All Tools Directory

Browse all 169 browser-based data conversion and cleaning utilities. Your rows never leave your browser.

Convert #1

CSV to JSON

Transform tabular CSV spreadsheets into structured JSON arrays of objects in your browser.

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Convert #2

JSON to CSV

Transform complex JSON arrays and nested API responses into clean, spreadsheet-ready CSV tables.

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Convert #3

CSV to TSV

Convert CSV data into tab-delimited values (TSV) for seamless copy-pasting directly into Excel, Sheets, and bioinformatics tools.

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Convert #4

TSV to CSV

Convert tab-separated datasets (TSV) into standardized comma-separated (CSV) spreadsheets compatible with all platforms.

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Convert #5

TSV to JSON

Transform tab-delimited records (TSV) into structured JSON arrays of objects for web APIs and NoSQL databases.

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Convert #6

JSON to TSV

Convert JSON documents and API arrays into tab-delimited values (TSV) for seamless copy-pasting directly into spreadsheet cells.

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Convert #7

CSV to Markdown Table

Transform CSV files and spreadsheets into clean, padded GitHub-Flavored Markdown tables for documentation and READMEs.

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Convert #8

JSON to Markdown Table

Transform JSON API payloads and data objects into clean, formatted Markdown tables for technical documentation and READMEs.

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Convert #9

CSV to SQL INSERT

Transform spreadsheet rows into clean, batched SQL INSERT statements with proper string escaping and NULL detection.

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Convert #10

JSON to SQL INSERT

Transform JSON API payloads and arrays of objects into structured SQL INSERT statements ready for database migration.

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Convert #11

CSV to TypeScript Interface

Generate strongly-typed TypeScript interfaces, types, and JSDoc comments directly from CSV column headers and sample data rows.

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Convert #12

JSON to TypeScript Interface

Convert JSON payloads and API responses into strongly-typed TypeScript interfaces with recursive sub-type generation.

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Convert #13

Excel to CSV

Convert Excel workbooks (.xlsx, .xls) into clean, standard CSV files with date repair and multi-sheet selection.

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Convert #14

CSV to Excel

Transform CSV files into native Excel workbooks (.xlsx) with preserved leading zeros and styled header rows.

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Convert #15

Excel to JSON

Transform Microsoft Excel workbooks (.xlsx, .xls) directly into clean, structured JSON arrays and objects.

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Convert #16

JSON to Excel

Transform complex JSON documents and API responses into styled, auto-fitted Microsoft Excel workbooks (.xlsx).

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Convert #17

CSV to JSON for Postman

Format CSV test cases and parameters into Postman collection runner JSON data files for automated API testing.

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Convert #18

CSV to JSON Lines

Transform CSV spreadsheets into newline-delimited JSON Lines (JSONL / NDJSON) for BigQuery, Elasticsearch, and AI training datasets.

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Convert #19

JSON Lines to CSV

Transform newline-delimited JSON Lines (JSONL / NDJSON) log files and datasets into clean, tabular CSV spreadsheets.

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Clean #25

Split Full Name into First and Last

Separate full name columns into dedicated first_name and last_name columns in CSV and Excel spreadsheets.

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Clean #26

Combine First and Last Name

Merge separate first and last name columns into a single clean full_name column, trimming extra spaces.

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Clean #27

Remove Duplicate Rows

Eliminate duplicate rows across your entire dataset or based on specific unique key columns.

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Clean #28

Fix Phone Numbers

Strip punctuation, resolve leading zeros, and format phone numbers with proper country codes.

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Clean #29

Phone Numbers to E.164

Standardize phone numbers into strict E.164 format (+) without spaces or symbols for SMS and CRM APIs.

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Clean #30

Trim Whitespace

Clean up accidental leading, trailing, and duplicate spaces across all columns in your spreadsheet.

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Clean #31

Change Text Case

Transform column text into UPPERCASE, lowercase, Title Case, Sentence case, or camelCase across your spreadsheet.

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Clean #32

Remove Empty Rows

Delete blank lines and rows containing only empty cells or whitespace across your entire spreadsheet.

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Clean #33

Remove Empty Columns

Detect and remove completely blank columns or columns containing only empty values across your dataset.

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Clean #34

Standardize Dates to ISO

Transform mixed and regional date formats into standardized ISO 8601 strings (YYYY-MM-DD).

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Clean #35

Fix Mixed Date Formats

Harmonize columns containing a mixture of slashes, dashes, text months, and timestamps into one uniform format.

