Text Statistics Analyzer
Comprehensive text analysis with word count, readability scores, frequency analysis, and detailed statistics
Text Analysis Examples & Use Cases
Blog Post Analysis
Optimize blog posts for readability and engagement.
Target Metrics: - Word count: 800-2,000 words - Reading time: 3-8 minutes - Readability: "Fairly Easy" to "Standard" - Average sentence length: 15-20 words - Paragraphs: 50-100 words each Analysis Results: ✅ Word count: 1,245 words ✅ Reading time: 6 minutes ⚠️ Difficulty: "Fairly Difficult" 💡 Recommendation: Shorter sentencesSocial Media Content
Optimize posts for different platform requirements.
Platform Limits: - Twitter: 280 characters - LinkedIn: 3,000 characters - Facebook: 63,206 characters - Instagram: 2,200 characters Content Analysis: Characters: 145 (within Twitter limit ✅) Words: 28 Hashtags detected: 3 Mentions detected: 1 Engagement prediction: HighExamples
Count repeated words and sentences
Hello world. Hello DevTools!characters: 28
characters without spaces: 25
words: 4
unique words: 3
sentences: 2
paragraphs: 1
lines: 1
most frequent: hello
frequency: {"hello":2,"world":1,"devtools":1}
byte size: 28Punctuation ends the two sentences and is replaced before the lowercased word-frequency count is built.
Detect paragraphs and empty lines
One line
Second line.characters: 22
characters without spaces: 18
words: 4
unique words: 3
sentences: 1
paragraphs: 2
lines: 3
most frequent: line
frequency: {"line":2,"one":1,"second":1}
byte size: 22A blank line creates two paragraphs and three lines, while only the final period creates a sentence boundary.
Inspect UTF-8 text with the ASCII-oriented word parser
Café 😀characters: 7
characters without spaces: 6
words: 1
unique words: 1
sentences: 1
paragraphs: 1
lines: 1
most frequent: caf
frequency: {"caf":1}
byte size: 10JavaScript string length counts the emoji as two UTF-16 code units, UTF-8 requires 10 bytes, and the parser drops the accented é and emoji from word metrics.
About this tool
Text Statistics Analyzer turns pasted or uploaded text into a detailed report covering characters, words, sentences, paragraphs, lines, word frequency, readability, and encoding. It separates counts such as letters, numbers, punctuation, whitespace, and line breaks, then reports structural averages alongside longest, shortest, and most frequent words.
The analyzer estimates reading time at 200 words per minute and uses a vowel-group heuristic to calculate Flesch Reading Ease and a grade-level label. Advanced controls can exclude numeric-only tokens or common English words and can require a minimum word length. Results can be copied as JSON or downloaded with the selected options and analysis timestamp.
Analysis runs in the browser. The word parser lowercases text and replaces non-word punctuation before counting, so its results follow JavaScript's ASCII-oriented \w behavior rather than a language-aware tokenizer; accented letters and many non-Latin scripts may therefore be split or omitted from word metrics even though their characters and UTF-8 byte size are still counted.
How to use
Enter or upload text
Paste text into the editor, load one of the four samples, or upload a .txt, .md, or .csv file.
Choose analysis options
Open Analysis Options to include or exclude numeric-only tokens, remove common English words, or set a minimum word length from one to four characters.
Analyze the text
Click Analyze Text, then use Overview for headline counts and readability, Frequency for repeated words, and Detailed for line, paragraph, encoding, and ratio data.
Export the report
Copy the statistics as formatted JSON or download a JSON file containing the statistics, options, timestamp, and a preview of the input.
Use cases
Review technical documentation
Check README or API documentation length, paragraph structure, repeated terminology, estimated reading time, and readability before publishing.
Audit editorial copy
Compare word count, sentence length, vocabulary repetition, and reading difficulty across an article, email, or product page.
Inspect text-file structure
Upload a .txt, .md, or .csv file to spot unexpected blank lines, line breaks, Unicode content, emoji, or byte-size growth.
Prepare machine-readable metrics
Copy or download the JSON report to attach reproducible text measurements to a review or content workflow.
Common mistakes
Mistake:Treating the word count as language-aware for accented or non-Latin text.
Fix:The parser uses JavaScript \w and is primarily ASCII-oriented. Use the character and byte metrics as shown, but verify word counts with a locale-aware tokenizer for multilingual text.
Mistake:Assuming the case-sensitive switch changes frequency results.
Fix:The current analyzer lowercases text before tokenization regardless of that switch, so Hello and hello are grouped together.
Mistake:Reading the Flesch score as an exact linguistic assessment.
Fix:Treat it as an estimate: syllables are inferred with a simple English heuristic, and short or specialized text can produce misleading scores.
Mistake:Expecting uploaded formatting or the full source text in the download.
Fix:Files are read as plain text, and the exported input preview is capped at 200 characters; retain the original file separately.
Frequently asked questions
Related guides
References & standards
Related tools
Binary Text Translator
Convert text to binary or hex bytes and decode it back
Case Converter & Text Formatter
Convert text between 14 different case formats including camelCase, snake_case, kebab-case with batch processing and advanced options
Character Frequency Analyzer
Count character, letter and word frequencies for text analysis
Find and Replace Text
Find and replace text with optional regex, case, and multiline matching
HTML to Markdown Converter
Paste HTML and get clean Markdown. Configurable heading style, bullet marker, and code block style — all processed locally in your browser.
Markdown Linter
Check Markdown for common style problems — skipped heading levels, trailing whitespace, hard tabs, missing space after #, trailing heading punctuation, long lines, and stacked blank lines