Create a workbook

In this exercise, you will use ArcGIS Insights to explore and start asking questions about your data. In 30 minutes or less, you will do the following:

  • Add data to Insights.
  • Start Insights and sign in to your account.
  • Create a workbook and add data from your content.
  • Create maps, charts, and tables to help you understand your data.
  • Interact with cards, including zooming and panning and making selections.

Add data to a new workbook

The data for this analysis has been provided publicly on the ArcGIS website, where it can be downloaded to your machine. Follow these steps to access and load the data into Insights:

  1. Download the College_Scorecard_09_28_2018 Excel file.
  2. Locate the downloaded file on your computer.

    Depending on your web browser, you may have been prompted to choose the file's location before you began the download. Most browsers download to your computer's Downloads folder by default.

    The downloaded file is a spreadsheet. Next, you'll create a workbook in ArcGIS Insights.

  3. Sign in to Insights using your licensed ArcGIS account.

    To access Insights, your ArcGIS organization's administrator must grant you a license for it. If you don't have an organizational account or if your organization does not have Insights licenses, you can sign up for a free trial.

    If this is your first time signing in to your Insights account, the Welcome to Insights window appears.

  4. If necessary, in the Welcome to Insights window, click Skip.

    The Insights home page appears.

  5. Click the Workbooks tab.

    Workbooks tab

    In Insights, your analysis is done in a workbook. A workbook stores all of the pages, data, and processes from your analysis.

  6. On the Workbooks page, click New workbook.

    The Add to page window appears with the Data tab open. The Data tab includes the data sources that are available to you in your current deployment.

  7. Click Upload file.

    Upload file on the Data tab

  8. Click Browse my computer and open the Excel file or drag the file into the Add to page window. Click Add.

    The workbook opens with the CollegeScorecard.Table1 dataset in the data pane.

  9. Click Untitled Workbook and rename it US Colleges - <Your Name>.

    Including your name in the title will make your workbook easier to find if you share your work.

  10. Click the Save button on the workbook toolbar.

    Save button

Explore your map

This section describes basic interactions you can make with map cards, but first you must enable location on your Excel file.

  1. In the data pane, next to the CollegeScorecard.Table1 layer, click the Dataset options button and choose Enable location.

    Enable location

    The default method of enabling location uses coordinates. The LONGITUDE and LATITUDE fields from the Excel file are already populated by default.

  2. Click the Repeat identical features check box.

    Checking Repeat identical features means that all of the colleges in the dataset will be added to the map individually, even if there are repeat features. This step will be important later in the lesson.

  3. Click Run.
  4. Expand the dataset in the data pane.

    A location field is added to the dataset

    A location field named Coordinates has been added to the dataset.

  5. Drag the dataset to your page and drop it on the Map drop zone to create a location map of United States colleges.

    Create a map


    If you prefer to use buttons, you can select a field from the dataset and click the Map button above the data pane.


    If your map is styled by Count of CollegeScorecard.Table1, you didn't check Repeat identical features when location was enabled. Click the Undo button until the Coordinates field is removed from the dataset, and start again at step 1.

  6. Drag the corners of the map to expand it.

    You can also drag the card to a different position on the page.

  7. Click the Basemaps button and choose Light Gray Canvas.

    The light gray canvas basemap provides a subtle background that will not compete with your data.

  8. Press Shift and draw a rectangle around the continental United States.

    You can also use the wheel button on your mouse or the Zoom tools button on the card toolbar to zoom in and out.

  9. Select the TYPE field in the data pane and drag it to your map.

    The map updates to show the colleges styled by unique color based on the type of school.

  10. Expand the TYPE layer on the map to open the Layer options pane.

    Expand the Layer options pane

    The Layer options pane lists the three college types—Private For-Profit, Private Nonprofit, and Public—and the number of features of each type. This information is useful, so it would be good to display it permanently.

  11. In the Layer options pane, click the Pop out legend button.

    The legend is displayed as a separate card on your map.

