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Style numbers

Map Viewer allows you to explore your data in different ways through a variety of smart mapping styles. When you use Change Style in Map Viewer, the nature of your data determines the styling suggestions you see by default. Once you have decided how you want to present your layer, you can make changes to its appearance that are immediately reflected on the map. Map Viewer gives you control over styling elements such as color ramps, line weights, transparency, and symbols.

Several styling options are available for visualizing features according to numeric values in your data.

Counts and Amounts (Color)

If you have numeric data, you may want to distinguish features using graduated colors to reflect a count or an amount. Different kinds of color ramps can be used—for example, a simple light-to-dark color ramp is good for showing low-to-high data values such as age, income, or ratio. Color ramps like this can be applied to points, lines, or polygons. For example, you can use a light-to-dark color ramp to represent the ratio of cropland area to general land area from low to high by county. See an example.

To style counts and amounts using color, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Choose an attribute to show. For this mapping style, choose an attribute that contains numeric values.
  3. Click the Counts and Amounts (Color) style and click Options.
  4. Do any of the following:
    • If your data isn’t already normalized or standardized, use Divided By to turn your raw data into rates or percentages. Examples of normalized data include X per capita, Y per sq. kilometer, or a ratio of x to y. Raw counts, by comparison, are better visualized with colors after they are standardized.
    • Choose a theme for the color ramp. A number of different color themes are available: High to Low, Above and Below, Extremes, and Centered On. Each tells a different story by matching colors to data in different ways.
    • To change how the color ramp is applied to the data, adjust the bounding handles along the color ramp. You can either drag the handle or click the number beside the handle and type a precise value. Experiment with the position of the handles and use the histogram and calculated average calculated average to understand the distribution of the data to fine-tune the message of the map.
    • To choose a different color ramp, or to change other graphic parameters such as stroke weights and colors, click Symbols and choose the settings you want. For more information, see Change symbols.
    • To invert, or flip, the colors in the color ramp, click Invert.
    • To see details in the histogram more closely, click Zoom in.
    • To further generalize your map, check Classify Data, choose the classification method and the number of classes, or if using standard deviation, choose the interval. You can also click Legend to manually edit the symbols and labels for the classes in the map legend.
    • If you are mapping point symbols, you have the option to rotate symbols based on a second numeric field. For example, the color of the points could depict air temperature at weather stations, while the rotation of the points depicts humidity. The default symbol is round, which doesn't depict rotation very well. It is best to choose a different shape.
    • To draw locations with missing data on the map, check Draw features with no value. Uncheck it to hide the features.
    • To hide the color ramp in the legend, uncheck the Show in legend box.
      Note:

      This option is not available if you selected Classify Data.

    • To calculate and set the optimal visible range, click Suggest next to the Visible Range slider. You can also manually set the visible range.
    • To change the transparency, move the Transparency slider to the left (less transparent) or the right (more transparent). To adjust the transparency of counts and amounts per feature, click Attribute Values, choose an attribute field, optionally choose an attribute to divide by (for normalizing the data), and set precise transparency values. You can only use this option if you have numeric or date data associated with your locations. For example, if your layer contains population data, you could adjust the transparency of each location proportional to its population. If you want to hide the transparency ramp in the legend, uncheck the Show in legend box.
      Tip:

      You can also use a custom attribute expression written in Arcade when setting transparency for features. Arcade expressions are supported for all styles except Heat map, Predominant Category, Predominant Category and Size, and the Age styles. If the layer has an existing rendering expression, you can select it from the bottom of the drop-down menu. Optionally, you can edit the expression directly in Map Viewer by clicking the Edit Expression button and making changes in the editor window.

      In addition, you can create your own expression by selecting New Expression from the drop-down menu and using the editor window to create your expression, including giving it a name. If an expression was previously created for the layer for use in labels or pop-ups, you can use it to build your expression by selecting it from the Existing tab in the editor window.

  5. Click OK when you are finished customizing your style or click Cancel to go back to the Change Style pane without saving any of your choices.

Counts and Amounts (Size)

This map style uses an orderable sequence of different sizes to represent your numeric data or ranked categories. Points, lines, and areas can all be drawn using this approach. Polygon features are displayed as proportional points over polygons. These proportional symbol maps use an intuitive logic that larger symbols equate to larger numbers. Adjust the size of the symbols to clarify the story you’re telling. For example, you could use proportional symbols to show the total population of cities. See an example.

