Data visualizations are a vital component of a data analysis, as they have the capability of summarizing large amounts of data efficiently in a graphical format. There are many chart types available, each with its own strengths and use cases. One of the trickiest parts of the analysis process is choosing the right way to represent
your data using one of these visualizations. In this article, we will approach the task of choosing a data visualization based on the type of task that you want to perform. Common roles for data visualization include: The
types of variables you are analyzing and the audience for the visualization can also affect which chart will work best within each role. Certain visualizations can also be used for multiple purposes depending on these factors. Charts for showing change over timeOne of the most common applications for visualizing data is to see the change in value for a variable across time. These charts usually have time on the horizontal axis, moving from left to right, with the variable of interest’s values on the vertical axis. There are multiple ways of encoding these values:
Charts for showing part-to-whole compositionSometimes, we need to know not just a total, but the components that comprise that total. While other charts like a standard bar chart can be used to compare the values of the components, the following charts put the part-to-whole decomposition at the forefront:
Charts for looking at how data is distributedOne important use for visualizations is to show how data points’ values are distributed. This is particularly useful during the exploration process, when trying to build an understanding of the properties of data features.
Charts for comparing values between groupsAnother very common application for a data visualization is to compare values between distinct groups. This is frequently combined with other roles for data visualization, like showing change over time, or looking at how data is distributed.
Charts for observing relationships between variablesAnother task that shows up in data exploration is understanding the relationship between data features. The chart types below can be used to plot two or more variables against one another to observe trends and patterns between them.
Charts for looking at geographical dataSometimes, data includes geographical data like latitude and longitude or regions like country or state. While plotting this data might just be extending an existing visualization onto a map background (e.g. plotting points like in a scatter plot on top of a map), there are other chart types that take the mapping domain into account. Two of these are highlighted below: Right: Cartogram of US Population from census.gov
Closing thoughtsChoosing the right chart for the job depends on the kinds of variables that you are looking at and what you want to get out of them. The above is only a general guideline: it is possible that breaking out of the standard modes will help you gain additional insights. Experiment with not just different chart types, but also how the variables are encoded in each chart. It’s also good to keep in mind that you aren’t limited to showing everything in just one plot. Often it is better to keep each individual plot as simple and clear as possible, and instead use multiple plots to make comparisons, show trends, and demonstrate relationships between multiple variables. For a handy reference guide with additional chart types and more details of when they should be used, check out our free eBook, How to Choose the Right Data Visualization. Is a commonly used tool for showing how the parts of a whole are distributed?Pie charts are used to show parts of a whole. A pie chart represents numbers in percentages, and the total sum of all the divided segments equals 100 percent.
Which of the following offers additional discussion of the Visual's content and can be up to several sentences long?A caption usually offers additional discussion of a visual's content. It can be several sentences long, if appropriate. Write effective titles, captions, and legends to help integrate your text and visuals.
Which type of chart would be best for evaluating how something has changed over time?The answer is now clear, line charts. Most data analysts prefer using a line chart as compared to other types. If you want to plot changes and trends over time, a line chart is your best option. Line charts compare data, reveal differences across categories, show trends while also revealing highs and lows.
What can compare two or more datasets to identify patterns and trends?A comparative analysis can compare two or more data sets to identify patterns and trends.
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