Data Profiler
Load any supported file to get an instant profile: row count, column types, null rates, distinct value counts, and numeric statistics. No upload — runs entirely in your browser.
Drop your .csv file here
or click to browse — max 50 MB
More Power Tools
SQL Query Tool
Write SQL queries against any loaded file. Join, aggregate, filter across multiple files.
Join Files
Join two files with INNER, LEFT, RIGHT, or FULL OUTER joins on any key column.
Find Duplicates
Find duplicate rows across any column combination and export the results.
Pivot Table
Build pivot tables from any data file — rows, columns, values, and aggregation.
Data Catalog
Browse free public datasets and query them directly in the SQL editor.
Mock Data Generator
Generate realistic sample data — names, emails, dates, numbers, and more.
Chart Builder
Visualize any data file as a bar chart, line chart, scatter plot, or histogram.
Lookup Tool
Add a column by looking up values from a reference table — like Excel VLOOKUP.
XML to CSV
Convert XML files to CSV, JSON, Parquet, and more — no upload required.
SQL Importer
Import a SQL dump and export the data as CSV, Parquet, or JSON.
Excel Sheet Extractor
Extract any sheet from a multi-sheet Excel workbook and convert to CSV or Parquet.
Frequently Asked Questions
Is my file uploaded to be profiled?
No. The profiler runs entirely in your browser using a WebAssembly SQL engine. Your file is read locally, statistics are computed on your device, and nothing is transmitted to any server.
What does the profile include?
Row count, column names and detected data types, null counts and null rates per column, distinct value counts, and min/max/mean for numeric columns — the checks you would normally script in pandas, without any code.
What file formats can I profile?
CSV, TSV, Parquet, JSON, NDJSON, Excel (XLSX), YAML, and Apache Arrow files are all supported.
When should I profile a file?
Before loading data into a database, warehouse, or ML pipeline. A ten-second profile catches unexpected nulls, wrongly typed columns, and suspicious distinct counts before they become downstream failures.