The best way to present such would be with a chart, right? Ok, but which chart?
A bar chart, pie chart, bubble chart, scatter diagram, heat map, line graph, funnel chart, or stacked bar?
If you’ve ever found yourself asking which chart is the best fit for your data, you’ve come to the right place. Below are some straight-to-the-point tips that will determine the right chart to apply to any given data set.
How to choose the right chart to visualize your data
It can be tasking having to go through a lengthy article like this anytime you’re trying to figure out the right plot for your data.
Find a scenario that best describes your data and use the corresponding chart therein.
If you don’t understand Abela’s flowchart or if it doesn’t contain the right scenario that describes your data, follow the step-by-step below to choose your chart manually another way.
Choosing the right chart for a data set: A step-by-step guide
To choose the right chart for your data, you need to answer the following questions. Your answer to each of the questions will determine the appropriate chart for your situation.
Do you want to compare stuff?
Perhaps you have a group of data sets you’re looking to compare with one another. For this scenario, what you need is a graph that allows you to compare two or many things.
Some popular names that would qualify for this are:
- Scatter Plot
For example, let’s say I have data on the market share of all the different search engines. To visualize this data and help my audience see which search engine has the largest share and which one has the lowest share, I can use a pie chart as shown below.
Do you want to show that something is a part of something?
Sometimes, you may want to show how individual parts make up the whole of something. For example, say your site visitors come from Google, PPC, and Social Media. And you have a data that backs this up. You can visualize this data to help your marketing team understand which area is lacking. This can help them understand the area to channel their next effort.
Some popular charts that would be perfect for this are:
- Stacked Bar
- Stacked Column
Do you want to understand the distribution of your data?
For example, you may want to identify the outliers in a research, the bottlenecks in your organization’s process, or the best-performing approaches in an ongoing process.
These are perfect examples of distributed data. And to visualize such data, you need plots that showcase variations.
Some of the popular names that come to mind include:
- Scatter Plot
For example, let’s say you ran a survey for your dental business across multiple cities. And then you’ll like to showcase how certain cities are completely off the mark. You can use a scatter plot to make your case.
Do you want to picture the trends in your data set?
Is there an increment or a decrement in something over time? How has XYZ behaved over the last few months? Is there a guarantee that the website will keep attracting traffic at the ongoing rate?
All these are perfect illustrations of trends.
When you’re interested in analyzing or understanding the trends in your data set, these are the kinds of plots you want to consider:
- Dual-Axis Line
For example, let’s say you have a website that’s currently not attracting enough traffic. And then, you conduct a study to understand why. You can use a line chart to quickly picture the trends in the data, which will help you understand what’s really going on.
Do you want to understand the relationship between data?
How are two or more data sets related to one another? Anytime this is of interest to you, the following charts come in handy.
- Scatter Plot
For example, let’s say you want to see how price slash affect sales or how a promo campaign affects customer loyalty. You can use a line chart to observe the relationship between the two variables.
This type of relationship observation visualization is the common theme for the traditional X-Y graphs we used to plot back then in school.
A brief preview of some popular chart types
This is your regular high school XY-axis graph. You use it when you need to show trends in data sets. For example, how something is happening over time or how something relates to another thing.
These types of plots are used to compare two or more items.
Technically the inverse of column charts. These graphs are used when there are so many items to compare. So, to avoid cluttering, you use bar graphs.
Usually best for scenarios where you need to show that something is a part of a whole.
These charts are used to showcase distribution trends across data sets.
Similar to a scatter plot, albeit with a third data set. The third data set is usually indicated by the size of the bubble.
Shows how two items or data sets are related. It also comes with a rating signature, which is indicated by the colors.