---
title: "Multiple Y axes"
slug: "graphing-multiple-columns"
updated: 2023-11-13T08:06:25Z
published: 2023-11-13T08:06:25Z
canonical: "userguide.dataclassroom.com/graphing-multiple-columns"
---

> ## 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.

# Graphing multiple columns of data

This article is for you if you have some **data** that looks like that on the **left**, and you want a **graph** like that on the **right** - i.e. you want to have two sets of data on one graph:

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1695387114658.png)

You have **two colums** of data, and you want to plot as **two lines**. You may have found yourself wishing for a second Y axis. Well in this case you don't in fact need multiple Y axes, as both your columns are measuring the same variable (height). (You can [see this dataset here](https://dataclassroom.com/en/dataseteditor/d13546a2-d0e4-469f-9ece-e59d223354dc), by the way).

The way to do this in DataClassroom is to **reorganize your data** so your multiple columns of data become two columns, each representing a different **variable:**

- One column (or variable) that says **which subject** the row of data is "about". In this case, Plant A or Plant B. This might be called "**Plant ID**" and should be a **Categorical** variable.
- One numeric column that contains **the thing** **being measured** with numbers. This might be called "**Height"** and is a **Numeric** variable.

The Melt functionThis reorganization is called a **melt** function, and DataClassroom has a special function to perform this operation. See [this article for how to do it](/v1/docs/melt-function-to-tidy-data).

Your table should start something like this (not all rows are shown):

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1695388012132.png)

You will of course then have twice as many rows. But you can then graph your data by putting **Height** on the Y axis, and using **Plant ID** as a **Z variable** which splits the data into two **groups**. (You can open the modified dataset [in DataClassroom here](https://dataclassroom.com/en/dataseteditor/a614d36f-5e7a-4546-8298-e64ba98332e9))

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1695387620259.png)

### Why is it like this?

You may be thinking this is a lot of bother to go through, when the data are really just the same. And indeed there was nothing "wrong" with the original table.

Well, now you have organized the data so you have two clearly named **variables**, i.e. **Plant ID** and **Height**. This is a **really valuable practice** when going forward to doing any analysis of the data, whether in DataClassroom or any other tool. This is the way that the pros most often do it in the real world.

*Notice that if you had had **three** plants, you'd still only have had the same **two variables** (and two columns), you'd just have had three possible **values** under **Plant ID**.*

This way of formatting data is called **Tidy Data**, and we have a [more detailed article on it here](/v1/docs/converting-data-to-tidy-format). Have a look under **Working with data** for more related tips and tricks.