Data visualization

Paste data, profile CSV columns, then chart or model the cleaned dataset.

CSV column profiler Quick charts Frequency pack Descriptive stats Linear regression
Other languages 日本語 | English | 简体中文 | 繁體中文 | 繁體中文(香港) | Español | Español (México) | Português (Brasil) | Português (Portugal) | Bahasa Indonesia | Tiếng Việt | 한국어 | Français | Deutsch | Italiano | Русский | हिन्दी | العربية | বাংলা | اردو | Türkçe | ไทย | Polski | Filipino | Bahasa Melayu | فارسی | Nederlands | Українська | עברית

Quick guide

  1. Paste CSV or TSV first when you need types, missing values, and the next chart or stats page.
  2. Move to quick charts once columns are clean and you want a fast visual check.
  3. Open descriptive stats when the next question is a one-column summary.
  4. Open linear regression when the next question is a two-column relationship.

Data quality check

Clean labels first. Keep one variable in one column.

Check outliers before you draw conclusions from charts.

Use the same scale when comparing two groups.

Export charts with notes so your future self can read them fast.

When sharing, include sample size and filters on the same page.

If data changes often, save one baseline chart for comparison.

Keep color and axis choices consistent across reports so trends remain easy to compare month to month.

Before presenting to stakeholders, add one plain-language caption that explains what changed, by how much, and why the change matters for decisions.

Tools

Calculators