106 characters · 8 words · 106 bytes (UTF-8)
Output will appear here
Click in the output to select all text
106 characters · 8 words · 106 bytes (UTF-8)
Output will appear here
Click in the output to select all text
Validate CSV data integrity, column count consistency, and quoting rules.
Format and align CSV columns with consistent delimiters and quoting.
Convert CSV rows into an array of JSON objects with type inference.
Split large CSV datasets into smaller chunks by row count or condition.
Merge multiple CSV files or blocks into a single unified dataset.
Comprehensive overview of words, characters, sentences, readability, and reading speed.
Before importing or cleaning a dataset, it helps to know what's actually inside it: which columns hold numbers versus text, how many blank cells exist, and how many unique values each column contains. This CSV analyzer profiles your data automatically, generating a per-column summary with inferred data type, null count, and unique value count, along with basic row-level statistics. It's a quick first step for data analysts, engineers doing data cleaning, and anyone auditing a spreadsheet export for quality issues. No formulas or pivot tables needed, just paste your CSV and get an instant profile. Analysis runs entirely in your browser, so your dataset is never uploaded, and there's no signup required. Paste your CSV below to see a full column breakdown.
It shows the inferred data type, count of null or empty values, number of unique values, and for numeric columns, basic statistics like minimum, maximum, and average.
It samples the values in each column and infers whether they're consistently numbers, dates, booleans, or plain text based on their format.
Yes, if a column contains a mix of numbers and text, it's flagged so you can investigate potential data quality issues.
Yes, each column's unique value count is reported, which helps identify categorical fields or potential duplicate records.
No, the entire analysis runs locally in your browser - your data is never transmitted to a server.
Yes, it's a useful pre-import check to catch null values, inconsistent types, and structural anomalies before they cause import failures.
Yes, it profiles every column regardless of width, though extremely large files may take a moment longer to summarize.
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