# Frequency Distribution Generator

Generate frequency distribution tables for data with support for numeric grouping, custom ranges, percentage statistics, and more. Perfect for data analysis, statistical reports, and data visualization preparation.

> Canonical page: https://elysiatools.com/en/tools/frequency-distribution-generator

- **Category:** Data Analysis

- **Keywords:** frequency, distribution, statistics, histogram, bins, data analysis, count, percentage

## Overview

The Frequency Distribution Generator allows you to quickly organize raw datasets into structured frequency tables, enabling deeper statistical insights and easier data visualization preparation.

## Inputs

- **Data Input** (textarea): Enter your CSV data (first row should contain headers)...
- **CSV Delimiter** (select)
- **Group By Column** (text): Enter column name to group by (leave empty for all data)
- **Bin Type** (select)
- **Number of Bins** (number): Enter number of bins (1-100)
- **Bin Width** (number): Enter bin width (integer)
- **Custom Bin Ranges** (textarea): Format: "min-max" or "value" for single value bins
- **Output Format** (select)
- **Include Percentages** (checkbox): Show percentage of total for each category
- **Include Cumulative Totals** (checkbox): Show cumulative frequency distribution
- **Sort By** (select)
- **Sort Direction** (select)
- **Trim Cell Values** (checkbox): Remove whitespace from beginning and end of cell values
- **Include Empty Values** (checkbox): Include empty cells in frequency count

## When to use

- When you need to summarize large datasets into meaningful numeric groups or bins.
- When preparing data for histograms or statistical reporting to identify trends and patterns.
- When you need to calculate percentage distributions or cumulative totals from raw CSV data.

## How it works

- Paste your raw CSV data into the input area and select the appropriate delimiter.
- Choose a binning method such as automatic detection, fixed width, or custom ranges to define your data groups.
- Configure additional settings like percentage inclusion, sorting preferences, and cumulative totals.
- Generate your frequency table in your preferred output format, including Markdown, JSON, or a formatted table.

## Use cases

- Summarizing customer age demographics into specific age brackets for marketing reports.
- Analyzing test score distributions by grouping numeric results into fixed-width grade ranges.
- Converting raw transaction logs into frequency counts to identify high-volume product categories.

## Frequently asked questions

### What input formats are supported?

The tool accepts raw CSV data. You can specify the delimiter used in your data, such as commas, tabs, pipes, or spaces.

### Can I define my own bin ranges?

Yes, by selecting the 'Custom Ranges' bin type, you can manually define specific intervals (e.g., '0-10', '10-20') to group your data exactly as needed.

### Does the tool calculate percentages?

Yes, you can enable the 'Include Percentages' checkbox to automatically calculate the percentage of the total for each category.

### How do I handle empty cells in my data?

The tool includes an 'Include Empty Values' option, which allows you to decide whether to count empty cells as a separate category in your distribution.

### What output formats are available?

You can export your results as a formatted table, Markdown table, JSON array, or raw CSV format.