To style counts and amount by size, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Choose an attribute to show. For this mapping style, choose an attribute that contains numeric values.
  3. Click the Counts and Amounts (Size) style and click Options.
  4. Do any of the following:
    • To change the styling of your proportional symbols (color, stroke, opacity), click Symbols and change the settings. For more information, see Change symbols.
    • To invert the symbol size order, click Invert.
      Note:

      By default, higher values are drawn with larger symbols and lower values are drawn with smaller symbols. Clicking Invert allows you to reverse this pattern.

    • To change how the proportional symbols are applied to the data, adjust the bounding handles along the histogram. You can either drag the handle or click the number beside the handle and type a precise value. All values above the upper handle are drawn with the same largest symbol. Values below the lower handle are displayed with the same smallest symbol. The remaining values in between are drawn with a proportional sequence of sizes between the two bounds. Experiment with the position of the handles and use the histogram to see the distribution of the data to fine-tune the message of the map.
    • To adjust the size of the symbols, click Size.
    • If you are mapping data associated with polygons, choose to adjust the size range automatically or specify the size range. For the automatic option, the symbols are optimized for the initial map zoom level and will automatically adjust so they look better across more zoom levels.
    • To see details in the histogram more closely, click Zoom in.
    • If you are mapping data associated with polygons, click Polygons to adjust the fill and stroke properties of the polygons.
    • To further generalize your map, check Classify Data, choose the classification method and the number of classes, or if using standard deviation, choose the interval. You can also click Legend to manually edit the symbols and labels for the classes in the map legend.
      Note:

      These options aren't available with the Color and Size, Types and Size, or Predominant Category and Size styles.

    • To draw locations with missing data on the map, check Draw features with no value. Uncheck it to hide the features.
    • To calculate and set the optimal visible range, click Suggest next to the Visible Range slider. You can also manually set the visible range.
    • To hide the size ramp in the legend, uncheck the Show in legend box.
      Note:

      This option is not available if you selected Classify Data.

    • To change the transparency, move the Transparency slider to the left (less transparent) or the right (more transparent). To adjust the transparency of counts and amounts per feature, click Attribute Values, choose an attribute field, optionally choose an attribute to divide by (for normalizing the data), and set precise transparency values. You can only use this option if you have numeric or date data associated with your locations. For example, if your layer contains urban areas, you could adjust the transparency of each location proportional to its size. If you want to hide the transparency ramp in the legend, uncheck the Show in legend box.
      Tip:

      You can also use a custom attribute expression written in Arcade when setting transparency for features. Arcade expressions are supported for all styles except Heat map, Predominant Category, Predominant Category and Size, and the Age styles. If the layer has an existing rendering expression, you can select it from the bottom of the drop-down menu. Optionally, you can edit the expression directly in Map Viewer by clicking the Edit Expression button and making changes in the editor window.

      In addition, you can create your own expression by selecting New Expression from the drop-down menu and using the editor window to create your expression, including giving it a name. If an expression was previously created for the layer for use in labels or pop-ups, you can use it to build your expression by selecting it from the Existing tab in the editor window.

  5. Click OK when you are finished customizing your style or click Cancel to go back to the Change Style pane without saving any of your choices.

Color and Size

With this style, you choose two attributes in your data and finalize both the color and the size of point symbols on your map. Or, you can use the same attribute twice: to set the size of the symbols, and to set the colors, based on the part of the data you want to emphasize. This is a good style to use when you want to show count information such as the number of female single-parent households shaded by a rate such as the rate of female single-parent households. See an example.

You can also use this style if your data contains date values that you want to show sequentially as a continuous timeline on the map along with another attribute. If the first attribute you choose is a date, color is used to show the date values while proportional symbols are used to show the other attribute. If the second attribute you choose is a date, the reverse is true: dates are shown using proportional symbols and color is used to show the other attribute.

To style two attributes using color and size, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Choose the first attribute to show.
  3. Click Add attribute and choose the second attribute to show.
    Tip:

    The first attribute uses color and the second attribute uses different symbol sizes. Switch the order of the attributes by clicking the Switch Attributes button to switch which styles are applied.

  4. Click the Color and Size style and click Options.
  5. Apply options to Counts and Amounts (Color) (first attribute) and Counts and Amounts (Size) (second attribute).
    Note:

    If one of your attributes contains date values, apply options to Continuous Timeline (Color) or Continuous Timeline (Size), depending on whether the date attribute is first or second. For the nondate attribute, apply options to Counts and Amounts (Color) or Counts and Amounts (Size).