  12. Resize the legend and move it to the lower left corner of your map.

    In Insights, the legend is interactive and can be used to understand the patterns in your data. In addition to filtering, it can also display relevant statistics about the data.

  13. On the legend, click the Card options button and choose Appearance.

    Choose Appearance options

  14. Click the Legend options tab, then check Show count. Close the Appearance pane.
  15. Click Private For-Profit in the legend.

    The for-profit schools are selected on the map and the other schools fade into the background.

    Select Private For-Profit on the legend

    Using the legend to make selections on the map can be useful for looking at patterns.

  16. Zoom and pan around your map to look for patterns in for-profit schools.

    Use the zoom tools or the wheel button on your mouse to zoom. Click and drag the map to pan. If you get lost, use the Default extent button to zoom to the full extent of the data.

    Default extent button

    The for-profit schools tend to be clustered around urban areas and are mostly in the eastern half of the continental United States.

  17. Click Private Nonprofit in the legend to change the selection on the map. Zoom and pan around the map again looking for patterns in the nonprofit schools.

    There are fewer nonprofit colleges than for-profit colleges, as shown by the Count values in the legend, and they are less concentrated in large urban areas. There are more private nonprofit colleges in Alaska and Hawaii than there are private for-profit colleges. The colleges are still concentrated in the eastern half of the United States.

  18. Click Public in the legend to change the selection on the map. Zoom and pan again to look for patterns in the public schools.

    Public schools have a slightly more uniform distribution across the country, including more colleges in Alaska and Hawaii and across the Midwest.

  19. Click Public again to clear the selection.
  20. Save your workbook.

Create charts and tables

Finding spatial patterns in your data is important, but you may also want to learn more about the nonspatial aspects of your data. You can do that using tables and charts.

  1. If necessary, expand the CollegeScorecard.Table1 dataset.

    Fields from the dataset are listed. Each field has an icon that indicates the field type, which is based on the type of data the field contains.

  2. Click the circles next to the REGION and COST fields.

    Blue circles around the check marks indicate selected fields.

  3. Drag the selected fields to the Table drop zone and drop them on Summary Table.

    Create a table


    If you prefer to use buttons instead of dragging fields, click the Table button above the data pane after you select your fields.

    A summary table appears as a card on your page. Each region is listed with the sum of costs for the colleges in the region. Instead of a sum of costs, average costs are more helpful to know.

  4. On the header for the COST column, change SUM to AVG.
  5. Click the arrows next to the COST statistic twice to sort the costs in descending order.

    Change the table to average and sort descending

    The table now shows the regions in order, with the most expensive region (New England) listed first and the least expensive (Southwest) listed last. The table is useful for discovering the exact values of the average cost, but it doesn't offer a quick view of the differences in average cost. Changing the table to a chart will give you a more visual representation of the costs.

  6. On the card toolbar, click the Visualization type button and choose Bar Chart.

    Bar Chart in the visualization menu

    The table updates to show a bar chart. Now that you've seen the average cost by region, you can also view average cost by college type.

  7. On the y-axis of the bar chart, click REGION to expand a menu of fields.

    The REGION field is a string field, so all of the fields listed in the menu also contain strings.

  8. Click TYPE to change the value on the axis.

    The bar chart now shows the type of college and the average cost.

    Private nonprofit colleges have the highest average cost, and public colleges have the lowest average cost. You can also change the style of the bar chart so that it matches the style of the map.

  9. On the card toolbar, click the Layer options button and click the Symbology tab.
  10. Change Symbol type to Unique symbols. Close the Layer options pane.

    College type styled by unique symbols

  11. Save your workbook.

Analyze your data with statistics

You now know which types of colleges have the highest costs. You can also see how much of an effect the costs have on earnings after graduation.

  1. In the data pane, select COST and EARNINGS.
  2. Drag the fields to the Charts drop zone and drop them on Scatter Plot.

    Create a scatter plot

    A scatter plot is created with the cost on the x-axis (horizontal) and the mean earnings on the y-axis (vertical).


    If your scatter plot is displaying the fields on the wrong axes, you can change them using the Switch axes button.

