CSV Analyzer

About this tool

Paste CSV data to get a quick analysis: number of rows and columns, the column names, and how many non-empty values each column has.

Example

Input: name,age\nAlice,30

Output: Rows: 1, Columns: 2

Privacy

This tool runs entirely in your browser. Your data is processed locally and never uploaded to a server.

How to use this tool

1. Paste your CSV text into the input box.
2. Check that the first row contains the column names you expect.
3. Review the row count, column count, and the list of column names.
4. Look at each column's non-empty value count to spot missing data.

Step by step, what happens

1. The tool reads the pasted CSV as plain comma-separated rows and columns.
2. It identifies the first row as the header row and uses it to show the column names.
3. It counts how many data rows are present and how many columns appear in the CSV.
4. It scans each column and counts values that are not empty so you can compare completeness across fields.

Worked example

Suppose you want to quickly check whether a small contact list has the right columns and any missing values.

Input: name,email,phone Alice,alice@example.com,555-0101 Bob,,555-0102

1. The tool reads the header row as name, email, and phone.
2. It counts two data rows and three columns.
3. It reports the non-empty value counts for each column so you can see that email is missing in one row.

Tips and common mistakes

• Make sure the first row is a header row, because the tool uses it as the column name list.
• Keep the delimiter consistent, since mixed commas and other separators can change how columns are read.
• If a field should count as empty, leave it blank between delimiters and do not add spaces inside it.
• Use the non-empty counts to catch missing data quickly, especially when one column has fewer filled values than the others.

Frequently asked questions