What are the most effective ways to create parallel coordinate plots?

Parallel coordinate plots are a powerful way to visualize multivariate and complex data. They allow you to compare multiple variables across different observations, identify patterns, clusters, outliers, and correlations. In this article, you will learn the most effective ways to create parallel coordinate plots using statistics and graphics principles.

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1 What are parallel coordinate plots?

A parallel coordinate plot is a type of graph that displays multiple variables as parallel vertical or horizontal axes. Each observation is represented by a line that connects the values of each variable on the corresponding axis. For example, if you have data on the height, weight, and age of different people, you can plot them as parallel coordinate plots with three axes. The line for each person will show how their height, weight, and age vary across the axes.

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Eren Unlu

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2y axes plots are one of the best basic ways to convey your message for two variables with a common covariate. Almost each library whether in python, R or javascript, whether high level or low level allows this feature.

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2 Why use parallel coordinate plots?

Parallel coordinate plots are a useful tool for exploring and analyzing data that have many variables and dimensions. They can help you compare the distribution and range of each variable across observations, detect outliers and anomalies that deviate from the norm, identify clusters and groups of similar observations based on their lines, discover correlations and interactions between variables by looking at the shape and slope of the lines, and visualize complex data structures such as hierarchical, network, or time-series data.

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3 How to create parallel coordinate plots?

When creating parallel coordinate plots, there are various tools and methods to choose from depending on the data and preferences. For instance, software or programming languages like R, Python, Excel, or Tableau have built-in functions or libraries for this purpose. Additionally, online platforms or applications such as Plotly, D3.js, or Parallel Coordinates can be used to upload data and generate the plots. Finally, manual or customized techniques involving designing axes, scales, colors, and labels can be employed through sketching, drawing, or coding.

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4 What are the best practices for parallel coordinate plots?

In order to make your parallel coordinate plots more effective and informative, it is important to consider several best practices. You should select the right number and order of variables to display on the axes, based on their relevance, importance, and relationship. Additionally, you should scale and normalize your variables to make them comparable and consistent across the axes, especially if they have different units or ranges. Furthermore, using colors, shapes, or styles can help distinguish different groups or categories of observations. It is also beneficial to add labels, legends, titles, and annotations to explain your variables, groups, and findings. Finally, you can filter, sort, or highlight your observations to focus on specific aspects or questions of your data.

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Eren Unlu

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In my opinion, there would be no specific addition to general best practices in 2D plotting for parallel coordinates, except of course to make attention to proper scaling. As for generic 2D plotting, I would like to emphasize the importance of binned plots, where there are many points superposed or very close.

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5 What are the challenges and limitations of parallel coordinate plots?

Parallel coordinate plots can be challenging and have their limitations. When there are too many variables or observations to display, the plot can become cluttered and confusing. It can also be misleading or inaccurate if the variables are not scaled properly or if there is missing or noisy data. Additionally, it can be difficult to interpret or communicate if the visual elements are not clear and consistent, or if the audience is unfamiliar with such plots. Furthermore, the order and orientation of the axes can influence how patterns and correlations of the data are perceived.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the most effective ways to create parallel coordinate plots?

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1 What are parallel coordinate plots?

2 Why use parallel coordinate plots?

3 How to create parallel coordinate plots?

4 What are the best practices for parallel coordinate plots?

5 What are the challenges and limitations of parallel coordinate plots?

6 Here’s what else to consider

Statistics

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What are the most effective ways to create parallel coordinate plots?

1

2

3

4

5

6

1 What are parallel coordinate plots?

2 Why use parallel coordinate plots?

3 How to create parallel coordinate plots?

4 What are the best practices for parallel coordinate plots?

5 What are the challenges and limitations of parallel coordinate plots?

6 Here’s what else to consider

Statistics

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