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What is the best way to choose a chart type for data distribution or density?

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Choosing the right chart type for your data can make a big difference in how you communicate your insights and findings. However, with so many options available, how do you decide which one is best suited for your data distribution or density? In this article, you will learn some basic guidelines and tips to help you select the most appropriate chart type for your data analysis goals.

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Ganiyat Olajumoke Ajala

LinkedIn Top Voice | Data Analyst | Incoming Data Scientist | Trainer | EdTech Innovator
Ricardo G.

Bridging Data & Business @ Mondelez | Senior Leader in Operations, Digital Transformation & Data Analytics | MBA |…

1 What is data distribution or density?

Data distribution or density refers to how your data values are spread or clustered across a range of possible values. For example, if you have a data set of heights of people, you might want to know how many people are in each height category, or how the heights are distributed along a scale. Data distribution or density can reveal important patterns, outliers, trends, and variations in your data.

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Ricardo G.

Bridging Data & Business @ Mondelez | Senior Leader in Operations, Digital Transformation & Data Analytics | MBA | Certified GBS Professional
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I was once at a music festival and found myself trying to figure out where everyone in the crowd was standing while waiting for the next act. I immediately noticed that people were not evenly distributed across the venue (uniform distribution). Instead, they were gathered in small groups (multimodal distribution), which may be evident because people tend to attend music festivals with friends. As the next act started, I noticed these small groups began breaking down, and everyone huddled near and around the stage (clustered). For whatever reason, I was trying to understand the layout of my data - in this case, the crowd. Data distribution tells you not who is there, but how they all fit together.

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Fahid Saqib

Business Intelligence | Global Logistics & Forecasting | Operational Analytics & Quality Management | Process Modelling & Improvement
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usually based on the characteristics of your data. For univariate distributions, histograms or kernel density plots provide insights, while box plots are effective for comparing multiple distributions. For bivariate distributions, scatter plots, contour plots, or 2D histograms can reveal patterns. Consider the nature of your data and the insights you aim to extract when choosing the most suitable chart type.

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2 Why does chart type matter?

The chart type you choose can affect how well you convey your message and how easily your audience can understand your data. Different chart types have different strengths and limitations, and they can highlight or obscure certain aspects of your data. For instance, a pie chart can show the relative proportions of a categorical variable, but it cannot show the distribution or density of a numerical variable. A histogram can show the frequency of a numerical variable, but it cannot show the relationship between two variables. Therefore, you need to choose a chart type that matches your data type, your analysis objective, and your audience's expectations.

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Ganiyat Olajumoke Ajala

LinkedIn Top Voice | Data Analyst | Incoming Data Scientist | Trainer | EdTech Innovator
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Charts are more than visuals—they're your voice to share insights. Choosing the right chart simplifies complex data, making it relatable. But remember, understanding chart concepts is crucial. Take pie charts, for instance—they're great for showing proportions, but packing too many slices with colors can muddle your message. Keep it clear and impactful

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Ricardo G.

Bridging Data & Business @ Mondelez | Senior Leader in Operations, Digital Transformation & Data Analytics | MBA | Certified GBS Professional
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At a previous job, I needed to visually present the distribution of purchase orders by total amount and approval levels. A pie chart could show the proportion of approved orders but not the amount ranges or approval levels. A bar chart could display amounts or ranges, but not approvals. The solution? A scatter plot. Each order was a point, plotted by amount and approval level, revealing patterns and outliers clearly. This choice transformed complex data into an insightful, easy-to-understand story, proving that the right chart type is crucial for effective data communication.

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3 How to choose a chart type for data distribution or density?

When deciding which chart type to use, there is no definitive answer as it depends on the purpose and context. However, some general steps and considerations can help guide the decision-making process. First, identify the data type - is it categorical, numerical, discrete, or continuous? Then, identify the analysis objective - do you want to compare, contrast, or rank different categories or groups? Lastly, consider the audience and context - who are you presenting your data to and what are their expectations? After narrowing down your options, evaluate and compare different chart types based on their advantages and disadvantages before selecting the one that best suits your purpose. Additionally, make sure the chart maximizes clarity, accuracy, and aesthetics.

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Ricardo G.

Bridging Data & Business @ Mondelez | Senior Leader in Operations, Digital Transformation & Data Analytics | MBA | Certified GBS Professional
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Choosing a chart type for data distribution is like picking the right golf club. Is your data a long drive (numerical) or a precise putt (categorical)? Decide your goal: comparing data (judging distance), showing a trend (tracking shot improvement), or highlighting an anomaly (that one lucky eagle). Tailor your approach to your audience, weekend golfers, or club pros. Each chart type has its strengths: pie charts show parts of a whole, scatter plots reveal trends and relationships. Select a chart that’s as effective as the perfect club, making your data clear, accurate, and engaging, like a well-played round of golf.

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4 What are some common chart types for data distribution or density?

Common chart types, such as histograms, box plots, density plots, scatter plots, and heat maps, can be used to show data distribution or density. A histogram is a type of bar chart that displays the frequency of a numerical variable in equal-sized bins or intervals. It can demonstrate the shape, spread, and skewness of a distribution, as well as any outliers or gaps. Box plots are a type of chart that show the summary statistics of a numerical variable. They can reveal the variability, symmetry, and outliers of a distribution. Density plots are charts that illustrate the probability density of a numerical variable along a continuous scale. Scatter plots are charts that show the relationship between two numerical variables by plotting their values as points on a Cartesian plane. Lastly, heat maps are charts that represent the frequency, distribution, or density of a multivariate data set with colors or shades. Each type of chart has its own advantages and disadvantages; however, they all provide valuable insights into data distributions and densities.

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5 How to improve your chart design and presentation?

When selecting a chart type to display your data distribution or density, you can further optimize your chart design and presentation with some best practices. Make sure to include appropriate labels, titles, legends, and captions that explain your data and chart clearly and concisely. Additionally, use consistent colors, shapes, and symbols to differentiate and highlight your data points or groups. Furthermore, use appropriate scales, axes, and grids to align and organize your data and chart accurately. Additionally, choose the right fonts, sizes, and styles to enhance the readability and aesthetics of your data and chart. Finally, use the right tools and software to create, edit, and export your chart in a suitable format and quality.

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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 is the best way to choose a chart type for data distribution or density?

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1 What is data distribution or density?

2 Why does chart type matter?

3 How to choose a chart type for data distribution or density?

4 What are some common chart types for data distribution or density?

5 How to improve your chart design and presentation?

6 Here’s what else to consider

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