CSV Analyzer

Upload or paste CSV/TSV files and get instant per‑column statistics—counts, unique values, nulls, and numeric min/max—entirely in your browser.

🎯 Over 8.5K successful operations completed

Start Analyzing CSV Files

Get instant column stats and export a concise report

Load Data

Summary

Rows: 0
Columns: 0

Column Statistics

Load a CSV or paste data to see analysis.

How to Use CSV Analyzer

  1. 1

    Import CSV or TSV

    Upload a .csv/.tsv file or paste data directly. The analyzer auto-detects delimiters but you can switch between comma, tab, semicolon, or pipe.

    Tip:Clean headers first for best results; prefer consistent casing and no spaces.
  2. 2

    Verify Headers & Delimiter

    Confirm the header row and check the delimiter setting. Adjust if columns look misaligned or quoted fields appear split.

    Tip:If your data contains commas inside quotes, keep auto-detect or set comma explicitly.
  3. 3

    Review Column Statistics

    Inspect per-column stats: total rows, non‑null values, nulls, unique counts, and min/max for numeric or length ranges for text.

    Tip:Use unique counts and nulls to spot keys, sparsity, and potential data quality issues.
  4. 4

    Export Findings

    Download a CSV summary of your analysis for documentation, QA, or to share insights with your team.

    Tip:Keep this report in your PR or issue for traceability of dataset assumptions.

Security & Privacy

  • Analysis runs entirely in your browser; files never leave your device.
  • No data is uploaded, logged, or stored.
  • Very large CSVs may affect performance — sample or split before analysis.

Common Pitfalls

  • Quoted commas can split columns if delimiter is forced incorrectly.
  • Mixed header casing makes joins harder — normalize headers first.
  • Large files may be slow — sample or split before analysis.

Features & Benefits

📊

Instant Column Stats

Counts, unique values, nulls, and per-column distributions at a glance.

🔢

Numeric Min/Max

Auto-detect numeric columns and compute min/max for quick sanity checks.

🧠

Automatic Delimiter Detection

Automatically detects tab/comma; supports semicolon and pipe as well.

📎

Upload or Paste

Analyze local files or paste raw CSV/TSV directly into the tool.

⬇️

Exportable Report

Download a concise CSV report of your results for reviews and audits.

🔒

Privacy‑First

Runs entirely in your browser—no uploads or external processing.

Frequently Asked Questions

Is my file uploaded anywhere?

No. All analysis runs locally in your browser. Files never leave your device.

Which delimiters are supported?

Auto‑detect covers comma and tab by default. You can also choose semicolon or pipe explicitly.

How are min/max computed?

For numeric columns we compute numeric min/max. For text columns we show min/max string length across unique values.

Does it handle quoted fields?

Yes. The parser respects quotes so commas inside quotes do not split columns.

What is the row limit?

Designed for typical CSVs used in day‑to‑day workflows. Very large files may be slower depending on your device.

Can I export results?

Yes. Download a CSV report summarizing per‑column stats for documentation or sharing.

Technical Specifications

Processing: 100% client‑side
Delimiters: Auto‑detect comma/tab; supports semicolon/pipe
Stats: Counts, unique, nulls, numeric min/max
Headers: First‑row header detection
Limits: Bound by browser memory
Privacy: No uploads or storage

Use Cases & Applications

Data QA

Data Quality Checks

Assess null rates, uniqueness, and ranges before importing into a database.

Exploration

Schema Discovery

Identify candidate keys and numeric columns quickly when exploring new datasets.

ETL

Pre‑ETL Inspection

Validate assumptions and catch anomalies before running transformations.

Analytics

Analytics Prep

Confirm column types and value distributions prior to dashboarding.

Engineering

Bug Reproduction

Attach a compact analysis report to issues for faster triage.

Governance

Review & Compliance

Share column statistics during reviews to document data handling.