  3. Click Color by on the x-axis and choose TYPE.

    The scatter plot shows that there is a slight positive relationship between the cost of colleges and the earnings after graduation. Chart statistics can help you quantify the relationship more accurately.

  4. On the card toolbar, click the Chart statistics button and choose Linear. Close the Chart statistics pane.

    Add statistics to the scatter plot

    A linear best fit line is added to the scatter plot, along with the line equation (y = 0.51x + 22,340) and R² value (0.299). The R² value, also called the coefficient of determination, is a goodness of fit measure that indicates the strength of the relationship between the variables on the scatter plot. The R² value is between 0 and 1, with values closer to 1 having a stronger relationship. In this case, the R² value is closer to 0, meaning that the cost of colleges does not have a strong effect on the earnings after graduation. Next, you will see if this is true for each type of college individually.

  5. On the scatter plot card toolbar, click the Enable cross filters button.

    A cross filter allows you to quickly filter data on a card by making a selection on a different card.

  6. On the map legend, click Private For-Profit.

    The for-profit colleges are selected on the map and bar chart, and the scatter plot is filtered to show only for-profit schools.

    Scatter plot filtered by for-profit colleges

    The statistics are recalculated for the for-profit colleges. The new line of best fit is still positive, but the R² value has dropped to 0.258, meaning that the cost of a for-profit college has little influence on the earnings of graduates. You can see from the scatter plot that a lot of colleges have higher-than-expected earnings after graduation based on the cost.

  7. Select Private Nonprofit, then select Public in the map legend. Note the R² values of each college type.

    Private nonprofit and public colleges each have an R² value of 0.396. These values are better than the full dataset and private for-profit schools, which implies that there is a stronger relationship between cost and earnings after graduation in nonprofit and public colleges than in for-profit colleges.

  8. Click Public again to clear the filter.
  9. Save your workbook.

You created a map, a chart, and a table in an Insights workbook and used them to explore a dataset. Next, you'll analyze the return on investment for American colleges.

Solve a spatial problem

In this exercise, you will use ArcGIS Insights to analyze United States Department of Education College Scorecard data in the form of a feature layer to find relationships between the cost of college and earnings by graduates. In 45 minutes or less, you will do the following:

  • Create interactive maps, charts, and tables.
  • Apply an advanced filter to your data.
  • Use spatial and nonspatial analysis techniques to solve a problem.

Calculate return on investment

The return on investment (ROI) for colleges is calculated using cost and earnings after graduation. In this section, you will begin your analysis by calculating ROI for all United States colleges.

  1. If necessary, open your US Colleges workbook.
  2. Drag the CollegeScorecard.Table1 dataset to the New page tab.

    New page tab

  3. Drag the dataset to your page and drop it on the Map drop zone to create a map of United States colleges.
  4. Change the basemap to Light Gray Canvas.
  5. Click the map to activate it, if necessary. Click the Action button on the map to open the Analytics pane.

    Action button

  6. Click the Find answers tab and click How is it related? to display spatial and nonspatial analysis capabilities.
  7. Click Calculate Ratio. For the numerator, choose EARNINGS, and for the denominator, choose COST. Name the field ROI and click Run.

    A data table appears, providing a view of your raw data. The ROI field is the last column in the table.

  8. Close the data table and save your workbook.

Find states with above average ROI

Now that your dataset has a field for return on investment, you can start to find more information about which areas have a high ROI. In this section, you will filter your data and determine which states have the highest ROI.

  1. On the map card, click the Card filter button.

    Card filter button

    The New filter pane appears.


    Using a card filter instead of a dataset filter will allow you to work with both the filtered and unfiltered data throughout your analysis.

  2. Click Advanced to open the Expression filter pane.

    An advanced filter is an expression-based filter that allows you to create complicated queries or incorporate calculations into your filter.

  3. Enter the expression ROI>AVG(ROI) to query only the colleges with a greater than average return on investment. Click Apply.

