Create a chart
Open a map
You'll start with a map of the Box Store's branch locations that your colleague shared. To make recommendations for underperforming branch locations, you first need to understand the data you have for each store.
- Open the Box Store Locations map.
This map is styled to show each Box Store location's year-over-year growth, or the percent change compared to the previous year's sales. Arrows pointing up show stores that sold more, and arrows pointing down show stores that sold less. The size of the arrow corresponds to how far above or below the average each store location performed.
This layer contains additional data that you want to explore.
- On the ribbon, click Sign In. Sign in to your ArcGIS organizational account.
Note:
If you don't have an organizational account, see options for software access.
- On the Contents toolbar, click Layers. In the Layers pane, click Box Store Branch Locations to select the layer.
- For the Box Store Branch Locations layer, click Options and choose Show table.
The layer's attribute table opens. This table shows the tabular data stored with the store locations. This data can be visualized on the map, like the current style that shows 2026 sales. It can be charted and used for deeper analysis.
- Scroll through the attribute table, taking note of the column headers.
The table contains sales data for different departments. It also has sales data for each branch over the past five years.
- In the table, scroll until you see the Sales 2025 column. Next to the Sales 2025 title, click the Menu button and choose Information.
A window appears, showing information about the attribute field, including the field type, description, and statistics about the values in the field.
- In the information window, scroll down until you see the Statistics section.
According to the attribute statistics, the average branch sales for 2025 was $25,148,807.40.
- Close the information window. Click the Sales 2025 header once to sort the table by ascending values.
The table updates to show store locations in order of lowest 2025 sales to highest.
- Check the check box next to the topmost record. On the table ribbon, click the Menu button and choose Zoom to selection.
Note:
The Zoom to selection option centers the point on the map. Depending how large the attribute table is, the point may be under it. Zoom and pan the map until you see the point.
According to the table, the lowest-earning store is located in Monroe.
- Close the attribute table.
Review a chart
Now that you have a better idea of the types of data stored for each location, you'll use charts to start assessing the data. Your colleague already created a chart before they shared the map. You can open, review, and edit this chart as needed.
- On the Contents toolbar, click the Charts button.
In the Charts pane, there is already a chart titled 2025 Median Household Income and Groceries (% of 2025 Sales). Charts can be saved and stored with maps and accessed by people the map is shared with.
- In the Charts pane, click the 2025 Median Household Income and Groceries (% of 2025 Sales) chart to open it.
A scatterplot opens, showing the relationship between spending on groceries and median household income. Based on this chart, you can tell that as median household income increased, spending on groceries as a percent of total sales decreased. This pattern suggests that in areas with higher incomes, other Box Store departments may be more profitable than the grocery department.
This is an interesting data point to get you started on your analysis, but not the only one you'll need for your presentation.
- Close the 2025 Median Household Income and Groceries (% of 2025 Sales) chart.
Create a chart
While the map shows branch locations' growth, it doesn't show overall performance. For example, while the Monroe store had the lowest sales in 2025, it still grew compared to 2024. These are both important metrics to consider, so you'll create a chart that compares sales from 2024 to 2025.
- On the Settings (light) toolbar, click Configure charts.
- In the Charts pane, click Add chart and choose Bar chart.
A blank Bar chart window appears and the Data pane opens. Bar charts summarize and compare categorical data using proportional bar lengths to represent values. In Map Viewer, they can be driven by category, numeric fields, or both. You'll start by adding numeric fields.
- In the Data pane, for Numeric fields, click Select numeric fields. In the Select fields window, choose Sales 2025 and Sales 2024.
By default, the chart shows the sum of each category for aggregation, showing the total value of sales in 2024 and 2025.
You can change this statistic. For example, using the mean would show the average sales by department for the dataset.
You can also add a Category value to sort the data by. For example, adding City as the Category value shows sales by category for each city that has Box Store locations.
- For Category, choose Store Name.
The chart redraws to show 2024 and 2025 sales by store.
- For Sort order, choose Y-axis descending.
Now the chart shows each store's 2024 and 2025 sales in order of highest-earning location to lowest-earning. You can also add references to this chart. Earlier, you used the attribute table to find that the 2025 sales averaged $25,148,807.4. You'll add this to the chart as a guide.
- Click the Guides tab. Click Add guide.
- For Y-axis guide 1, in the Start box, delete the current text and type or copy the value 25,148,807.4.
A guideline is added to the chart.
- For Guide name, delete the current text and type or paste 2025 Average Sales. For Guide label, type or copy the same text.
You can make more changes to the chart, including changing the color of the bars.
- Click the Series tab. In the Series group, for the Sales 2024 field, click the color swatch and choose #cba6e3.
- Close the Series style window.
The chart can be used to explore data interactively.
- On the chart, click one of the bars for the Baton Rouge – Cortana location, the highest earning store.
The corresponding point is highlighted on the map.
Tip:
If you don't see the point on the map, you may need to zoom and pan the map until you find it. You can also resize the chart window using the Expand and Collapse buttons. You can also point to store names in the chart to show the full name.
- On the map, click the point for the Baton Rouge – Cortana location.
A pop-up showing details about the store appears. Using the map and chart, you can see that while the store was the top earning location, it is experiencing relatively moderate growth compared to other locations.
Save the map
This map is a great tool for visualizing regional patterns and can be exposed in ArcGIS applications alongside multiple charts, graphs, and indicators for additional insight. You'll save a copy of the chart and the map.
- In the Configure charts pane, click the General tab.
- For Chart title, delete the current text and type or copy and paste 2024 and 2025 Sales.
- For Y-axis title, type Total sales.
The chart is now fully configured. Charts are saved with maps and can also be exported as images or tables to be used in other formats, such as documents and presentations.
- On the chart toolbar, click Export and choose Export as Image.
The file is saved to your computer.
- On the Contents toolbar, click Save and open and choose Save as.
- In the Save map window, provide the following information:
- For Title, type Box Stores Performance.
- For Tags, type Retail, Box Store, Sales, Tutorial.
- For Summary, type This map shows sales data for the fictional Box Store locations in Louisiana.
- Click Save.
In this tutorial, you created a bar chart comparing two years worth of sales data for Box Store locations in Louisiana. Charts, used together with maps, can help uncover patterns and trends in data.
This tutorial is part of the series Integrate maps, apps, and scenes to tell a story.
You can find more tutorials in the tutorial gallery.
