Selecting Right Chart For Your Dashboard

Bar chart or Line? Scatter plot or box plot? These are the questions we ask ourselves when we set out to make a chart. Because, “Selecting right chart for our data” is very important to tell our story.

Why is it important to make right chart?

Because right charts lead to right decisions. We use charts to tell stories, evaluate alternatives, understand trends or find-out if everything is normal. So, an incorrect charting choice can lead to poor judgment of the messages where as a correct chart can lead to right and faster decisions.

The Chart Making Process

Chart making process can be divided in to 4 steps- 

1. Find-out what you want to say? 
2. (Re)arrange the data 
3. Prepare the chart 
4. Format the chart 

1. Finding out what you want to say

This is the first and most important step in chart preparation. You must ask yourself, “what is the purpose of this chart?”. Once we know the clear reason why the chart should exist, we will naturally be able to select the correct chart type for that reason.

a. To Compare: You want to compare one set of value(s) with another.

Examples: 

Performance of Product A vs. Product B in 5 regions 

Interview performance of various candidates 

Charts that can be used for this reason: 

• Bar Charts, 
• Column Charts 
• Scatter Plots 
• Pie Charts 
• Line Charts 
• Data Tables 

b. To Show the Distribution : You want to show the distribution of a set of values (to understand the outliers, normal ranges etc.)

Examples: 

Distribution of Call waiting times in a call center 

Distribution of bugs found in 10 week software testing phase 

Charts that can be used to show distribution:

• Column Charts 
• Scatter Plots 
• Line charts 
• Box Plots 

c. Parts of Whole : You want to show how various parts comprise the whole

Examples: 

Individual product sales as a percentage of whole revenue 

Browser types of customers visiting our website 

Charts that can be used to show Parts of Whole: 

• Column Charts 
• Bar Charts 
• Pie Charts 
• Data Table 

d. Trend over time : You want to understand the trend over time of some variable(s).

Examples: 

Customer footfalls on the last 365 days 

Share price of MSFT in the last 100 trading sessions 

Charts that can be used to show Trend Over Time:

• Column Charts 
• Line Charts 
• Data Table 

e. Deviations : You want to see which values deviate from the norm.

Examples: 

Failures (or bugs) in the context of Quality Control 

Sales in Various Stores 

Charts that can be used to show Deviations:

• Column Charts 
• Bar Charts 
• Line Charts 
• Data Table 

f. Relationship : You want to establish (or show) relationship between 2 (or more) variables

Examples: 

Relationship between Search Phrases and Product Purchases in your website 

Relationship between in-store sales and holidays 

Charts that can be used to show Relationship: 

• Scatter Plot 
• Line Chart 
• Data Table 

What to do when you have more than one reason for the chart?

Simple, use common sense. If I were you, I would either cut down the messages to one or make 2 charts (each conveying one message). If that is not possible, I would consider using dynamic charts or combination charts.

2. (Re)arranging the Data

Even when we know the message and corresponding chart, sometimes, our data may not support us. We then have to rearrange the data. Using excel formulas, pivot tables, tables and data cleaning tools we can easily massage the data.

Once we have the data in required format, we proceed to step 3.

3. Prepare the chart

Since you have already selected the chart type in Step 1, this is very straight forward. Most of the regular charts are available in MS Excel as default charts. You can insert them with few clicks.

But for some special chart types, you may have to prepare the chart by helper series, formatting etc.

4. Format the chart

While most formatting is done as per individual taste, there are some ground rules that apply on almost all charts.

Here they are, 

• No non-zero axis scale on bar charts 
• Make subtle grid-lines (or remove them) 
• Add labels to important points 
• Add descriptive, bold titles 
• Position axis, scales at the right places (for eg. y-axis to the right on a large time series chart) 
• Use simple, easy colors 

A final word

The ideas in this post are meant to be guide lines, not final words in the world of visualization. While these rules can help you make a good chart, a great chart take so much more. Knowledge of your data, Passion for what you do and Genuine focus on your audience’ needs can make your chart truly outstanding.