Scatter Plot 3D

What is Scatter Plot 3D?

A scatter plot 3D, also known as a 3D scatter plot, is a data visualization technique that represents the relationship between three variables. It extends the concept of a 2D scatter plot, where two variables are plotted against each other on a two-dimensional plane, by adding a third variable along a third axis, usually the vertical axis.

In a scatter plot 3D, each data point is represented by a marker or symbol positioned in three-dimensional space, with its location determined by the values of the three variables being plotted. The horizontal axes represent the values of two independent variables, while the vertical axis represents the values of the dependent variable.

When to use Scatter Plot 3D?

Here are some scenarios where you might consider using a Scatter Plot 3D:

  • Visualizing multivariate data: If you have a dataset with three continuous variables, a Scatter Plot 3D can help you understand how these variables interact with each other. It enables you to identify patterns, clusters, or trends that may not be evident in two-dimensional plots.
  • Exploring spatial data: Scatter Plot 3D can be particularly useful when dealing with spatial data, such as geographical or geospatial data. By plotting data points in three dimensions, you can analyze relationships between variables and uncover spatial patterns or correlations.
  • Time series analysis: If you have a time-dependent dataset with three variables, a Scatter Plot 3D can be used to examine how these variables change over time. By plotting the data in a three-dimensional space, you can observe the evolution of the variables and identify any relationships or patterns that emerge.
  • Data clustering: Scatter Plot 3D can be employed to visualize clusters or groups within your data. If you have a clustering algorithm that assigns data points to clusters based on three variables, a 3D scatter plot can help you understand the spatial distribution of the clusters and assess their separability.
  • Comparing multiple datasets: If you have multiple datasets with three variables each, a Scatter Plot 3D can be used to compare and contrast them. By plotting the data from different datasets in the same 3D space, you can visually analyze similarities, differences, or relationships between the variables.

Guidelines for correct usage of Scatter Plot 3D

  • Use a medium to large sample size for effective representation of data.
  • Larger samples help to reveal patterns in the data more clearly.
  • Select the sample data randomly to ensure statistical validity.
  • Random samples are used to make inferences about a population.
  • Non-randomly collected data may not accurately represent the population.

Alternatives: When not to use Scatter Plot 3D

  • Heatmap: If you have a large dataset and want to visualize the density or distribution of the data across three dimensions, a heatmap can be a good option. A heatmap uses color intensity to represent the values of the third variable, with higher intensity indicating higher values. This allows for a quick visual assessment of the distribution and patterns in the data.

Example of Scatter Plot 3D?

The goal of a food scientist is to find the best combination of time and temperature for heating a frozen dinner. To achieve this, the scientist conducts an experiment by preparing 14 samples at different durations and temperatures. A panel of professional food tasters evaluates each sample, providing ratings based on overall quality. To analyze the data, the scientist utilizes a 3D scatterplot to visualize and examine the outcomes. She has performed this in following steps:

  1. She worked all day and gathered the necessary data.

  1. Now, she analyzes the data with the help of
  2. Inside the tool, she feeds the data and map the respective columns as follows:
  3. After using the above mentioned tool, she fetches the output as follows:

How to do Scatter Plot 3D

The guide is as follows:

  1. Login in to QTools account with the help of
  2. On the home page, you can see Scatter Plot 3D under Graphical Analysis.
  3. Click on Scatter Plot 3D and reach the dashboard.
  4. Next, update the data manually or can completely copy (Ctrl+C) the data from excel sheet and paste (Ctrl+V) it here.
  5. Next, you need to put the value of confidence level.
  6. Finally, click on calculate at the bottom of the page and you will get desired results.

On the dashboard of Scatter Plot 3D, the window is separated into two parts.

On the left part, Data Pane is present. In the Data Pane, each row makes one subgroup. Data can be fed manually or the one can completely copy (Ctrl+C) the data from excel sheet and paste (Ctrl+V) it here.

On the right part, you need to map the columns with the respective parameters.