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Clean #36

Remove Special Characters

Strip invisible control characters, non-ASCII symbols, smart quotes, and unwanted punctuation from spreadsheet cells.

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Clean #37

Merge Columns

Concatenate multiple columns into a single unified column using custom delimiters (space, comma, hyphen, slash).

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Clean #38

Split a Column by Delimiter

Divide single cell values into multiple new columns based on delimiters like commas, slashes, hyphens, or spaces.

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Clean #39

Extract Domain from Email

Parse email addresses to extract website domain names into a dedicated column for lead enrichment and corporate classification.

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Clean #40

Clean an Email List

Scrub email lists by fixing syntax errors, trimming spaces, removing duplicates, and lowercasing addresses.

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Clean #41

Fix Currency and Number Formats

Strip currency symbols ($ , € , £ , KES), resolve thousands commas, and format numbers into clean numeric decimals.

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Clean #42

Fix a Messy CSV Export

Diagnose and repair common CSV corruptions: unclosed quotes, broken delimiters, jagged row lengths, and encoding glitches.

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Clean #43

Remove Duplicate Emails

Deduplicate subscriber and customer lists based exclusively on normalized email addresses.

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Clean #44

Fix Name Capitalization

Transform SHOUTING all-caps or all-lowercase names into natural Title Case with cultural naming rule support.

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Clean #45

Add or Remove Leading Zeros

Pad numbers with leading zeros to meet fixed-width requirements (e.g. 00123) or strip unnecessary leading zeros.

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Clean #46

Fix ZIP and Postal Codes

Repair postal codes damaged by Excel auto-truncation, format US ZIP+4, and standardize UK and Canadian formats.

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Clean #47

Standardize Country Names and Codes

Convert inconsistent country names ("USA", "US", "United States") to standardized ISO 3166-1 alpha-2, alpha-3, or full country names.

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Clean #48

Standardize State Abbreviations

Convert US, Canadian, and Australian state names to official 2-letter postal codes (e.g. CA, NY) or expand codes to full names.

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Clean #49

Remove HTML Tags from Cells

Strip HTML markup tags and decode HTML entities from product descriptions, CMS exports, and scraped text.

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Clean #50

Remove Line Breaks Inside Cells

Remove internal carriage returns and newline characters inside cells that cause broken CSV rows and database parsing errors.

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Clean #51

Fix Garbled Characters (Encoding)

Repair character encoding glitches (mojibake) caused by Windows-1252 or ISO-8859-1 interpreted as UTF-8 (e.g. é -> é, ’ -> ').

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Clean #52

Remove Emojis from Text

Remove emojis, pictographs, and Unicode symbols from social media text, customer reviews, and feedback.

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Clean #53

Standardize Yes/No Values

Normalize inconsistent boolean flags across your dataset into standard True/False, Yes/No, or 1/0 formats.

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Format #54

JSON Formatter

Beautify and indent unformatted JSON strings into clean, human-readable structured trees.

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Format #55

JSON Minifier

Compress structured JSON files into single-line minified strings to reduce payload size.

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Format #56

Change CSV Delimiter

Switch spreadsheet delimiters between commas, semicolons, tabs, and pipes seamlessly.

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Format #57

Add a Header Row to CSV

Insert column headers to raw CSV files that lack a top header row.

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Format #58

Remove the Header Row

Remove the top header row or metadata lines from a CSV dataset.

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Format #59

Sort CSV by Column

Sort tabular CSV records ascending or descending by any column value.

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Format #60

Reorder CSV Columns

Change the horizontal sequence of columns in a CSV file.

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Format #61

Rename CSV Columns

Rename column headers or standardize them into snake_case / camelCase.

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Format #62

Escape Quotes in CSV

Escape internal quotation marks to prevent broken rows in standard parsers.

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Format #63

Wrap CSV Values in Quotes

Wrap all cells or specific text columns in quotation marks.

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Validate #64

Validate CSV

Audit CSV files for structural errors, encoding problems, and row-length inconsistencies.

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Validate #65

Validate JSON

Parse and validate JSON strings to expose syntax errors at exact line and column positions.

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Validate #66

Find Duplicate Rows

Identify and count duplicate rows in CSV files by exact match or by key column selection.

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Validate #67

Find Missing Values

Audit CSV columns for empty, null, and whitespace-only cells and produce a completeness report.

