Why use this first?
- Check whether each column looks numeric, text, boolean, date, or mixed before charting.
- See missing-rate, unique-count, range, and outlier hints in one pass.
- Route each column toward Quick Charts, Descriptive Stats, or Linear Regression without guessing.
如何使用
- Paste CSV or TSV data, or load a small file locally.
- Confirm delimiter and whether the first row is a header.
- Read the column table, then open the suggested next tool for the columns you want to analyze.
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.
Column table
How this differs from nearby tools
使用 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.
常見問題解答
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.