    Expression filter pane

  4. Close the Card filters pane.

    A result dataset is added to the data pane with the same name as your original dataset. You'll rename the result to distinguish it from the original.

  5. Hover over the result dataset and click the Rename dataset button.

    Rename dataset button

  6. Rename the dataset Colleges_ROI and press Enter to set the changes.

    There are several ways to analyze ROI within states. In this case, you will use a stacked bar chart so you can incorporate the state and type of college.

  7. Expand Colleges_ROI to display the fields. Select STATE and TYPE, drag them to the Chart drop zone, and drop them on Stacked Bar Chart.

    Stacked bar chart of STATE, TYPE, and COUNT

    A stacked bar chart is created showing the count of colleges with an above average ROI for each state and college type.

  8. Drag the bottom edge of the chart card down to see all of the states.
  9. On the card toolbar, click the Sort button and choose Sort descending.

    Sort descending

    The chart now shows the state with the highest count of colleges with above average ROI at the top, and the rest of the states in descending order. Now you can change the axis labels to make the chart easier to understand.

  10. On the card toolbar, click the Card options button, and click Edit labels.

    Edit labels

  11. Click the axis to rename it. Name the x-axis (horizontal) Count of colleges with above average ROI and rename the y-axis (vertical) State and college type.

You now have a bar chart that shows the count of high-ROI colleges for each state and college type. In the next section, you will analyze the colleges spatially.

Analyze the ROI spatially

    In the previous section, you used a chart to calculate the count of colleges with above average ROI. Another way to calculate the count is through spatial aggregation. Spatial aggregation will allow you to display the counts on a map and incorporate spatial patterns into your analysis. To perform spatial aggregation, you will need a spatial dataset with the appropriate boundaries.
  1. On the page toolbar, click the Add to page button.

    Add to page

    The Add to page window appears.

  2. Click Living Atlas to display the available ArcGIS Living Atlas layers.
  3. Search for USA States and select the USA States (Generalized) dataset. Click Add.

    A map of U.S. states is added to your page. You do not need to keep this map on the page to use it in your analysis.

  4. On the map of U.S. states, click Card options and click Delete.

    Delete button

  5. Drag the state dataset from the data pane onto the map of Colleges_ROI and drop it on Spatial aggregation.

    The Spatial Aggregation pane appears. By default, the aggregation will calculate the count of colleges in each state.

  6. Click Run.

    Count of colleges with above average return on investment, by state

    The Colleges_ROI result dataset is replaced with a new Spatial Aggregation 1 dataset. The map is updated to show the counts of high-ROI colleges for each state with graduated symbols. The map shows the same information as the chart, but without incorporating college type. Rather than using two methods to display the same information, you can create a map that shows the percentage of colleges with a high ROI. To do this, you will need a count of all colleges in each state.

  7. Drag the original College_Scorecard.Table1 dataset to the map and drop it in the Spatial aggregation drop zone. Click Run to calculate the count of colleges in each state.

    The count is calculated by default.

    A second spatial aggregation dataset is added to the data pane and the map updates to show the new Count of CollegeScorecard.Table1 field.

  8. Expand the Spatial Aggregation 2 dataset.

    There are two count fields: Count of Colleges_ROI, which includes the count of colleges with above average ROI in each state, and Count of CollegeScorecard.Table1, which includes the total count of colleges in each state.

  9. Click the Rename dataset button next to Spatial Aggregation 2 and name the dataset College counts.
  10. Open the Dataset options menu and click View data table.

    The data table appears, displaying the raw data for the dataset. The data table can be used to calculate the percentage of colleges that have an above average ROI.

  11. Click + Field to add a new field to the data table.

    Add a field

  12. Click New Field and change the field name to PercAboveAvgROI (Percent above average ROI).
  13. Click the Enter calculate function box and enter the equation (Count of Colleges_ROI/Count of CollegeScorecard.Table1)*100. Click Run and close the data table.
  14. In the College counts layer, next to PercAboveAvgROI, click the number field button and choose Rate/Ratio to change the field type.

    Changing the field type

    The new field will now be treated as a proportional value, rather than a quantity.

