Free online CSV analyzer. Just upload your CSV file in the form below, and this tool will automatically print detailed information about its structure, values, and selected columns. In the options, you can choose which statistics to include in the output, such as general CSV dimensions, value type detection, shortest and longest values, and detailed statistics for specific columns. Created by programmers from team Browserling.
Free online CSV analyzer. Just upload your CSV file in the form below, and this tool will automatically print detailed information about its structure, values, and selected columns. In the options, you can choose which statistics to include in the output, such as general CSV dimensions, value type detection, shortest and longest values, and detailed statistics for specific columns. Created by programmers from team Browserling.
This tool analyzes CSV (Comma Separated Values) files and prints a detailed plain-text report about the file structure and values. It helps you inspect the CSV structure and contents before using the data. Paste your CSV into the input box, and the tool will count rows, columns, expected values, total values, empty values, whitespace-only values, and missing values. It also detects common value types, such as strings, integers, decimals, booleans, dates, times, date-and-time values, email addresses, and URLs. In the input options, you can choose the delimiter character, quote character, and comment-line prefix. For example, use a comma for regular CSV, a semicolon for semicolon-separated files, or \t for tab-separated data. If your file contains comment lines that start with a character such as #, the tool can skip them. You can also skip empty lines and choose whether the first analyzable row should be treated as headers. When headers are skipped, they are excluded from statistics, but they can still be used for selecting columns by name. The analysis can include three main sections. General information provides an overview of the CSV. It prints the number of analyzed rows and columns, the expected number of values, the actual total number of values, and the locations of empty, whitespace-only, and missing values. The value types section shows the types of data that appear in the CSV. It counts string values, numeric values, integers, decimals, booleans, dates, times, date-and-time values, email addresses, and URLs. The value lengths section lists the shortest and longest non-empty values. Each listed value includes its character length and its original row and column position, so you can quickly find unusually short or long fields in the source CSV. You can also enable column analysis to inspect specific columns in more detail. Select columns by position, such as 1, 2, 5, or by ranges, such as 1-3. Negative positions count from the end, so -1 means the last column and -2 means the second-to-last column. You can also select a column by its header name, and if the same header appears more than once, you can analyze all matching columns. Each column report shows the actual column number, the first value in that column, the total number of existing values, the number of empty values, the number of whitespace-only values, the number of missing values, the detected value type, the numeric minimum, maximum, average, and the shortest or longest values. Csv-abulous!
This tool analyzes CSV (Comma Separated Values) files and prints a detailed plain-text report about the file structure and values. It helps you inspect the CSV structure and contents before using the data. Paste your CSV into the input box, and the tool will count rows, columns, expected values, total values, empty values, whitespace-only values, and missing values. It also detects common value types, such as strings, integers, decimals, booleans, dates, times, date-and-time values, email addresses, and URLs. In the input options, you can choose the delimiter character, quote character, and comment-line prefix. For example, use a comma for regular CSV, a semicolon for semicolon-separated files, or \t for tab-separated data. If your file contains comment lines that start with a character such as #, the tool can skip them. You can also skip empty lines and choose whether the first analyzable row should be treated as headers. When headers are skipped, they are excluded from statistics, but they can still be used for selecting columns by name. The analysis can include three main sections. General information provides an overview of the CSV. It prints the number of analyzed rows and columns, the expected number of values, the actual total number of values, and the locations of empty, whitespace-only, and missing values. The value types section shows the types of data that appear in the CSV. It counts string values, numeric values, integers, decimals, booleans, dates, times, date-and-time values, email addresses, and URLs. The value lengths section lists the shortest and longest non-empty values. Each listed value includes its character length and its original row and column position, so you can quickly find unusually short or long fields in the source CSV. You can also enable column analysis to inspect specific columns in more detail. Select columns by position, such as 1, 2, 5, or by ranges, such as 1-3. Negative positions count from the end, so -1 means the last column and -2 means the second-to-last column. You can also select a column by its header name, and if the same header appears more than once, you can analyze all matching columns. Each column report shows the actual column number, the first value in that column, the total number of existing values, the number of empty values, the number of whitespace-only values, the number of missing values, the detected value type, the numeric minimum, maximum, average, and the shortest or longest values. Csv-abulous!
In this example, we analyze a short reading list CSV containing book titles, page counts, and read flags (true/false). We enable only the General Information and Value Types blocks. The report shows that the CSV has 3 rows, 3 columns, and 9 values that should exist; all 9 values are present, so there are no empty, whitespace-only, or missing fields. The value type analysis shows that the CSV contains text values, integer page counts, and boolean read flags.
In this example, we analyze a CSV file containing a small course catalog. The data has three columns: course name, number of lessons, and course level. The general analysis shows 7 rows and 3 columns, so the CSV should contain 21 values. It actually contains 20 values because the last row is missing the level field. The analysis also finds one empty value in the SQL lessons column. The value-length analysis then lists the shortest existing values, including the one-digit lesson counts, and the longest values, including the course level names.
