Using charts in a presentation is an effective way to get your audience to analyze and understand the relationship between various data sets. To understand how data can be illustrated meaningfully, here’s a primer on the types of charts that can be used for effective data analysis.
This is the best type of graph for presenting comparisons of data between one or more value sets. A bar chart contains two axes, with numerical values on the horizontal axis and the category sets on the vertical axis. The bars can also be plotted vertically and bar charts are sometimes called column charts. Some of the best practices for using a bar chart include:
- Color coordinate the variables to make it easier to differentiate the data.
- Don’t meddle with the shape of the bar chart by making the edges curvy or 3D, as it makes it more difficult to analyze the data.
- Annotate the values at the end of the bars or in the middle, to help viewers compare and analyze.
When to use a bar chart
- Analyzing monthly revenue of a product
- Monitoring team performance over a quarter
- Project management reports
- Social media engagement analytics
This is the perfect solution for analyzing trends in data, or multiple sets of data, over a period of time. The continuous data range is plotted on the Y-axis, and the variable range, which is usually time or duration, over the X-axis. Line graphs are minimalistic in style, so here are some ways you can make your line chart more interesting:
- Give contrasting colors for multiple lines
- Mark, label, or annotate important individual points
- Don’t plot too many lines (more than four can make it difficult to visually analyze)
When to use a line chart
If you have continuous data that you’d like to represent, then a line chart is a good option. This graph is all the more effective when trying to identify how data has performed over a specific time period. You can also use line charts in your reports to:
- Forecast revenue based on a comparison of previous years
- Analyze revenue earned from different products
The scatter plot is excellent for showing the relationship between two data series and determining their correlation. The dots on the graph represent the intersection of the data on the X and Y axes. This type of chart is great for showing the distribution trends of data and identifying the outliers. Here are some design best practices for using a scatter chart:
- Label your axes.
- Color code or differentiate your data with different sizes.
- Start y-axis at 0 for accurate representation of data.
- Use trend lines to make the correlation easier to understand.
When to use a scatter chart
The dots on a scatter plot not only report the values of individual data points but also patterns or trends when the data is taken as a whole. You can use scatter charts for:
- Budget analysis of a business project
- Tracking visitors and analyzing the time spent on a web page
- Distribution of consumers in a specific region
Pie charts are the best type of charts to represent the composition of data holistically. These are often used to illustrate the percentage breakdown of smaller parts of a data set. Here are some best practices on visually representing categories of a whole:
- Label or mark the slices in percentage
- Don’t clutter the chart with too many categories
When to use a pie chart
This type of chart is used to compare the difference in the size of the data slices. Use it to:
- Explain your target demographics
- Understand regional breakdowns of sales
- Break down your users by their age and location
This is effective when showing stacked, cumulative data series, and is a perfect way of representing overall trends. This allows your audience to visualize the area (or weightage) of each series relative to each other. Here are some design best practices for your area chart:
- Use transparent or lighter shade colors for the categories
- Limit the categories to 4 to avoid clutter
- Keep the high variable data at the top of the chart to make it easy to read.
- Start the Y-axis value at 0
When to use an area chart
Use area charts to showcase part-to-whole relationships when you want to analyze the trend of one particular variable or when you want to communicate an overall trend:
- Website traffic from different sources
- Cumulative sales revenue from different products
- Individual representative’s contribution to overall sales
Choosing a similar chart type for all your data sets will not only make your data vague but also make your presentation less interesting. Using the right chart type is key to explaining the relationship and trends between your data sets. Remember, the focus should not be on making charts fancy or sophisticated, but to give your audience a clear visualization of data.