The ability to visualize data is an important skill one must possess no matter what level you are in with an organization or what domain you work in. You either need to understand the nuances of data visualization to tell your story in the right way or understand someone else’s story when said!

Charts are one of the prominent visualization techniques and understanding the right type graphs to use based on the data you have and the story you want to say is very important. A well-designed chart should be simple enough such that the consumer can easily understand the insights it was designed to reveal. Choosing the wrong type of data is not going to help this cause!

In this article, we will discuss some of the common types of charts used and precisely understand “what chart to use when and for what data?”!

Key Considerations For Selecting a Chart:

There are two key considerations for selecting the right chart :

  • Type of Data you have
  • Story that you want to convey with your data

To begin with, let’s summarize some of common chart types one would choose based on the types of data:

Qualitative Data Quantitative Data
The best charts for qualitative data are:
Bar graphs
Side-by-side bar graphs
Pie charts		The best charts for quantitative data are:
Histograms
Line charts
Bar charts
Column charts

The above table is just intuition and is not the only defining criteria. We will dive deeper to understand what type of charts to use when. But, before we go there let us understand more about some of the common chart types used.

Common types of charts used:

Following are some of the common type of charts used:

Some of these inputs may seem trivial!. But in reality I often find people use types of charts just because they like that specific type of chart, even when its totally not relevant to the data or the story they intend to tell.

So, Now that we have gone over some type of charts, let us dive into “What to use when”!

What chart to use when?

The answer to the above question is fairly straight forward. If you understand your data and know what story you want to tell, then choosing the chart is a straight forward process. The type of chart may depend on answer to one of the below question:

  • Do you want to show a comparison between Values?
  • Are data trend over time important to you?
  • Is Analysing distribution data your goal?
  • Do you want to show the relationship between your data?
  • Do you want to deep dive into the composition of your data?

Based on the questions you can broadly classify Chart types into one of following four buckets:

  • Comparison Charts
  • Relationship Charts
  • Distribution Charts
  • Composition Charts

These broader buckets can be broken down further based on the following characteristics :

  • Number of Variables / Categories
  • Point in time Vs Change over time

So lets now see some of the common chart types used for each of these buckets. Having talked so much about visualization, i hope the rest of the sections are self explanatory 🙂

1. Comparison

2. Relationship & Distribution

3. Composition

Conclusion

In this article we have summarized some of the key considerations for choosing charts when visualizing your data. Hope you found this article. Keep following Digital Tesseract for trending articles on Data Science & Analytics!

You can download the complete cheat sheet here :

Download