Frequency Distribution Calculator
A frequency distribution table organises raw data by listing each unique value and showing how many times it appears. It is one of the first steps in any exploratory data analysis because it immediately reveals which values are common, which are rare, and whether the data cluster around a single peak or spread across multiple values. Relative frequency expresses each count as a percentage of the total number of observations, which makes it easy to compare the shape of different data sets regardless of their size. Cumulative frequency shows the running total of observations up to and including each value, and cumulative percentage shows what proportion of the data falls at or below each value. Cumulative frequency is the starting point for estimating percentiles and building ogive charts. This calculator takes a comma-separated list of numbers, finds each unique value, counts how many times each appears, and assembles the full frequency distribution table sorted in ascending order of value. The hero output is the number of unique values (the number of distinct categories in the data), alongside the total observation count and the most frequent value. The full table below the result card shows all four columns: value, count, relative frequency percentage, and cumulative percentage. The tool handles repeated decimals and negative numbers, and sorts data automatically. It suits students building statistics tables for assignments, teachers preparing class demonstrations, researchers summarising survey responses, and data analysts exploring raw count data before applying further analysis.
How it works
The calculator parses the input list, sorts the values numerically, and builds a map of each unique value to its count. Relative frequency for each value is count divided by total times 100. Cumulative count is a running sum of counts from the smallest value upward. Cumulative percentage is cumulative count divided by total times 100. The mode is the value with the highest count; in the case of a tie, the smallest tied value is reported first. The table rows are sorted in ascending order of value.
Worked example
Data: 2, 3, 3, 4, 4, 4, 5, 5, 6 (n = 9). Unique values: 2 (count 1, 11.11%), 3 (count 2, 22.22%), 4 (count 3, 33.33%), 5 (count 2, 22.22%), 6 (count 1, 11.11%). Number of unique values = 5. Mode = 4 (appears 3 times). Cumulative % at 4 = (1+2+3)/9 x 100 = 66.67%. These match the default values pre-filled above.
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