## Related tools

- [Data Boundary Processor](https://elysiatools.com/en/tools/data-boundary-processor): Advanced boundary value processing tool that identifies and handles minimum/maximum values in numerical data. Perfect for data validation, range checking, statistical analysis, and data preprocessing. Features: - Multiple boundary detection methods (absolute, percentile, standard deviation) - Flexible handling strategies (clip, remove, replace, transform) - Custom range validation - Asymmetric boundary handling - Batch processing capabilities - Comprehensive boundary statistics - Data quality assessment - Visual boundary reports Common Use Cases: - Data validation and quality control - Sensor data range checking - Financial data limit enforcement - Statistical data preprocessing - Machine learning feature engineering - Database constraint validation
- [Data Deduplicator](https://elysiatools.com/en/tools/data-deduplicator): Remove duplicate rows from CSV files based on multiple column combinations. Perfect for cleaning customer lists, survey responses, and database exports. Features: - Multi-column combination deduplication - Fuzzy matching for similar records - Custom deduplication strategies (keep first, last, or most complete record) - Case-insensitive matching option - Whitespace trimming - Detailed duplicate statistics Common Use Cases: - Remove duplicate customer records - Clean email marketing lists - Eliminate redundant survey responses - Prepare data for analysis
- [Data Outlier Processor](https://elysiatools.com/en/tools/data-outlier-processor): Advanced outlier detection and processing tool that identifies, removes, or replaces anomalous values in numerical data using multiple statistical methods. Perfect for data cleaning, statistical analysis, and machine learning data preparation. Features: - Multiple detection methods (IQR, Z-score, Modified Z-score, Isolation Forest) - Flexible handling strategies (Remove, Replace with mean/median/mode, Cap) - Automatic threshold optimization - Multi-dimensional outlier detection - Visual outlier statistics and reporting - Batch processing capabilities - Custom sensitivity levels - Comprehensive impact analysis Common Use Cases: - Data cleaning and preprocessing - Statistical analysis preparation - Machine learning dataset cleaning - Quality control in manufacturing - Financial anomaly detection - Sensor data validation
- [Z-Score Standardizer](https://elysiatools.com/en/tools/data-zscore-normalizer): Standardize numerical data using Z-score (standard score) normalization to transform values with mean=0 and standard deviation=1. Perfect for statistical analysis, machine learning feature preprocessing, outlier detection, and data comparison across different scales. Features: - Z-score standardization (mean=0, std=1) - Robust Z-score option (using median and MAD) - Custom scaling to target range - Multiple column selection - Automatic data type detection - Handles missing values intelligently - Preserves non-numeric columns - Comprehensive statistical summary - Outlier detection and reporting Common Use Cases: - Machine learning feature preparation - Statistical hypothesis testing - Outlier detection and removal - Data comparison across different units - Principal Component Analysis (PCA) preprocessing
- [CSV Data Grouper](https://elysiatools.com/en/tools/csv-data-grouper): Group CSV data by specified columns with aggregation options. Perfect for summarizing and analyzing large datasets by categories, dates, or other criteria.
- [Data Range Limiter](https://elysiatools.com/en/tools/data-range-limiter): Limit numerical values to specified ranges by clipping, filtering, or marking out-of-bounds values. Perfect for data quality control, sensor data cleaning, business rule enforcement, and data preprocessing. Features: - Range clipping (clip values to min/max boundaries) - Range filtering (remove out-of-bounds rows) - Range marking (flag modified values) - Per-column range configuration - Automatic numeric column detection - Multiple handling strategies - Detailed modification reports - Statistical analysis of changes - Business rule enforcement Common Use Cases: - Sensor data validation and cleaning - Machine learning input preparation - Data quality control and validation - Business constraint enforcement - Outlier management and control - Data preprocessing pipelines
- [Duplicate Column Remover](https://elysiatools.com/en/tools/duplicate-column-remover): Remove duplicate columns from CSV data with flexible detection strategies. Perfect for cleaning datasets, removing redundant information, and optimizing data structure. Features: - Detect columns with identical headers - Find columns with identical data content - Support for case-sensitive/insensitive matching - Multiple removal strategies available - Preserve data integrity - Support for large datasets - Fast and efficient processing Common Use Cases: - Clean up merged datasets - Remove redundant data columns - Optimize data for analysis - Prepare data for machine learning - Reduce file size and complexity - Standardize data format
- [Data Crosstab Generator](https://elysiatools.com/en/tools/data-crosstab-generator): Advanced crosstab (pivot table) generator that creates powerful cross-tabulation analysis from your data. Perfect for business intelligence, statistical analysis, data exploration, and reporting. Features: - Multiple aggregation functions (sum, count, average, min, max, median) - Flexible row and column grouping - Percentage and ratio calculations - Row/column totals and grand totals - Multi-dimensional analysis - Conditional formatting support - Statistical significance testing - Custom sorting and filtering - Export-ready formatting Common Use Cases: - Sales analysis by region and product - Customer demographics analysis - Financial statement analysis - Survey response analysis - Inventory turnover analysis - Performance metrics tracking

## Samples

- [CSV Samples](https://elysiatools.com/en/samples/csv-samples): Sample CSV files with various data types, sizes, and complexity levels
- [Windows String Processing - C# Samples](https://elysiatools.com/en/samples/windows-string-processing-csharp): Comprehensive C# string processing examples for Windows platform including string manipulation, splitting, joining, regex operations, and text analysis
- [Python Samples](https://elysiatools.com/en/samples/python): Essential Python code examples and Hello World demonstrations
- [WebRTC Real-Time Communication Samples](https://elysiatools.com/en/samples/webrtc-samples): Comprehensive WebRTC samples for peer-to-peer audio/video communication, data channels, screen sharing, and signaling server implementation
