The easiest and quickest way to generate a professional density plot.
Density plots are easy to create in Displayr. Simply enter in your data, and Displayr will generate the visualization for you. Then you’ll be able to see the distribution of your data and identify important characteristics like the mean, median, mode and skewness.
Displayr’s density plot maker lets you customize the appearance of your density plot including different colors, sizes, labels and font options. There are many options to choose from, so you can create a density plot that is as visually appealing as it is informative.
With Displayr, you can quickly publish or export your graph or entire presentation to PowerPoint with just a few clicks. Additionally, duplicating your density plot and replacing the data is a simple and efficient process, allowing you to create new density plots with minimal effort.
Follow the prompts to connect, type, or paste your data and create your density plot. Next, add your other visualizations and text annotations.
Add some filters to make your report interactive and publish or export to PowerPoint or as a PDF with one click.
Ready to create more stunning visualizations? In addition to using our density plot maker, we’ve got a variety of other awesome ways to visualize your data.
Whether it’s histograms, line graphs, or radar charts, Displayr can help you transform your data into whatever story you want to tell!
And just like density plots, you can customize colors, fonts, and sizes and have a play with Displayr’s cool features.
Even better, combine different graphs to create a truly impressive infographic or presentation. What are you waiting for?
Instantly visualize what you are learning. Displayr is a robust, collaborative analysis and reporting tool built for humans, not robots. SQL, R, and no-code work in harmony together so you can analyze, visualize, and build your report simultaneously in the same app.
Density plots are a type of data visualization, used to show the distribution of a set of continuous data points. They are best used when you are trying to understand the shape of the distribution of some data over a continuous interval or time period. Instead of plotting data directly, density plots use an algorithm to estimate the shape of the distribution first, before drawing it.
The chart is a variation of the histogram, but it uses an algorithm to smooth out the noise and therefore showing a smoother shape to the distribution. The peaks of a density plot help audiences see where values are concentrated over the interval.
It can therefore show you important features of the data distribution including, the mean, median, mode, skewness, and any outliers. For this reason, density plots are often used in fields such as statistics, data analysis, and research.
When creating a density plot it is best to start with raw data – values that show observations of a particular quantity. This could include, number of hours spent online, the average price of tomatoes each day for a year, the number of visitors to a museum each day over a year, etc.
For a density plot to be effective, you should have enough observations in your dataset for it to be a meaningful estimate of the distribution. Avoid using figures that are aggregated or only form a small set.
Director, Satrix Solutions
What is a density plot?
A density plot shows the distribution of data for a variable over a time period or continuous interval. The density plot is a smoothed variation of a histogram and uses kernel smoothing to smooth out noise in the data. The peak of the density plot shows where values are the most concentrated over time. Density plots are also known as a Kernel density plot or a density trace graph.
What is a density plot vs histogram?
Density plots are smoothed variations of histograms. A histogram shows values from a selected column as binned distribution in the form of bars. A density plot takes this and uses kernel smoothing to smooth out the noise. This helps form a smooth curve across bins which helps create a more defined distribution shape.
Density plots can be preferred to histograms because they are better when you want to determine the distribution shape. This is because they are not affected by the number of bins (bars on the histogram). For example, it would be difficult to form a distribution shape from a histogram with a few bins, but possible with a density plot.
How do you analyse a density plot?
Looking at the density curve on a density plot should give you an idea of the shape of distribution. The peak of the density curve is where the values are most concentrated. However, a density plot may also have more than one peak of frequently occurring values. If a density curve has only one peak, the distribution is described as unimodal. If it has two peaks, it is called a bimodal distribution.
Looking at whether the curve skews to the left or right also indicates the location of the mean and median. If a density curve has no skew, the mean is equal to the median. If it skews left, the mean is less than the median. If it skews right, the mean is greater than the median.
How do you create a density plot in Displayr?
To use Displayr’s density plot creator, you need to sign up first, confirm your email by clicking on the confirmation link that you’ll receive, and then follow the prompts to create your first density plot.
© 2025 Displayr Pty Ltd. All rights reserved.
