Continuous Data

Continuous data is numeric data that can take any value along a measurable continuum, where the gaps between values are real and meaningful.

Unlike labels, continuous values are quantities you measure: height, temperature, time, weight, price. Between any two of them lies another possible value — between 1.5 and 1.6 metres sits 1.55. Because the numbers live on a true scale, arithmetic on them is meaningful: you can average them, subtract them, and say one is exactly twice another.

How continuous data appears in a chart

Continuous data is plotted on a numeric axis where position carries quantitative meaning and the scale sets the spacing. It suits line charts (values changing over a continuous variable like time) and scatter plots (two continuous variables at once). Because individual continuous values can be infinitely varied, they are often grouped into ranges before charting so patterns in their distribution become visible.

A concrete example

Suppose you record the heights of 100 people, ranging from 150 cm to 190 cm. Each reading is continuous — 167.3 cm is just as valid as 167. To chart the spread you group the values into ranges such as 150–160, 160–170, 170–180 and 180–190, then count how many fall in each. If those counts are 18, 42, 32 and 8 they sum to 100, and a histogram of the four ranges reveals where heights cluster. That grouping step is what turns raw continuous numbers into a readable shape.

Related terms

Continuous data contrasts with categorical data, which is distinct groups rather than measurable numbers. The ranges it is grouped into are called bins. To chart a continuous variable's distribution, see the histogram guide; for category counts, the bar chart guide.