Any text — articles, code, essays, books, logs...
Ready to analyze
Paste text and click Analyze Frequency// analyze word frequency from any text input
Generate a sorted word frequency table from any text. Count word occurrences, find most used words, and export results as CSV instantly in your browser.
Ready to analyze
Paste text and click Analyze FrequencyCopy any text — articles, essays, code comments, logs, or entire documents — and paste into the input field.
Toggle stopword exclusion, case sensitivity, and choose how many top words to display in results.
Click Analyze to generate a sorted frequency table. Sort by count, alphabet, or length. Export as CSV anytime.
The Word Frequency Counter scans any text and counts how many times each word appears, then displays results in a sortable table with percentage scores and visual bars. All processing happens in your browser — no data is sent to any server.
Stopwords are common English words like "the", "a", "is", "in", "and" that appear very frequently but carry little meaningful information. For most analysis — writing style, SEO, topic identification — it's better to exclude them so meaningful keywords stand out.
By default, analysis is case-insensitive, so "Word", "word", and "WORD" are counted as the same word. Enable the Case-sensitive option if you need to differentiate between capitalized and lowercase variants — useful for code analysis.
The percentage shown for each word is its count divided by the total number of analyzed words (after filtering), multiplied by 100. It represents how much of your text consists of that specific word.
The CSV export includes three columns: Word, Count, and Percentage. The file is UTF-8 encoded and compatible with Excel, Google Sheets, and any standard spreadsheet application. Rows are ordered by current sort selection.
No. All text analysis runs entirely in your browser using JavaScript. Your text never leaves your device and is never stored, logged, or transmitted anywhere. This makes the tool safe for analyzing confidential documents.
There is no hard limit. The tool handles very large texts — even entire books — though processing time increases with length. For texts over 500,000 words, you may notice a brief delay of a second or two before results appear.
A word frequency counter is a text analysis tool that reads a body of text and tallies how many times each unique word appears. The result is a frequency table — a ranked list showing every word alongside its occurrence count and percentage share of the total word pool. This simple but powerful analysis reveals patterns invisible to the naked eye: which concepts dominate a piece of writing, whether certain words are overused, and how a text's vocabulary distribution compares to expectations.
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Word frequency analysis has applications across many fields. In content writing and SEO, it helps writers understand keyword density — ensuring important terms appear often enough to be relevant without crossing into keyword stuffing territory. Search engines use sophisticated versions of frequency analysis when evaluating content relevance.
In academic and literary research, frequency tables are foundational tools for stylometrics — the statistical analysis of writing style. Researchers use them to study authorship attribution, track how an author's vocabulary evolved over time, or compare two versions of a manuscript. Linguists use frequency data to understand how language is actually used versus how it's taught.
For developers and data engineers, frequency analysis is useful for understanding log files, tokenizing text datasets for machine learning, and debugging repetitive patterns in generated output. When building NLP pipelines, word frequency is often one of the first preprocessing steps.
Our tool presents results in a structured table with five columns:
You can re-sort the table by frequency (default), alphabetically, or by word length — each sort reveals different aspects of the text's structure.
In any natural language text, a small set of function words — called stopwords — dominate by sheer frequency. Words like "the", "of", "and", "a", "to", "in" are grammatically essential but semantically empty. If you're trying to understand what a text is about, these words create noise.
Our stopword filter removes the 100+ most common English function words, leaving only content words with meaningful semantic weight. This is enabled by default and is the recommended setting for most use cases. Toggle it off if you need a complete unfiltered frequency count — for example, when analyzing writing style, where function word ratios are actually informative.
One of the most striking patterns in word frequency analysis is how predictable it is. In virtually any large corpus of natural language, the most common word appears roughly twice as often as the second most common word, three times as often as the third, and so on. This inverse relationship between rank and frequency is known as Zipf's Law, and it holds with remarkable consistency across languages, genres, and time periods.
When you analyze your own texts with our tool, you'll often see this pattern emerge — a few words dominating with high counts, then a long tail of words that appear only once or twice. This "power law" distribution is a universal signature of human language.
After analyzing your text, you can export the frequency table as a CSV file. This comma-separated format is universally compatible with Excel, Google Sheets, LibreOffice Calc, and any data processing tool. The exported CSV includes the word, count, and percentage for every word in the current sorted view — making it easy to import into further analysis pipelines or share with collaborators.
The Copy CSV button copies the same data to your clipboard, which is useful for pasting directly into a spreadsheet or another tool without creating a file.
Because word frequency analysis runs entirely in your browser using JavaScript, none of your text ever leaves your device. This makes it completely safe to analyze confidential documents, proprietary content, or sensitive personal writing. There are no accounts, no uploads, no data retention — just instant client-side processing.