---
title: "Time and Date values"
slug: "times-and-dates"
updated: 2025-01-16T12:00:08Z
published: 2025-01-16T12:00:08Z
canonical: "userguide.dataclassroom.com/times-and-dates"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://userguide.dataclassroom.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Time and Date values

It can be tricky handling **time and date** values in datasets. Typically they will be in a source spreadsheet in a format like one of these:

- 9/23/2023  (a date)
- 9/23/2023 14:22  (a date and time, aka a timestamp)
- 1:40  (a duration, one minute and 40 seconds)
- 12:35 PM  (a time)
- 2017 (a year)

To perform any kind of numerical analysis on these values they will have to be converted into **simple numeric values**. You'll need to think about what **corresponding value** is meaningful for your graph or statistical test and also **which units** to use. Some examples:

- A birthdate could be converted into a persons age in years, or days.
- A recent date might be converted into a number of days since an experiment started.
- A timestamp value (date plus time) might be converted into how long a process has been applied, in hours, minutes or even seconds.
- A time value in hours and minutes (e.g. 5:33) could be converted to a duration in minutes.

Doing these conversions is best done in a spreadsheet program like Sheets or Excel, where you can perform calculations on dates and times, before importing the data to DataClassroom.

#### Example: converting a date into number of days:

Given the values in the first column, the days_elapsed value can be calculated.

In both Sheets and Excel, when date-formatted cells are subtracted from each other the resulting difference is the number of days.

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1737024439876.png)

#### Example: converting a duration in hours and minutes into seconds:

Here is an example using Excel. The cells in the **seconds** column have a formula multiplying the values in the **hh:mm** columns by 86400 (number of seconds in 24 hours) and are then formatted as **General** - to ensure they display as simple numbers.

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1737027185026.png)

#### Example: changing absolute years to year numbers

A year (like 1966) is already a simple numeric value. However, it will often be good to convert it to a relative value, because it might well be the "age" or other relative value that is interesting.

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1737027745762.png)

Also, for regression analyses, you will have an advantage if your time values are small (like between year 1 and 10) rather than having a large offset (like from 2015 to 2025). This is maybe not obvious but a difference of 1 year is 20% of the mean value (5.5) in the first case, but only 0.2% of the mean value in the second case. This can result in loss of precision.