Show HN: I built an "ilovepdf" for CSV files (and I called it ILoveCSV)
4 months ago
- #data-analytics
- #machine-learning
- #data-visualization
- Unified analytics workspace for transforming, analyzing, and visualizing datasets.
- Voice-powered data analysis via Gemini Live API.
- Predictive analytics for time-series data using native algorithms.
- Interactive visual data exploration and chart generation.
- Automatic statistical profiling including skewness and variance analysis.
- Comprehensive audit for missing values, cardinality, and data types.
- Pearson heatmap for discovering relationships between variables.
- Detailed numeric distribution analysis and variance metrics.
- Linear modeling to identify predictive power between variables.
- Unsupervised segmentation using K-Means algorithm.
- Feature creation using multi-column mathematical expressions.
- Date feature extraction like Weekend, Weekday, Quarter.
- Advanced anomaly detection with capping or removal logic.
- Visual comparison between two dataset versions.
- Strategic missing value filling based on category averages.
- Categorical label renaming and grouping via dictionary logic.
- Text feature extraction (Word Count, Char Count, Contact info).
- Logical integrity rules between columns (e.g., End > Start).
- Normalization (0-1) or standardization of variables.
- Binary numeric feature transformation from categorical strings.
- Grouping continuous numbers into discrete segment buckets.
- Rolling window transformations for time-series denoising.
- Keyword density and term frequency identification in text columns.
- Dynamic multidimensional data summarization and cross-tabulation.
- Dataset collapse into summarized views based on grouping keys.
- Rotation of wide datasets into long formats for BI and databases.
- Dataset combination using exact matching alignment keys.
- Approximate string matching for joining datasets with naming discrepancies.
- Automated deduplication and whitespace sanitization.
- Intelligent similarity-based record deduplication with priority logic.
- Probabilistic record merging using Levenshtein distance similarity.
- Advanced pattern-based data recovery and text transformation.
- Statistical anomaly detection using Z-scores.
- Mathematical shocks or cumulative trends injection into variables.
- Strategic data gap interpolation using linear heuristics.
- Header standardization and snake_case normalization.
- Statistical data expansion via Box-Muller transformations.
- CSV to structured JSON conversion for web and app use.
- Secure transformation baking into native Excel files.
- Spatial text recovery from document layers for tabular extraction.
- Normalization of detected formats to ISO-8601 timestamps.
- Advanced logical query chains with multi-operator support.
- Specialized cleaning for CSV quirks and formatting.
- Unique row extraction in CSV files.
- Value occurrence counting in selected CSV columns.
- Automatic merging of multiple CSVs, aligning columns and resolving header mismatches.
- Instant schema inference and visualization for CSVs, including types and constraints.