  15. Drag PercAboveAvgROI to the map to update the style.

    Percent of colleges with above average return on investment

    A choropleth map (a map styled with graduated colors) is created.

  16. Resize the map so that it fits onto your page and all of the states are visible.
  17. Save your workbook.

Change the classification on your map

Now that you have your map, you can start making conclusions about ROI in different states. However, it's important to remember that your conclusions are going to be affected by the classification on the map. Therefore, you should confirm which classification is being used before you finish your analysis.

  1. On the map card, click the arrow next to the layer name to open the Layer options pane.
  2. Click the Symbology tab. Click Classification to expand the classification type and number of classes.

    The default classification is natural breaks with five classes. Natural breaks is a useful classification for seeing natural groupings inherent in the data, but it may not be the best classification for this scenario.

  3. Click Natural breaks to expand the Classification type menu.

    There are six classification options available: Natural breaks, Equal interval, Quantile, Standard deviation, Unclassed, and Manual.

    An unclassed classification gives the map a continuous color ramp rather than discrete classes. In this case, it is probably best to have discrete classes so that the states can be analyzed in groups. An equal interval classification is good for data with a known range, such as percentages, because it allows you to group your data into set ranges (for example, a dataset with percentages could be divided into five intervals with ranges of 20 percent). A quantile classification divides the data into groups with an equal number of features, which makes it a good choice for data that you want to display by rank. In this case, a ranked classification may be useful. A standard deviation classification is useful when you want to focus on the distance from the mean. While knowing the average may be helpful in this scenario, it doesn't need to be the focus of your analysis. Finally, a manual classification can be used to create a custom classification scheme. Manually changing the classification can be useful for data with specific values that need to be taken into account or for standardizing the classification between multiple maps.

    On the surface, quantile and equal interval seem like the best options. However, this dataset has 51 features (50 states plus the District of Columbia), which makes it difficult to divide the data equally into a quantile classification. It may be best to try equal interval.

  4. In the Classification type menu, click Equal interval.

    Equal Interval map and settings

    The classification updates. You can click the dividers to see the ranges of the intervals. The divisions are 21.21, 34.09, 46.97, and 59.85. It makes sense to have an equal interval, but these values are not intuitive. It makes more sense to apply an equal interval to a full percentage range from 0 to 100. You will use intervals of 10.

  5. Change the number of classes to 8.
  6. Click the first slider and change the value from 16.38 to 10. Press Enter.

    The divider moves to 10 and the Classification type updates to Manual.

    First class divider set to 10

  7. Change the other dividers to 20, 30, 40, 50, 60, and 70.

    Percent of colleges with above average ROI, classified by ROI

  8. In the Layer options pane, click the Legend tab to see the values.
  9. Click the legend entry for > 70 - 73 then hover over the selected feature on the map to view its pop-up.
  10. Click the other entries in the legend to see which states are in each class.
  11. Close the Layer options pane.
  12. Save your workbook.

The highest percentage of above average ROI colleges is in Wyoming. The next-highest percentages are in South Dakota and New Mexico. These states are all in the central part of the continental United States. As discussed earlier, the central states, Hawaii, and Alaska had relatively few private for-profit and nonprofit schools, and a relatively large proportion of public colleges. You also see in the bar chart that the majority of high-ROI colleges are public. It makes sense that states with a high proportion of public colleges would have a large percentage of colleges with a high ROI.

Next, you'll share your results as a model and an interactive page.

Share your analysis

In this exercise, you will set up and share your results with others on your marketing team. In less than 10 minutes, you will do the following:

  • Reorganize and resize your cards for display.
  • Give your cards titles and descriptions.
  • Share your analysis workflow so that it can be rerun.
  • Share your page so it can be viewed or embedded in a web page.

Share your workflow

You want to save the steps to your analysis so that you can repeat the workflow the next time the data updates. While you work, Insights captures each step of your analysis. To share the model from your analysis, do the following:

  1. Open your US Colleges workbook and go to the page where you analyzed return on investment.
  2. Click the Analysis view button on your page toolbar.
    Analysis view

    Your model appears in the analysis view. This model can be shared with your team to automate the analysis. For example, they can instantly reproduce the analysis by updating the shared model with more recent data.

