CSV Column Profiler

Inspect column types, missing values, and next chart routes before you jump into visualisation or regression.

Use this before Quick Charts or Descriptive Stats when the next question is “What is actually in this CSV?” rather than “Which chart do I want?”

Other languages 日本語 | English

Why use this first?

How to use

  1. Paste CSV or TSV data, or load a small file locally.
  2. Confirm delimiter and whether the first row is a header.
  3. Read the column table, then open the suggested next tool for the columns you want to analyze.

Wave 85 expansion

Inspect columns before charting

This page sits before Quick Charts and Descriptive Stats. It is not a full data-cleaning tool; it is a fast routing and sanity-check page.

Paste CSV or TSV data, then run the profiler.

Checklist
    Warnings

      Column table

      How this differs from nearby tools

      Use Quick Charts when you already know which columns should be plotted. Use Descriptive Stats when one numeric column is already ready for summary. Use this page first when the CSV structure itself still needs a quick sanity check.

      FAQ

      When should I use this instead of Quick Charts?

      Use this page first when you need to inspect columns, missing values, and type guesses before charting. Use Quick Charts after you already know which numeric and categorical columns should be plotted.

      Does this upload my CSV?

      No. Profiling runs locally in your browser. The share URL stores only lightweight settings such as delimiter and header mode, not your pasted dataset.

      What does the next-tool suggestion mean?

      Numeric columns point toward Descriptive Stats or Linear Regression, while text/date columns paired with numeric columns point toward Quick Charts. The suggestion is a routing hint, not a hard rule.

      What should I check before charting?

      Confirm the header row, missing-rate column, and any mixed-type columns first. Clean those issues before you rely on a chart or regression result.