Table chart parameters for LookML dashboards

This page demonstrates how to add and customize a LookML dashboard element of type: looker_grid with LookML dashboard parameters in a dashboard.lkml file.

For information about building a table chart through the Looker UI, see the Table chart options documentation page.

Example usage


## BASIC PARAMETERS
name: element_name
title: 'Element Title'
type: looker_grid
height: N
width: N
top: N
left: N
row: N
col: N
refresh: N (seconds | minutes | hours | days)
note_state: collapsed | expanded
note_display: above | below | hover
note_text: 'note text'

## QUERY PARAMETERS
model: model_name
explore: explore_name
fields: [view_name.field_name, view_name.field_name, …]
dimensions: [view_name.field_name, view_name.field_name, …]
measures: [view_name.field_name, view_name.field_name, …]
sorts: [view_name.field_name asc | desc, view_name.field_name, …]
pivots: [view_name.field_name, view_name.field_name, …]
fill_fields: [view_name.field_name, view_name.field_name, …]
subtotals: [view_name.field_name, view_name.field_name, …]
total: true | false
row_total: right | left | false
limit: N
column_limit: N
filters:
  view_name.field_name: 'Looker filter expression' | 'filter value'
filter_expression:  'Looker custom filter expression'
listen:
  dashboard_filter_name: view_name.field_name
query_timezone: 'specific timezone' | user_timezone
analysis_config: # can only be used when the Forecasting Labs feature is enabled
  forecasting:
  - confidence_interval: N
    field_name: view_name.field_name
    forecast_n: N
    forecast_interval: day | month | a time frame with dimension fill
    seasonality: N
merged_queries:
- 'primary query definition'
- 'next source query definition'
  join_fields:
  - field_name: view_name.field_name
    source_field_name: view_name.field_name

## COLUMN PARAMETERS
auto_size_all_columns: true | false
column_order: [view_name.field_name, view_name.field_name, …]
pinned_columns:
    view_name.field_name: left

## PLOT PARAMETERS
table_theme: editable | white | gray | transparent | unstyled
show_row_numbers: true | false
hide_totals: true | false
hide_row_totals: true | false
transpose: true | false
hidden_fields: [view_name.field_name, view_name.field_name, …]
limit_displayed_rows: true | false
limit_displayed_rows_values:
  show_hide: show | hide
  first_last: first | last
  num_rows: 'N'

## SERIES PARAMETERS
truncate_text: true | false
show_view_names: true | false
size_to_fit: true | false
dynamic_fields:
- table_calculation: {'table calculation definition'}
- measure: {'custom measure or custom filtered measure definition'}
- dimension: {'custom dimension definition'}
series_labels:
    view_name.field_name: 'Series Label'
series_column_widths:
    view_name.field_name: N
series_cell_visualizations:
    view_name.field_name:
        is_active: true | false
        palette:
            palette_id: 'palette ID'
            collection_id: 'collection ID'
            custom_colors:
            - 'color value'
        value_display: true | false
series_text_format:
    view_name.field_name:
        fg_color: 'color value'
        bg_color: 'color value'
        bold: true | false
        italic: true | false
        align: left | center | right
series_collapsed:
    view_name.field_name: true | false
series_value_format:
    view_name.field_name:
        format_string: 'value formatting string'

## FORMATTING PARAMETERS
color_application:
    collection_id: 'collection ID'
    palette_id: 'palette ID'
header_font_color: 'color value'
header_background_color: 'color value'
header_text_alignment: left | center | right
header_font_size: N
rows_font_size: N
enable_conditional_formatting: true | false
conditional_formatting_include_totals: true | false
conditional_formatting_include_nulls: true | false
conditional_formatting:
  {'desired conditional formatting'}

