Exploratory Analysis
Automated EDA & Profile
Comprehensive exploratory profiles generated instantaneously from raw datasets.
Recipe Overview & Methodology
Upload any CSV, Parquet, or SQL dataset and receive full univariate and bivariate profiling: column distributions, cardinality, null proportions, skewness, and quantile thresholds.
Statistical Validation Rules
- Automatic schema deduction and statistical type classification.
- Summary statistics: mean, median, mode, IQR, standard deviation.
- Shapiro-Wilk normality testing across continuous numerical columns.
- Automated Vega histogram and density plot generation.
Sample Output Metrics
Columns Analyzed
24
16 numeric, 8 categorical
Null Percentage
0.4%
Clean data health
Non-Normal Columns
6
Non-parametric tests advised
Compute Time
120ms
In-memory engine
Execution LogicClustey Engine
# Automated Exploratory Profile
profile = dataset.profile(
computations=['quantiles', 'normality', 'correlations'],
visual_render='vega_spec'
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