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Validate #68

Validate an Email List

Check every email in a CSV column for valid RFC 5322 format without sending test messages.

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Validate #69

Validate Phone Numbers

Scan a CSV phone column for format errors, missing country codes, and invalid digit counts.

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Validate #70

Check Column Consistency

Audit CSV columns to detect mixed data types, inconsistent formats, and type anomalies.

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Validate #71

Find Invalid Dates

Scan date columns for invalid entries: impossible dates, ambiguous formats, and future or past-range anomalies.

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Validate #72

Find Outliers in a Number Column

Identify statistical outliers in numeric columns using IQR or Z-score threshold methods.

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Validate #74

CSV Row and Column Counter

Count data rows, header columns, total cells, and non-empty cell percentages in any CSV.

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Validate #75

Profile a CSV

Automatically profile every CSV column: type inference, null rate, unique count, min/max, mean, and top-5 values.

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Reshape #81

Transpose CSV

Flip a CSV matrix by turning rows into columns and columns into rows.

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Reshape #82

Pivot a CSV

Summarise long-format CSV data into pivot tables grouped by row and column keys.

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Reshape #83

Group By and Count

Aggregate CSV rows by one or more group-by columns with count, sum, mean, min, or max.

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Reshape #84

Filter CSV Rows by Condition

Keep or discard CSV rows based on flexible conditions applied to any column.

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Reshape #85

Select or Remove Columns

Select columns to keep or specify columns to drop from a CSV, with optional reordering.

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Reshape #86

Add a Calculated Column

Create new columns derived from existing columns using arithmetic, string, or conditional expressions.

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Reshape #87

Pick Random Sample Rows

Extract a reproducible random sample of rows from large CSV datasets.

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Reshape #88

Keep the First or Last N Rows

Extract the first N or last N data rows from a CSV file, preserving the header.

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Reshape #89

Add Row Numbers or Unique IDs

Add sequential row numbers or UUID/ULID unique identifiers to every row in a CSV.

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Platform #90

Shopify Customer Export Cleaner

Normalize Shopify customer exports: merge split address fields, clean phones, and strip internal metadata.

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Platform #91

Stripe CSV to JSON

Convert Stripe balance and payment CSV exports to clean JSON with amount conversion and metadata parsing.

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Platform #92

Google Contacts CSV Fixer

Fix Google Contacts CSV exports to import into Outlook, Apple Contacts, or CRM platforms.

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Platform #93

Mailchimp List Cleanup

Clean Mailchimp subscriber exports: remove unsubscribes, deduplicate, fix emails, and strip metadata.

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Platform #94

WooCommerce Order Export Cleaner

Clean WooCommerce order CSV exports: fix address fields, strip HTML entities, and normalise totals.

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Platform #95

Fix Excel Exports with Merged Cells

Fill down blank cells in CSV exports caused by merged cell regions in Excel workbooks.

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Platform #96

LinkedIn Connections Export Cleaner

Clean LinkedIn connections CSV: strip header notice, split company/position, validate emails, normalize dates.

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Platform #98

Google Ads Report Cleaner

Clean Google Ads CSV exports: strip summary rows, convert percentages/currency to numbers, normalise column names.

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Platform #99

Bank Statement CSV Cleaner

Standardize bank statement CSVs: detect debit/credit, normalize dates, strip metadata rows.

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Platform #100

Accounting Export Cleaner

Normalize QuickBooks, Xero, Wave, and FreshBooks CSV exports for data analysis.

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Transform #101

Column to Comma-Separated List

Extract a CSV column and convert it to a comma-separated list for SQL IN clauses or code arrays.

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Transform #102

Comma-Separated List to Column

Convert a comma-separated, line-separated, or SQL IN list into a single-column CSV.

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Transform #103

Lines to CSV

Convert plain-text newline-delimited records into structured CSV tables.

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Transform #104

CSV to Lines

Convert a CSV to a newline-delimited text file with configurable field separators.

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Clean #105

Find and Replace in CSV

Replace text values across all cells or within specific columns in a CSV file.

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Clean #106

Regex Replace in CSV

Apply regex patterns with capture groups to transform cell values across CSV columns.

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Transform #107

Add Prefix or Suffix to Values

Prepend a prefix or append a suffix to every value in a CSV column.

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Clean #108

Truncate Text in Cells

Trim CSV cell values to a specified maximum character length with optional ellipsis.