Compare A to B

This style allows you to map the ratio between two numbers and express that relationship as percentages, simple ratios, or overall percentage. For example, you can map the estimated population for 2025 as a percentage of the known population in 2015 to observe the trend of population shift. See an example.

To style ratios, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Select the first attribute to show.
  3. Click Add attribute and choose the second attribute to show.
  4. Click the Compare A to B style and click Options.
  5. Do any of the following:
    • To change labels in the legend and the histogram, click Labels. You can switch between ratio, which shows the ratio of A to B, A as percent of A and B, which shows A as a percent of A and B, and percent, which shows A as a percent of B. The icons change as you click Labels.
    • To center the histogram, click Center at. You can switch between a=b, which centers the histogram on equal values, and average, which centers on the average value.
    • To change how colors are applied to the data, adjust the bounding handles along the color ramp. You can either drag the handle or click the number beside the handle and type a precise value. Experiment with the position of the handles and use the histogram beside the color ramp to see the distribution of the data to fine-tune the message of the map.
    • To invert, or flip, the colors in the color ramp, click Invert.
    • To choose a different color ramp, or change other graphic parameters such as stroke weights and colors, click Symbols and change the settings.
    • To see details in the histogram more closely, click Zoom in.
    • If you are mapping point symbols, you have the option to rotate symbols based on a second numeric field. For example, the color of the points could depict air temperature at weather stations, while the rotation of the points depicts humidity. The default symbol is round, which doesn't depict rotation very well. It is best to choose a different shape.
    • To draw locations with missing data on the map, check Draw features with no value. Uncheck it to hide the features.
    • To calculate and set the optimal visible range, click Suggest next to the Visible Range slider. You can also manually set the visible range.
    • To hide the color ramp in the legend, uncheck the Show in legend box.
    • To change the transparency, move the Transparency slider to the left (less transparent) or the right (more transparent).

Predominant Category

This map style is useful if your layer contains multiple related attributes that you want to compare and show which attribute is predominant—that is, has the highest value—and the degree of its predominance compared to the other attributes in the layer. For example, in a layer that shows per capita personal income by United States county across a range of years, it is valuable to see which year had the highest per capita personal income in each county, and how much higher the predominant year's value is compared to the other years. See an example.

To use the Predominant Category style, choose two to ten numeric attributes with the same unit of measure (for example, United States dollars), each representing a distinct category (for example, 2006, 2007, 2008, and 2009) related to the subject of your map (for example, per capita personal income by county). Each attribute is drawn with a different color—for example, red for 2006 and blue for 2007—defined by the color ramp applied to the layer or by colors you apply to the individual attribute categories.

This style uses transparency to show the relative strength of the predominant attribute for each feature in the layer. The strength, or degree, of predominance is calculated as a percentage of the total value of all the attributes for a given feature. Generally, the higher the transparency (that is, the lighter the color) of a feature, the lower the strength of its predominant attribute compared to the total. In the per capita personal income example, this means that counties in which the predominant year is 2007 are drawn in different shades of blue to reflect the value of per capita personal income in 2007 as a percentage of the total per capita income value for all of the years.

Note:

This style is available for hosted feature layers, feature collections, and CSV layers.

To learn more about smart mapping using predominance, explore this Story Map.

To style features by predominant category, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Select an attribute to show. For this mapping style, select an attribute that contains numeric values.
  3. Click Add attribute and choose the second numeric attribute to show. The attribute should represent a distinct category related to the first attribute and should have the same unit of measure.
  4. Specify up to eight additional numeric attributes by repeating the previous step for each additional attribute you want to include.
  5. Choose the Predominant Category style and click Options.
  6. Do any of the following:
    • To choose a different color ramp or change other graphic parameters, such as line width and outline pattern, click Symbols and change the settings. For more information, see Change symbols.
    • To customize the color of any of the categories individually, click the colored symbol beside the category in the list. Depending on whether your data is points, lines, or polygons, you will see appropriate styling options for each kind of symbol. For example, if your data is points, you can change the shape, fill color, stroke, and size of the point symbol.
    • To customize any of the category labels, click the label you want to change, type a new label, and press Enter.
    • If you are mapping point symbols, you have the option to rotate symbols based on a second numeric field. For example, the color of the points could depict air temperature at weather stations, while the rotation of the points depicts humidity. The default symbol is round, which doesn't depict rotation, so it is best to choose a different shape.
    • To change the overall transparency of the layer, move the Transparency slider to the left (less transparent) or the right (more transparent).
    • To adjust the transparency per feature based the relative strength of the predominant attribute, click Predominant Percentage. To change how transparency is applied, adjust the bounding handles along the transparency ramp. Values reflect the relative strength of the predominant attribute as a percentage of the total value of all attributes. You can either drag the handle or click the number beside the handle and type a precise value. Features whose predominant percentage value is above the upper handle value (high values) are drawn with the same transparency (darker or less transparent). Features whose predominant percentage value is below the lower handle value (low values) are displayed with the same transparency (lighter or more transparent). Features with a predominant percentage in between are drawn with continuous transparency between the two bounds. Experiment with the position of the handles and use the calculated average calculated average to help you apply transparency effectively.

