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Browse the tool catalog - Data & Tables | Page 3

Structured data cleanup, analysis, transformation, and table workflows Page 3.

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Data Processing

Excel Formula Evaluator

Evaluate bounded Excel-style formulas against JSON cell values and explain results, references, and spreadsheet errors.

Data Processing

Find Key

Find the first matching key using lodash _.findKey

Data Processing

Fill Array

Fill array with value from start to end index using lodash _.fill

Data Processing

Feature Scaler

Scale and normalize features using various methods for machine learning preprocessing and data standardization

Data Processing

Drop Items

Drop first N items from array using lodash _.drop

Data Processing

Drop Right Items

Drop last N items from array using lodash _.dropRight

Data Processing

Drop While

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

Data Processing

.env Parser

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

Data Processing

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

Data Analysis

Dataset Imbalance Detector & Resampler

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

Data Analysis

Dataset Quality Profiler

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

Data Processing

Defaults Deep

Apply deep default values using lodash _.defaultsDeep