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Analyze #109

Count Word Frequency

Count word frequency across a text column in a CSV and output a frequency table.

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Analyze #110

Count Unique Values

Count distinct values per CSV column and generate a value-count frequency table for each.

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Analyze #111

Top N Values in a Column

Extract the top N or bottom N rows from a CSV ranked by a numeric column.

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Clean #112

Fill Down Blank Cells

Forward-fill blank cells by propagating the last non-blank value down through a CSV column.

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Clean #113

Fill Missing Values

Replace blank CSV cells with a constant, column mean, median, previous value, or 'Unknown'.

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Clean #114

Convert Text to Numbers

Strip formatting from text-formatted number columns to produce clean numeric values.

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Transform #115

Convert Numbers to Text

Format numeric CSV values as human-readable text with currency symbols, commas, and decimal precision.

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Transform #116

Round Numbers in a Column

Round numeric CSV column values to a specified decimal precision or nearest integer/multiple.

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Transform #117

Add Thousands Separators

Add thousands separators (comma or period) to numeric CSV columns for display formatting.

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Transform #118

Convert Percentages

Convert percentage strings to decimal fractions or decimal fractions to percentage strings in CSV columns.

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Analyze #119

Rank Rows

Rank CSV rows by a numeric column and add a rank column with configurable tie-breaking.

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Analyze #120

Running Total

Add a running (cumulative) total column to a numeric CSV column, with optional group reset.

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Analyze #121

Percent of Total

Add a percentage-of-total column showing each row's share of the column sum.

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Transform #122

Normalize Numbers (Min-Max)

Scale numeric CSV column values to the 0–1 range using min-max normalization.

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Reshape #123

Unpivot (Wide to Long)

Convert wide-format pivot tables to long format by stacking multiple columns into variable/value pairs.

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Reshape #124

Pivot (Long to Wide)

Convert long-format (tidy) CSV to wide pivot format by spreading a variable column into column headers.

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Transform #125

CSV to Key-Value Pairs

Convert CSV rows to key=value or key:value pair strings for config files, ENV files, or logs.

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Transform #126

CSV to Vertical Records

Convert CSV rows into vertical field:value blocks, one block per row, for human-readable review.

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Transform #127

CSV to Mail-Merge Output

Fill a text template with {{field_name}} placeholders from each CSV row to generate personalized output.

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Extract #128

Extract Emails, Phones or URLs from a Column

Extract email addresses, phone numbers, or URLs embedded in free-text CSV cells into separate columns.

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Clean #129

Clean URLs (Remove Tracking Parameters)

Strip UTM parameters, fbclid, gclid, and marketing tracking tokens from CSV URL columns.

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Extract #130

Extract Domain from URL

Extract the root domain, subdomain, path, or protocol from full URL strings in a CSV column.

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Clean #131

Split an Address into Parts

Split unformatted postal addresses into clean structured address columns.

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Clean #132

Normalize Company Names

Harmonize company name variations, legal suffixes, and capitalization across your account list.

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Validate #133

Find Similar Duplicates (Fuzzy Match)

Identify subtle duplicates and typos in your CSV using configurable fuzzy matching algorithms.

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Clean #134

Parse Names with Titles and Suffixes

Extract professional titles (Dr., Rev.) and suffixes (Jr., III, Ph.D.) into distinct columns.

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Validate #135

Detect and Fix Delimiter Problems

Scan for ragged rows where unescaped commas or semicolons broke table alignment.

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Validate #136

Fix Unclosed Quotes

Detect mismatched quotes that cause entire rows of data to be swallowed into a single cell.

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Clean #137

Remove the Byte-Order Mark (BOM)

Remove the hidden 3-byte BOM sequence that breaks database imports and pandas scripts.

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Transform #138

Convert Encoding to UTF-8

Fix mangled accented characters (mojibake) by decoding legacy encodings into clean UTF-8.

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Transform #139

Convert Line Endings

Switch between Windows CRLF and Linux LF line breaks across your files.

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Reshape #140

Remove Columns by Name Pattern

Delete batches of columns matching regex or text patterns from wide exports.

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Reshape #141

Keep Columns by Name Pattern

Extract a focused subset of columns matching a name pattern from massive wide tables.

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Transform #142

Convert Time Zones in a Column

Shift timestamps between UTC and local regional time zones with full daylight saving support.

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Transform #143

Date to Weekday

Derive day-of-week names or numeric values from date columns for cohort analytics.