In this example, we inspect two columns from CSV-style greenhouse sensor data that uses semicolons as delimiters. We set the input delimiter to a semicolon, ignore the comment line and the empty line, skip the headers from the statistics, and analyze the "value" and "measured_at" columns by name. The analysis shows that the "value" column is a clean decimal column and gives its minimum, maximum, and average. In the "measured_at column", the analyzer checks that every time entry is present and written in the correct HH:MM format.
You can pass input to this tool via ?input query argument and it will automatically compute output. Here's how to type it in your browser's address bar. Click to try!
Edit the contents of a CSV file in a neat editor.
Remove duplicate rows in a CSV file.
Convert a CSV file to an HTML table.
Convert an HTML table to a CSV file.
Convert a CSV file to a Markdown table.
Convert a Markdown table to a CSV file.
Draw an ASCII table from CSV data.
Draw an ANSI table from CSV data.
Draw a Unicode table from CSV data.
Convert CSV to a PDF document.
Extract data from a PDF and create a CSV file.
Create a screenshot of CSV data.
Draw a CSV file as a PNG, JPG or GIF picture.
Extract data from an image and create a CSV file.
Convert a CSV file to an Excel spreadsheet.
Convert an Excel spreadsheet to a CSV file.
Convert a CSV file to a vCard file.
Convert a vCard file to a CSV file.
Convert CSV to a LaTeX table.
Generate SQL insert queries from a CSV file.
Create a CSV file from SQL query results.
Convert a CSV file to a qCSV (quoted CSV) file.
Convert a qCSV (quoted CSV) file to a CSV file.
Convert a CSV file to an INI file.
Convert an INI file to a CSV file.
Convert a CSV file to a JSONL (JSON Lines) file.
Convert a JSONL (JSON Lines) file to a CSV file.
Convert a CSV file to a plain text file.
Convert a plain text file to a CSV file.
Convert a CSV file to a null-separated values file (0SV).
Convert a null-separated values file (0SV) to a CSV file.
Convert a CSV file to a semicolon-separated file (SSV).
Convert a semicolon-separated file (SSV) to a CSV file.
Convert a CSV file to a hash-separated file (HSV).
Convert a hash-separated file (HSV) to a CSV file.
Convert a CSV file to a pipe-separated file (PSV).
Convert a pipe-separated file (PSV) to a CSV file.
Create an SQLite database from the given CSV file.
Export tables from an SQLite database as CSV files.
Convert a CSV file to a GeoJSON file.
Convert a GeoJSON file to a CSV file.
Merge together two or more CSV files.
Visually show the differences between two CSV files.
Run the diff algorithm on two CSV files.
Find CSV cells that contain certain data.
Return data in a CSV file that matches a pattern.
Extract a slice from a CSV file.
Cut a fragment from a CSV file.
Move CSV columns to the left or right.
Move CSV data rows up or down.
Sort the data in one or more CSV rows.
Randomly change the positions of CSV columns.
Randomly change the order of CSV rows.
Randomly change the order of all CSV values.
Change the name of CSV columns.
Generate a random CSV of any size.
Generate a CSV file that contains nothing.
Generate a large CSV file for testing.
Generate a custom CSV file with m rows and n columns.
Remove CSV columns that are completely empty.
Remove CSV rows that are completely empty.
Remove all fields in a CSV file that are empty.
Remove all empty lines in a CSV file.
Delete the comma separator from CSV files.
Delete extra commas around CSV values.
Delete comments (lines starting with # or //) from CSV files.
Delete the column header from a CSV file.
Delete the first line from a CSV file.
Minify a CSV file and remove unnecessary whitespaces.
Reduce the file size of a CSV file.
Change the character encoding of a CSV file to UTF8 or ISO-8859-1.
Add extra spaces between CSV columns.
Convert a CSV file to an m-by-n matrix.
Convert a CSV file to an array of arrays of fields.
Convert an array of arrays of fields to a CSV file.
Create a list from one or more CSV columns.
Create a list from one or more CSV rows.
Create an array from one or more CSV columns.
Create an array from one or more CSV rows.
Find the number of rows and columns of a CSV file.
Find the number of columns in a CSV file.
Find the number of rows in a CSV file.
Find the sum of CSV columns.
Find the sum of CSV rows.
Find the average value of CSV columns.
Find the average value of CSV rows.
Use different colors for CSV data, quotes, and commas.
Animate CSV data by showing column after column.
Automatically fix a broken CSV.
Introduce random errors to a CSV file for fuzz testing.
Hide personal or sensitive information in a CSV file.
Mask data in a CSV file.
Hide a secret message in a CSV.
Encrypt a CSV file and hide information in it.
Decrypt a previously encrypted CSV file and make it readable.
Create a visual drawing that shows the CSV structure.
Create a new CSV file in the browser.
Distort a CSV file by infusing it with Zalgo characters.
Neutralize the chaotic Zalgo and restore CSV integrity.
Preview the contents of a CSV file in an interactive editor.
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We're Browserling — a friendly and fun cross-browser testing company powered by alien technology. At Browserling our mission is to make people's lives easier, so we created this collection of CSV tools. Our tools have the simplest user interface that doesn't require advanced computer skills and they are used by millions of people every month. Our CSV tools are actually powered by our web developer tools that we created over the last couple of years. Check them out!