  3. Open the Share and edit page menu and click Share.

    Share and edit menu

  4. Change Type to Model.
  5. For Title, type Return on Investment at United States Colleges. For Description, type Find colleges with above average return on investment and group them by college type.

    You can also choose to share your model with your organization, groups within your organization, or the public.

  6. Click Share.
  7. Click the Page view button to return to your cards.

    Page view button


    To view your new model item, click the Addto page button on the page toolbar. In the Add to page window, click the Models tab.

    Models tab on the Add to page window

    Your shared models from Content, Groups, and Organization are available. Close the Add to page window.

Resize and document the cards

Now that you have completed your analysis, you can share your results as a read-only page view with stakeholders. Your cards can be resized to display the map and chart more efficiently and to fit correctly on the platform where they will be displayed, such as a website or ArcGIS StoryMaps.

  1. Click a card to activate it. Drag the corners and sides to resize the cards to the desired size and shape. Zoom and pan the map to center it on the card.

    Now that the cards have been resized, you can start documenting them with titles and descriptions.

  2. Click the Flip card button for the map to show the back of the card.

    Flip card button on the map card

  3. Change the card title to Percent of colleges with above average ROI. For Description, type The percentage of colleges with above average return on investment. Return on investment was calculated as (earnings after graduation)/(cost).
  4. Turn the card over again using the Flip card button.
  5. Repeat the step for the chart. Change the title to ROI by State and Type and the description to A count of colleges with above average return on investment by state and grouped by type.
  6. Flip the card to the front.
  7. Save your workbook.

Add a legend

You can also allow users to see the classification of the data on your map. To do that, you will add a legend to your map.

  1. On the map card, expand the PercAboveAvgROI layer to open the Layer options pane.
  2. Click the Pop out legend button to display your legend on the page. Close the Layer options pane.

    The legend is added to your map.

  3. Resize the legend and move it to the lower left corner of your map.
  4. Click the Card options button on the legend, then click the Appearance button on the menu.

    Card options button for the legend card

    The Appearance pane appears.

  5. Expand the Card background color palette and change the transparency to 30 percent.
  6. Close the Appearance pane.

    Now that the legend is available, you no longer need access to the layer options.

  7. Click the Layer options button on the map toolbar.

    Layer options button on the map card toolbar

    The layer is hidden. The layer will remain hidden when you share the page in the next section.

Share the page

Insights pages can be shared as Page items in your organization. When a page is shared, the Page item is saved on the Pages tab of the home page, where it can be opened and viewed. You are also given an <iframe> code that can be used to embed the page in a website.


Feature layers must be shared to be visible on a shared page. All other layers, including results, will be visible without being shared first. In this case, sharing your data is not required.

  1. Click the Share and edit page button and choose Share from the menu.

    The Share as window appears with Type set to Page.

  2. For Title, type Return on Investment at United States Colleges. For Description, type Colleges with above average return on investment, grouped by college type.
  3. Under Share with, check Everyone (public) and click Share.

    You can view your shared page, access the item you just created in your organization, or use the embed code to embed your page results into a web page.

  4. Under View your shared page, click Go.

    You see the cards you created. This read-only view allows users to view your Page item and interact with your results. Shared pages cannot be edited in the Page Viewer.

  5. Close the tab for the viewer and return to your workbook.
  6. Optionally, use the <iframe> code under Embed to embed your page in a website.

    Embed code


    You will not be creating a website or story map in this exercise. To view your shared page, copy and paste the <iframe> code into an HTML editor.

  7. Close the window and save your workbook.

You can explore Insights on your own. You may want to create a workbook to share with members of your organization or rerun your analysis using different datasets. You can also create a story in ArcGIS StoryMaps with an embedded <iframe> code.

You can find more lessons in the Learn ArcGIS Lesson Gallery.