Would transaction times be considered discrete quantitative variables, despite being of dtype float?

[thngimajigger]

In this exercise, the transactions["Transaction Time"] DataFrame column is a float dtype yet it seems to have characteristics of a discrete variable (as opposed to a continuous variable), at least as I’m currently understanding the difference in quantitative variables.

The transaction times are encoded as float numbers between 0 and < 24 (0 and 23.999999), with 0 being 12:00am and < 24 being just before midnight of the next day, or 11:59pm. I’m thinking that, despite my initial instincts, it has characteristics of a discrete variable in that it’s ultimately a closed set of numbers between 0 and < 24. However, I know that floats are usually continuous variables and the fact that it’s “< 24” (approaching 24) makes me think that it is indeed a continuous quantitative variable.

Would these transaction times be continuous or discrete, and is my reasoning sound?

[lisalisaj]

Yep, it’s a discrete variable. Discrete variables are counted, and can only take a specific value that has a finite outcome whereas continuous variables are measured like blood pressure, weight, height, etc.