Free — no account required

Exploratory Analysis In Minutes

Upload data, get exploratory analysis results with interactive charts. Free.

24,000+ analyses run
Encrypted & deleted in 7 days
PDF & citation included

Drop your CSV here

or click to browse · max 3 MB

📊
-
Rows
-
Columns
-
Numeric

Running exploratory data analysis - high-dimensional demo analysis...

Running exploratory data analysis - high-dimensional demo analysis...

Your report is ready

Sent to — interactive charts, statistical results, R code, and AI insights.

Analyze another file
Sample Output

Every report includes interactive charts, tables, and AI insights

Upload your data to get your own report

View all case studies See all free tools

How it works

Comprehensive exploratory analysis for high-dimensional datasets with mixed variable types.

Use this when you need exploratory analysis on your data.

See related tools for alternatives.

Built for: Analyst, data scientist, business user

Typical data source: CSV with relevant columns

analytics

What data do you need?

Data for exploratory analysis

dimension (any)
example1
example2
example3

Minimum 10 rows · Best with 100-5000 rows

What's in the report?

Comprehensive exploratory analysis template for high-dimensional datasets with mixed numeric and categorical variables. Demonstrates full EDA capabilities with bivariate comparisons, statistical tests, normality checks, pairwise plots, cross-tabulation, and feature importance ranking.

📋

Descriptive Statistics

Summary statistics for all numeric variables

📉

Distributions

Distribution of each numeric variable

🟧

Correlation Analysis

Pairwise Pearson correlations between numeric variables

📊

Missing Values

Missing data patterns across variables

🔵

Bivariate Analysis

Pairwise relationships between key variables

📋

Statistical Tests

ANOVA and Kruskal-Wallis tests for group differences

📋

Normality Tests

Shapiro-Wilk normality test for each numeric variable

📊

Target Analysis

Distribution of the dependent variable

📊

Feature Importance

Relative importance of variables for predicting the target

🔵

Pairwise Plots

Scatterplot matrix of top numeric variables

📋

Validation

Data quality and integrity checks

🤖

AI Insights

Plain-English interpretation — what the numbers mean, what's significant, and what to do next.

Questions?

See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.

Your data has more stories to tell

Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.

Try Free — No Credit Card
Powered by MCP Analytics