Charts help you spot patterns, trends, and comparisons in your data that might be difficult to see in a table of numbers. By presenting your data visually, charts make it easier to understand what's happening and communicate insights to colleagues and stakeholders.
Why use charts
When you're tracking emissions across your supply chain or monitoring progress toward sustainability targets, a well-chosen chart can reveal the story behind your data. You might notice that carbon intensity spikes in certain months, that one supplier consistently outperforms others, or that you're ahead of your reduction targets. These patterns become immediately visible in a chart, whereas they might be buried in rows of figures.
Charts also make it easier to share findings with stakeholders who may not have time to analyse detailed tables. A clear chart can communicate your key message at a glance.
The variety of chart types
Analyse data offers a range of chart types, each suited to different kinds of questions. The right choice depends on what you're trying to show.
Chart type | What it shows |
Bar chart | Compares values across categories or groups. Bars can be horizontal or vertical, and stacked to show parts of totals. |
Line chart | Shows how values change over time, helping you spot trends and anomalies. |
Area chart | Similar to line charts but fills the space below the line, useful for showing magnitude or cumulative values over time. |
KPI chart | Highlights a single metric prominently—ideal for headline figures like total emissions or year-on-year change. |
Scatter plot | Shows the relationship between two numeric values, helping identify correlations and outliers. |
Combo chart | Combines different mark types (such as bars and lines) on a single chart, useful for comparing metrics with different scales. |
Box chart | Displays the distribution of values, showing minimum, median, maximum, and quartiles. |
Pie and donut charts | Show how parts contribute to a whole—best with a small number of segments. |
Sankey diagram | Shows how data flows between stages or categories, useful for visualising distributions across a process. |
Funnel chart | Measures values across sequential stages in a process, helping identify where drop-offs occur. |
Gauge chart | Displays a single value against a radial scale, useful for showing progress toward a target. |
Waterfall chart | Shows how an initial value is affected by positive and negative changes, helpful for explaining how figures build up. |
Maps | Display data geographically. Region maps colour areas by value; point maps plot specific coordinates. |
For detailed guidance on each chart type and when to use it, see Chart types reference.
Anatomy of a chart
Most charts share common components that help viewers understand the data.
Component | Purpose |
Title | Describes what the chart shows. A clear, descriptive title helps viewers quickly grasp the chart's purpose. |
Axes | Provide the reference framework for your data. The horizontal axis (X-axis) typically shows categories or time periods; the vertical axis (Y-axis) shows values being measured. |
Legend | Explains what each colour or symbol represents, particularly when your chart shows multiple data series. |
Data labels | Display actual values on the chart itself, making it easier to read precise figures without referring to the axes. |
How charts connect to data
Every chart in Analyse data is linked to a data source—either a data model (outside your workbook), a table or pivot table (in your workbook). When you create a chart, you select the data source and then configure which columns to display on each axis.
This connection means your charts stay up to date automatically. When the underlying data changes—for example, when new monthly figures are added—your charts reflect those changes without any manual updates needed.
Creating your first chart
Creating charts from the UI Menu
To create a chart:
Click Charts in the floating UI menu
Choose the chart type you want
Select your data source
Configure the axes by choosing which columns to display
Once created, you can adjust your chart using the Properties panel (to change what data is displayed) and the Format panel (to change how it looks).
Creating charts from tables and pivot tables
In Analyse data, anything you add to a workbook page is called an element. Tables, pivot tables, charts, and controls are all types of elements. You can add elements directly from a data model, or you can create them from other elements already on the page.
When you create a chart from an existing table or pivot table, the chart becomes a child element of that source. This parent-child relationship is useful because the child automatically inherits data and filters from its parent. If you filter the table to show only data from a specific region, any child charts will automatically show only that region's data too. This makes it easy to build coordinated views where tables, pivot tables, and charts stay in sync.
To create a chart from an existing table or pivot table
Select the source table or pivot table
Select Create child element in the top right of the table or pivot table
Then choose Chart.
What's next
To learn which chart type is best for your data, see Chart types reference. For step-by-step guidance on formatting and styling, see Customise chart appearance.