      If you want to hide the transparency ramp in the legend, uncheck the Show in legend box.

      If you want to change the amount of transparency applied to high and low values, type new values in the High Values and Low Values boxes. By default, no transparency (0 percent) is applied to high values (above the upper handle) and 85 percent transparency is applied to low values (below the lower handle). Click OK when finished setting transparency.

    • To calculate and set the optimal visible range, click Suggest next to the Visible Range slider. You can also manually set the visible range.
  7. Click OK when you are finished customizing your style or click Cancel to go back to the Change Style pane without saving any of your choices.

Predominant Category and Size

Use this map style to compare multiple related attributes with the same unit of measure. Like the Predominant Category style, this style uses color to show the predominant attribute and transparency to show the degree of its predominance compared to the other attributes. In addition, the Predominant Category and Size style uses a third element—size—to represent the sum of the attributes for each feature. For example, in a layer that shows crop production by United States county, you can apply this style to see which crop—wheat, corn, soybeans, and so on—has the highest value in each county, and how much higher the predominant crop's value is compared to the other crops. In addition, by applying proportional symbols to the layer, you can compare total crop production across counties, visualizing which counties have high total crop production and which have a lower yield. See an example.

To use the Predominant Category and Size style, choose two to ten numeric attributes with the same unit of measure (for example, acres), each representing a distinct category (for example, wheat, cotton, or soybeans) related to the subject of your map (for example, crop production). Each attribute is drawn with a different color, defined by the color ramp applied to the layer or by colors you apply to the individual attribute categories. As with the Predominant Category style, this style uses transparency to show the relative strength of the predominant attribute (for example, wheat) compared to the total; generally, higher transparency equates to lower strength (that is, a lower percentage of the total value of all attributes). For the size component of this style, proportional symbols are used to show the sum of the categories (for example, total crop production by county); larger symbols represent larger numbers.

Note:

This style is available for hosted feature layers, feature collections, and CSV layers.

To learn more about smart mapping using predominance, explore this Story Map.

To style features by predominant category and size, do the following:

  1. Follow the first four steps in the Change style workflow.
  2. Choose an attribute to show. For this mapping style, choose an attribute that contains numeric values.
  3. Click Add attribute and choose the second numeric attribute to show. The attribute should represent a distinct category related to the first attribute and should have the same unit of measure.
  4. Specify up to eight additional numeric attributes by repeating the previous step for each additional attribute you want to include.
  5. Choose the Predominant Category style and click Options.
  6. Apply options to Predominant Category (attribute with the highest value) and Size (sum of the attributes).

Relationship

Using the Relationship smart mapping style, you can visualize the relationship between two numeric attributes in your point, line, or polygon feature data. For example, you may want to see whether there is a relationship between smoking rates and excessive drinking rates in the United States and in which areas of the country the relationship is most pronounced. Based on the bivariate choropleth mapping technique, the Relationship style applies a distinct graduated color ramp to the classified data in each attribute and then combines the color ramps, allowing you to see where the attributes may be related. You can explore the relationship using different focus options—for example, you can focus on where smoking and excessive drinking rates are both high or change your focus to highlight areas where they are both low. You can also change the classification method and other options. See an example.

Note:

This style is available for ArcGIS Server feature layers, hosted feature layers, feature collections, CSV layers, and ArcGIS Server 10.6 or later map services that have dynamic layers enabled.

To learn more about relationship smart mapping, explore this Story Map.

  1. Follow the first four steps in the Change style workflow.
  2. Choose an attribute from attribute to show as the first attribute in the relationship. For this mapping style, choose an attribute that contains numeric values.

