tool that identifies and handles minimum/maximum values in numerical data. Perfect for data validation, range checking, statistical analysis, and data preprocessing. Features: - Multiple boundary detection methods (absolute, percentile, standard deviation) - Flexible handling strategies (clip, remove, replace, transform) - Custom range validation - Asymmetric boundary handling - Batch processing capabilities - Comprehensive boundary statistics - Data quality assessment - Visual boundary reports Common Use Cases: - Data validation and quality control - Sensor data range checking - Financial data limit enforcement - Statistical data preprocessing - Machine learning feature engineering - Database constraint validation

Data Processing

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 Processing

Remove duplicate rows from CSV files based on multiple column combinations. Perfect for cleaning customer lists, survey responses, and database exports. Features: - Multi-column combination deduplication - Fuzzy matching for similar records - Custom deduplication strategies (keep first, last, or most complete record) - Case-insensitive matching option - Whitespace trimming - Detailed duplicate statistics Common Use Cases: - Remove duplicate customer records - Clean email marketing lists - Eliminate redundant survey responses - Prepare data for analysis

Data Processing

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