Data Visualization
Overview
Data visualization, or charting, shows information in a graph. We use data visualization to display complex and dense data in a way that's easy for users to understand. Data visualization helps users see patterns, answer questions, and make decisions.
Principles
Effective data visualization should:
Adapt to different users
Different users have different data needs. Data visualization should factor in granularity and scalability — how will a chart change with variations in detail, or with more or fewer data points?
Assist in telling a story
Data visualization should communicate messages clearly. Users should be able to explore and interpret data in a way that's engaging and intuitive.
Accurately represent information
Users should be able to understand the message without distortion. Data visualization should keep the integrity of the original data.
Choosing the right chart
When deciding how to visualize data, ask yourself what kind of data you’re presenting and what message you’re trying to communicate.
What type of data is it?
Data that can be split into groups is categorical data. Use a bar or pie chart for categorical data.
Nominal numbers are used to identify someone or something, not to denote an actual value or quantity, such as the number on the back of a footballer's shirt, the number on a racing car, or a house number. Ordinal number defining a thing's position in a series, such as first, second or third. Use bar charts for ordinal data, pie charts for nominal.
Discrete data has a finite number of values. Use bar charts for discrete data, and line charts for continuous data.
What are you trying to say about it?
Make a comparison
If you want to compare values, use a pie chart for relative comparison or a bar chart for precise comparison.
If you want to compare volumes, use an area chart or a bubble chart.
Show correlation and changes
If you want to demonstrate trends, patterns, or changes over time, use a line chart, bar chart, or scatter plot.
Relationships
If you want to show a relationship between data, choose scatter plots, bubble charts, or line charts.
Bar
When to use:
- Comparing parts of a bigger set of data, highlighting different categories, or showing change over time.
- Have categories with long labels—bar charts offer space.
- If you want to illustrate both positive and negative values in the dataset.
When to avoid:
- If you're using multiple data points.
- If you have many categories, avoid overloading your graph. Your graph shouldn't have more than 7 bars.
Donut and pie
When to use:
- To show relative proportions and percentages of a whole data set.
- If you have a small dataset.
- To compare the effect of one factor on different categories.
- If you have up to 6 categories.
- If the data is nominal and not ordinal.
When to avoid:
- If you have a big dataset.
- If you want to make a precise or absolute comparison between values.
Line
When to use:
- If you have a continuous dataset that changes over time.
- If your dataset is too big for a bar chart.
- If you want to display multiple series for the same timeline.
- If you want to visualize trends instead of exact values.
When to avoid:
- Line charts work better with bigger datasets, so, if you have a small one, use a bar chart instead.
Related
Referenced in this section:
Updated 7 months ago