Automated Data Analysis

Analyze your dataset.

Upload a CSV file to inspect data quality, calculate descriptive statistics, identify outliers and relationships, and visualize important patterns.

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Upload your dataset

Drop your CSV file here, or choose one from your computer.

Select CSV File Exploration stays in your browser. Model training uses the secure cloud API.

Dataset

Dataset successfully loaded.

Rows0

Columns0

Missing Values0

Duplicate Rows0

Data Quality

Initial assessment of the uploaded dataset.

Data Health Score

100%

Numeric Columns

Text / Categorical

Potential Outliers

Automated Findings

Important observations detected during the initial analysis.

Descriptive Statistics

Summary statistics for numeric variables. Outliers are detected using the 1.5 × IQR rule.

Visual Exploration

Inspect numeric and categorical distributions.

Numeric Distribution

Categorical Frequency

Correlation Analysis

Pearson correlations between numeric variables. Values near +1 or -1 indicate stronger linear relationships.

Variable 1	Variable 2	Correlation	Strength

Machine Learning Mode

Select the variable you want to predict. The analyzer will inspect the target and determine the most likely machine-learning problem type.

Target variable

Analysis goal

Detected Problem —

Target Type —

Unique Target Values —

The models above are structural candidates. Run live training below to compare supported models using measured cross-validation performance.

Train & Compare Models

Run predictive modeling for the selected target. The backend preprocesses usable features, performs cross-validation, compares supported models, and recommends the strongest tested model.

Exploratory analysis above runs locally in your browser. Clicking Train & Compare Models sends your CSV to the hosted analysis API for model training. Do not upload confidential, regulated, or sensitive personal data.

Recommended Model

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Selected from the models tested by the API.

Column Analysis

Type detection, missing values, cardinality, and column-level quality information.

Dataset Preview

Showing the first 10 rows.

End-to-End Analytics Workflow

This analyzer combines browser-based exploratory analysis with server-side predictive modeling. Model recommendations are based on measured performance from the models actually tested by the API.