What are the best ways to visualize data across different groups?

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Data visualization is the art and science of presenting data in a clear, engaging, and meaningful way. It can help you communicate your findings, reveal patterns and trends, and persuade your audience. But how do you choose the best way to visualize data across different groups? In this article, you will learn about some advanced graphical techniques that can help you compare and contrast data from multiple categories, segments, or dimensions.

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1 Bar Charts and Histograms

Bar charts and histograms are among the most common and versatile ways to visualize data across different groups. They can show the distribution, frequency, or proportion of values in each group, and allow for easy comparison and ranking. Bar charts use vertical or horizontal bars of equal width to represent the values of each group, while histograms use bars of varying width to represent the frequency of values in each bin or interval. You can use bar charts and histograms to compare categorical, ordinal, or numerical data across groups, as long as the groups are mutually exclusive and exhaustive.

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Md Shahrukh

Data Analyst || Biomedical Engineer|| Power BI || Insights Development|| SQL || Machine learning || Statistics || Python ||
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A Parallel coordinates plot is used to analyze multivariate numerical data. It allows a comparison of the samples or observations across multiple numerical variables. ? Each variable is represented by a vertical axis. ? Variables are placed at equal intervals along one axis and the value of each variable is plotted on the other axis as a dot. ? For a given observation, dots are connected to form multi-segment line. The choice of visualization depends on the nature of the data, the variables being compared, and the insights you aim to derive from the visualization.

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2 Pie Charts and Donut Charts

Pie charts and donut charts are circular charts that show the relative size or percentage of each group in a whole. They are useful for visualizing data across different groups when the groups are few and distinct, and the focus is on the proportion or share of each group. Pie charts use sectors or slices of a circle to represent the values of each group, while donut charts use rings or arcs of a circle to represent the values of each group. You can use pie charts and donut charts to compare nominal or categorical data across groups, as long as the groups add up to 100%.

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3 Scatter Plots and Bubble Charts

Scatter plots and bubble charts are graphical techniques that show the relationship between two or more variables across different groups. They can help you explore the correlation, trend, or clustering of data points in each group, and identify outliers or anomalies. Scatter plots use dots or markers to represent the values of each group on a Cartesian plane, while bubble charts use circles or bubbles of varying size or color to represent the values of each group on a Cartesian plane. You can use scatter plots and bubble charts to compare numerical or continuous data across groups, as long as the groups are independent and have a meaningful association.

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Eren Unlu

Co-Founder
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'Facet's are not being used enough for some reason, even though it is one of the most straightforward ways of implementing visualization. Even for co-axial data, sometimes showing side-by-side scatter plots rather than stacking in to the same graph may convey better information.

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4 Box Plots and Violin Plots

Box plots and violin plots are graphical techniques that show the distribution and variation of data across different groups. They can help you summarize the central tendency, spread, and shape of data in each group, and detect differences or similarities among groups. Box plots use rectangles or boxes to represent the interquartile range (IQR) of each group, and whiskers or lines to represent the minimum and maximum values or outliers of each group, while violin plots use curves or violins to represent the density or frequency of values in each group. You can use box plots and violin plots to compare numerical or continuous data across groups, as long as the groups are comparable and have a common scale.

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Eren Unlu

Co-Founder
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The famous "shap" library for calculating Shapley values introduced recently "layered violin plots" which boost the interpretability. I hope to see utilization of it for totally other contexts.

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5 Heat Maps and Treemaps

Heat maps and treemaps are graphical techniques that show the intensity or magnitude of data across different groups. They can help you highlight the contrast, variation, or hierarchy of data in each group, and draw attention to the most or least significant values. Heat maps use colors or shades to represent the values of each group on a grid or matrix, while treemaps use rectangles or tiles of varying size or color to represent the values of each group on a nested or hierarchical structure. You can use heat maps and treemaps to compare numerical or continuous data across groups, as long as the groups are discrete and have a logical order or arrangement.

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Eren Unlu

Co-Founder
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I would suggest do not fall into "beauty" of full spectrum hue of heatmaps. Usually, a monochromatic hue is the most interpretable coloring choice for a single scalar feature. Opt for the green. Mammal brains are evolved to differentiate greenish hue more than other colors due to surrounding vegetation : a reason nightvision systems prefer it.

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Shahid Ali

????Erasmus Mundus Scholar ??Danube AgriFood Joint Master (DAFM'22) ??M.Sc. (Hons.) Agronomy ??Research and Analysis
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I would prefer heat maps if my data is derived from a global case study, it indicates area of concern in more accurate way. Basically, the choice of map depends on your data sample, its pool size and variables.

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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 best ways to visualize data across different groups?

1

2

3

4

5

6

1 Bar Charts and Histograms

2 Pie Charts and Donut Charts

3 Scatter Plots and Bubble Charts

4 Box Plots and Violin Plots

5 Heat Maps and Treemaps

6 Here’s what else to consider

Statistics

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What are the best ways to visualize data across different groups?

1

2

3

4

5

6

1 Bar Charts and Histograms

2 Pie Charts and Donut Charts

3 Scatter Plots and Bubble Charts

4 Box Plots and Violin Plots

5 Heat Maps and Treemaps

6 Here’s what else to consider

Statistics

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