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Transform #144

Calculate Age from Date of Birth

Derive current age in full completed years from birthday columns.

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Transform #145

Date Difference Between Two Columns

Calculate elapsed time between two date columns in days, working days, or hours.

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Transform #146

Combine Date and Time Columns

Join isolated date and time fields into single standard timestamp columns.

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Transform #147

Split Date and Time

Separate composite timestamp columns into distinct date and time components.

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Transform #148

Excel Date Serial to Date

Translate cryptic Excel 5-digit serial numbers back into human-readable calendar dates.

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Transform #149

Date to Excel Serial

Convert standard calendar dates into Excel-compatible numeric serial day values.

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Transform #150

Convert Units in a Column

Convert numeric measurements across metric and imperial units (lbs to kg, miles to km).

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Clean #151

Unmerge Cells and Fill

Repair spreadsheets corrupted by merged cells by filling parent values down across all rows.

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Transform #152

Split an Excel File by Sheet

Export all worksheets from a multi-tab workbook into individual CSV tables.

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Reshape #153

Merge Excel Files

Consolidate multiple Excel workbooks into a single master spreadsheet or CSV table.

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Clean #154

Remove Formulas and Keep Values

Freeze calculated spreadsheet formulas into static values and strip formula overhead.

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Transform #155

Excel to Import-Ready CSV for Google Sheets

Format and clean Excel files so they import into Google Sheets without corrupted dates or fonts.

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Transform #156

Flatten Nested JSON

Transform deeply nested JSON objects into flat dot-notated key-value pairs.

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Transform #157

Extract a Field from a JSON Array

Pluck a single attribute (like email or id) across all objects in a JSON array.

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Clean #158

Remove Null Values

Recursively purge null, empty string, and undefined attributes from JSON payloads.

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Transform #159

Rename JSON Keys

Remap property keys across JSON records to align with target API or database schemas.

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Convert #160

JSON Array to CSV with Nested Columns

Export hierarchical JSON arrays into clean CSV tables with flattened dot-notated columns.

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Transform #161

JSON to Table

Render complex JSON payloads as an interactive, searchable spreadsheet grid.

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Validate #162

Compare Two JSON Arrays

Diff two JSON arrays to find added, deleted, and modified records based on a shared key.

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Reshape #163

Merge JSON Files

Combine multiple JSON documents or arrays into a single consolidated JSON file.

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Clean #164

Deduplicate a JSON Array

Remove duplicate records from JSON arrays based on designated key properties or full object equality.

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Transform #165

Sort a JSON Array by Field

Sort JSON objects alphabetically, numerically, or chronologically by any property key.

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Reshape #166

Filter a JSON Array

Filter JSON array records based on conditional criteria, status flags, or numeric thresholds.

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Format #338

Case Converter

Convert text between any capitalisation style: uppercase, lowercase, title case, sentence case, camelCase, PascalCase, snake_case, and kebab-case.

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Clean #339

Remove Duplicate Lines

Remove repeated lines from any text block, with options for case sensitivity and whitespace handling.

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Format #340

Sort Lines Alphabetically

Sort any block of text lines alphabetically, reverse alphabetically, or numerically.

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Clean #345

Remove Empty Lines

Remove all blank and whitespace-only lines from any block of text.

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Clean #346

Remove Extra Spaces

Collapse multiple consecutive spaces into one and strip leading/trailing spaces from any text.

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Format #349

Find and Replace Text

Replace any word, phrase, or regex pattern in any block of text.

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Validate #351

Text Diff Checker

Compare two versions of a text document and highlight additions, deletions, and changes.

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Extract #372

Extract Emails from Text

Extract all email addresses from any block of text or document paste.

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Extract #373

Extract URLs from Text

Extract all URLs and hyperlinks from any block of text or document paste.

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Extract #374

Extract Numbers from Text

Extract all numbers — integers, decimals, and formatted amounts — from any block of text.

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Extract #375

Extract Hashtags

Extract all hashtags from social media posts, captions, or any text block.

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Format #376

Text to URL Slug

Turn any text title into a lowercase, hyphen-separated URL slug safe for web addresses.

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Clean #377

Remove Accents and Diacritics

Strip all diacritical marks from accented characters, converting to plain ASCII equivalents.

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Convert #378

Markdown to HTML

Convert Markdown documents to clean, semantic HTML in your browser.

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Convert #379

HTML to Markdown

Convert HTML documents and fragments into clean, readable Markdown.

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