    The first attribute will be styled using color to show its potential relationship with the second attribute.

  3. Click Add attribute and choose a numeric attribute from attribute to show as the second attribute in the relationship.

    The second attribute will be styled using color to show its potential relationship with the first attribute.

  4. Choose the Relationship style and click Options.
  5. From the Focus drop-down menu, choose one of the following options to specify the aspect of the relationship that you want to highlight:
    • High values—The legend focuses on features with high values for both attributes.
    • High values/Low values—The legend focuses on features with high values in the first attribute and low values in the second attribute.
    • Low values/High values—The legend focuses on features with low values in the first attribute and high values in the second attribute.
    • Low values—The legend focuses on features with low values for both attributes.
    • None—The legend has no specific focus.
  6. From the Grid size drop-down menu, choose the grid size to use for the legend.

    The higher the grid numbers, the more detailed the color gradient in the color ramp will be applied.

  7. From the Method drop-down menu, choose the classification method you want to use to classify the attribute values in your data. You can also click Legend to manually edit the symbols and labels for the classes in the map legend.
  8. Do any of the following:
    • To choose a different color ramp or change other graphic parameters, such as line width and outline pattern, click Symbols and change the settings. For more information, see Change symbols.
    • If your data isn’t already normalized or standardized, you can turn your raw data into rates or percentages. When mapping relationships, normalizing data is recommended. Examples of normalized data include X per capita, Y per square kilometer, or a ratio of x to y. Raw counts, by comparison, are better visualized with colors after they are standardized. For each attribute you're mapping, expand the attribute and choose an option from the Divided By drop-down menu. To change how the data is distributed, adjust the bounding handles along the histogram by either dragging the handle or clicking the number next to the handle and typing a precise value. You can also use the calculated average calculated average to understand the distribution of the data and fine-tune the message of the map.
    • To draw locations with missing data on the map, check Draw features with no value. Uncheck it to hide the features.
    • If you're mapping point symbols, you have the option to rotate symbols based on a second numeric field. For example, the color of the points could depict air temperature at weather stations, while the rotation of the points depicts humidity. The default symbol is round, which doesn't depict rotation, so it's best to choose a different shape.
    • To change the transparency, move the Transparency slider to the left (less transparent) or the right (more transparent). To adjust the transparency of numeric values per feature, click Attribute Values, choose an attribute field, optionally choose an attribute to divide by (for normalizing the data), and set precise transparency values. You can only use this option if you have numeric or date data associated with your locations. For example, if your layer contains population data, you could adjust the transparency of each location proportional to its population. If you want to hide the transparency ramp in the legend, uncheck the Show in legend check box.
    • To calculate and set the optimal visible range, click Suggest next to the Visible Range slider. You can also manually set the visible range.
  9. Click OK when you're finished customizing your style or click Cancel to go back to the Change Style pane without saving any of your choices.

Relationship and Size

Use the Relationship and Size map style to see the relationship between numeric attributes in your point, line, or polygon feature data. As with the Relationship style, this style applies distinct graduated color ramps to the classified data in two attributes and then combines the color ramps to show relationships between the attributes. In addition, the Relationship and Size style uses different-sized symbols to represent a third numeric attribute you specify. For example, you may want to see whether there is a relationship between obesity rates and diabetes rates in the United States, and whether rates of physical inactivity are consistent with the pattern. Using this map style, you can also visually identify the areas of the country where the relationship is most and least pronounced. Relationship and Size allows you to explore relationships in your data using different focus options, classification methods, and other options. See an example.

Note:

This style is available for ArcGIS Server feature layers, hosted feature layers, feature collections, CSV layers, and ArcGIS Server 10.6 or later map services that have dynamic layers enabled.

To learn more about relationship smart mapping, explore this Story Map.

  1. Follow the first four steps in the Change style workflow.
  2. Choose an attribute from attribute to show as the first attribute in the relationship. For this mapping style, choose an attribute that contains numeric values.

    The first attribute will be styled using color to show its potential relationship with the second attribute.

  3. Click Add attribute and choose a numeric attribute from attribute to show as the second attribute in the relationship.

    The second attribute will be styled using color to show its potential relationship with the first attribute.

  4. Repeat the previous step to choose a third numeric attribute from attribute to show.

    The third attribute will be styled in the map using different-sized symbols.

  5. Choose the Relationship and Size style and click Options.
  6. Apply options to Relationship (for the first two attributes) and Size (for the third attribute).