๐Ÿ“Š Instant CSV Data Quality Reports

Upload a file, grab a coffee, and come back to a full audit โ€” all in your browser, no backend, no signup.


Upload your CSV and run analysis

Takes just seconds to load your dataset and start the full analysis process.

1. Data Overview

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High-Level Overview in Seconds

Instantly see the structure and health of your dataset: rows, columns, nulls, outliers, skewness, and more โ€” all in a scrollable dashboard.

  • ๐Ÿ“ Rows ร— columns, column data types
  • โš ๏ธ Null counts, duplicates, constants
  • ๐Ÿ“ˆ Outlier counts (3ฯƒ+) & skewness range
  • ๐Ÿ‘€ Table preview with column names and types

2. Datatype/Statistical Analysis

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Smart Per-Type Breakdown

We break your dataset into numeric, categorical, and boolean types and run deep stats โ€” no plots, just actionable structure.

  • ๐Ÿ“Š Mean, std, skew, kurtosis, min/max for numerics
  • ๐Ÿ”ข Category counts & imbalance detection
  • ๐Ÿงฎ Boolean distributions & missing detection
  • ๐Ÿ” Outlier thresholds across ฯƒ-levels

3. Quality Checklist

Full Data Quality Checklist

Statistical diagnostics spot problems fast โ€” and we explain every flag.

We run a full battery of automated checks to identify issues and give recommendations โ€” no config, no fuss.

  • โš ๏ธ Null Column Check: Flags all columns with missing values
  • ๐Ÿ“‰ Class Imbalance Check: Detects dominant categories (95%+ skew)
  • ๐Ÿชž Duplicate Column Check: Identifies identical feature columns
  • ๐Ÿ” Duplicate Row Check: Spots repeated rows in the dataset
  • ๐Ÿ“Ž Multicollinearity Check: Warns for high VIF (>10) in numeric fields
  • ๐Ÿ“ˆ High Correlation Check: Detects highly correlated feature pairs (> 0.95)
  • ๐Ÿšซ Constant Column Check: Flags columns with a single repeated value
  • ๐ŸŽญ High Cardinality Check: Identifies categorical columns with 50+ unique labels
  • ๐Ÿ“Š Low Variance Check: Highlights numeric columns with zero variance

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Audit While You Brew

Start a full audit now. It runs in-browser, takes seconds, and tells you exactly whatโ€™s wrong โ€” while you sip your coffee.

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