Text Pattern Stats

Text Pattern Stats | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Text Processing
Input types: textarea, select, text, checkbox, number
Output type: json
Sample coverage: 4
API ready: Yes

Overview

Text Pattern Stats is a utility tool that performs frequency analysis on text to identify and count patterns such as numbers, email addresses, URLs, and more. It helps users extract statistical insights from unstructured text data quickly and accurately.

When to use

When you need to count occurrences of specific patterns like numbers or emails in a large text document.
When analyzing logs, reports, or datasets to find common elements such as phone numbers or dates.
When preparing text data for further processing by extracting structured information based on patterns.

How it works

1Input your text into the text area provided.
2Select a pattern type from the dropdown, such as numbers, emails, or URLs, or choose 'Custom Regex' to define your own.
3Configure optional settings like case sensitivity, show distribution, and maximum results.
4The tool scans the text and returns a JSON output with statistics, including frequency counts and distribution details if enabled.

Use cases

Extracting all email addresses from customer feedback forms for contact list generation.
Counting the number of URLs in web scraping data to analyze link density.
Analyzing a document to find and tally all dates mentioned for timeline or event tracking.

Examples

1. Extracting Numbers from Financial Reports

Financial Analyst

Background

A financial analyst has a text-based report with scattered numerical data on revenues and expenses.

Problem

Need to quickly identify and count all numerical values to summarize financial metrics without manual review.

How to use

Paste the report text into the text input, select 'Numbers' as the pattern type, and set max results to 200.

Outcome

The tool returns a JSON list of all numbers with their frequencies, enabling efficient data aggregation for analysis.

2. Auditing Email Addresses in Server Logs

System Administrator

Background

Server logs contain entries with email addresses from user activities and notifications.

Problem

Need to find all unique email addresses for security auditing and compliance checks.

How to use

Input the log text, choose 'Email Addresses' as the pattern type, and enable case sensitivity if required.

Outcome

A JSON output with all email addresses and their occurrence counts, facilitating quick audit and monitoring.

FAQ

What pattern types are supported?

Numbers, uppercase words, capitalized words, email addresses, URLs, phone numbers, dates, and custom regex patterns.

Can I use my own regex pattern?

Yes, select 'Custom Regex' from the pattern type dropdown and enter your pattern in the custom regex field.

What does the 'Show Distribution' option do?

It includes a frequency distribution chart in the JSON results, showing how often each pattern appears in the text.

Is there a limit to the text length or number of results?

The tool can handle large texts, but you can set a maximum number of results (10 to 500) to control output size and performance.

How are the results formatted?

Results are returned in JSON format, detailing each pattern found, its count, and distribution if enabled.

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Inputs

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Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Extracting Numbers from Financial Reports

2. Auditing Email Addresses in Server Logs

FAQ

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