Parameter definitions

Parameter Name Description
Basic Parameters
name (for elements) Creates an element
title (for elements) Changes the way an element name appears to users
type (for elements) Determines the type of visualization to be used in the element
height (for elements) Defines the height of an element in units of tile_size for layout: tile and layout: static dashboards
width (for elements) Defines the width of an element in units of tile_size for layout: tile and layout: static dashboards
top Defines the top-to-bottom position of an element in units of tile_size for layout: static dashboards
left Defines the left-to-right position of an element in units of tile_size for layout: static dashboards
row Defines the top-to-bottom position of an element in units of rows for layout: newspaper dashboards
col Defines the left-to-right position of an element in units of columns for layout: newspaper dashboards
refresh (for elements) Sets the interval at which the element will automatically refresh
note_state Defines whether the note will be collapsed or expanded if it is too big to fit on a single row within the element's width
note_display Defines where the note displays on an element
note_text Specifies the text that displays in the note
Query Parameters
model Defines the model to be used for the element's query
explore (for elements) Defines the Explore to be used for the element's query
fields Defines the fields to be used for the element's query. This can be used in place of dimensions and measures.
dimensions Defines the dimensions to be used for the element's query
measures Defines the measures to be used for the element's query
sorts Defines the sorts to be used for the element's query
pivots Defines the dimensions that should be pivoted to be used for the element's query
fill_fields Defines the dimensions that utilize the dimension fill option
subtotals Defines the fields that are subtotaled
total Specifies whether column totals are displayed for a table visualization
row_total Specifies whether row totals are displayed for a table visualization
limit Defines the row limit to be used for the element's query
column_limit Defines the column limit to be used for the element's query
filters (for elements) Defines the filters that cannot be changed for the element's query
filter_expression Defines a custom filter that cannot be changed for the element's query
listen Defines the filters that can be changed for the element's query, if filters (for dashboard) have been created
query_timezone Defines the time zone that should be used when the query is run
analysis_config ADDED 21.14 Defines the forecast analysis that should be performed when the query is run. Requires the Forecasting Labs feature to be enabled.
merged_queries Defines a merged results query
Column Parameters
auto_size_all_columns Autosizes each table column to the width of its column heading or longest data value, whichever is wider
column_order Orders the columns in the table chart
pinned_columns Defines the columns to be pinned, or frozen, on the left side of the table chart
Plot Parameters
table_theme Applies one of five table coloring options to a table visualization
show_row_numbers Sets whether to show a row number at the beginning of each table row
hide_totals Sets whether a table visualization displays column totals
hide_row_totals Sets whether a table visualization displays row totals
transpose Sets whether to transpose table rows into columns
hidden_fields Specifies any fields to use in the query but hide from the chart
limit_displayed_rows Shows or hides rows in a visualization based on their position in the results
Series Parameters
truncate_text Shortens column headers and text inside data cells with an ellipsis (…)
show_view_names Shows the view name along with the field name for each column header
size_to_fit Automatically sizes the widths of all columns so that the table perfectly fits the width of the element in which it is being viewed
dynamic_fields Includes table calculations or custom fields in your table chart
series_labels Specifies a custom label for each column in the visualization
series_column_widths Specifies specific widths for columns in the visualization
series_cell_visualizations Specifies whether columns use the Cell Visualization visualization option. This parameter has the subparameters is_active, palette, and value_display.
series_text_format Specifies cell text layout for each column. This parameter has the subparameters fg_color, bg_color, bold, italic, and align.
series_collapsed Specifies whether a column that has subtotals will appear collapsed
series_value_format Defines the value format for a column using custom formatting
Formatting Parameters
color_application Applies colors to cell visualizations and conditional formatting
header_font_color Applies a font color to column headers
header_background_color Applies a color to the backgrounds of column headers
header_text_alignment Applies left, right, or center alignment to column headers
header_font_size Applies a font size to column headers
rows_font_size Applies a font size to text inside data cells
enable_conditional_formatting Sets to true to define color coding rules for a table visualization
conditional_formatting_include_totals Specifies whether totals are included in the color coding scheme
conditional_formatting_include_nulls Specifies whether null values should be represented as a zero
conditional_formatting Uses conditional_formatting and its subparameters to define the rules that color code your table visualization

Basic parameters

When defining a LookML dashboard element, you must specify values for at least the name and type parameters. Other basic parameters like title, height, and width affect the position and appearance of an element on a dashboard.

name

This section refers to the name parameter that is part of a dashboard element.

name can also be used as part of a dashboard filter, described on the Dashboard parameters documentation page.

Each name declaration creates a new dashboard element and assigns it a name. Element names must be unique. Names are sometimes referenced in the elements parameter when you're using layout: grid dashboards.

- name: orders_by_date

title

This section refers to the title parameter that is part of a dashboard element.

title can also be used as part of a dashboard, described on the Dashboard parameters documentation page.

title can also be used as part of a dashboard filter, described on the Dashboard parameters documentation page.

The title parameter lets you change how an element's name will appear to users. If unspecified, the title defaults to the element name.

Consider this example:

- name: sales_overview
  title: '1) Sales Overview'

If you used this format, instead of the element appearing as Sales Overview, it would appear as 1) Sales Overview.

type

This section refers to the type parameter that is part of a dashboard element.

type can also be used as part of a dashboard filter, described on the Dashboard parameters documentation page.

type can also be used as part of a join, described on the type (for joins) parameter documentation page.

type can also be used as part of a dimension, described on the Dimension, filter, and parameter types documentation page.

type can also be used as part of a measure, described on the Measure types documentation page.

The type parameter determines the type of visualization to be used in the element.

- name: element_name
  type: text | looker_grid | table | single_value | looker_single_record |
        looker_column | looker_bar | looker_scatter | looker_line | looker_area |
        looker_pie | looker_donut_multiples | looker_funnel | looker_timeline |
        looker_map | looker_google_map | looker_geo_coordinates | looker_geo_choropleth | looker_waterfall | looker_wordcloud | looker_boxplot

See the type (for LookML dashboards) documentation page for an overview of the different types of LookML dashboard elements.

height

This section refers to the height parameter that is part of a dashboard element.

height can also be used as part of a dashboard row, described on the Dashboard parameters documentation page.

For dashboards with tile or static layouts

The height parameter defines the height of an element, in units of tile_size (which is defined in pixels), for layout: tile and layout: static dashboards.

For example, the following code specifies tile_size: 100 and height: 4, making the orders_by_date element 400 pixels in height.

- dashboard: sales_overview
  tile_size: 100
  ...

  elements:
  - name: orders_by_date
    height: 4
    ...

For dashboards with newspaper layout

The height parameter defines the height of an element, in units of row, for layout: newspaper dashboards.

A dashboard with newspaper layout defaults to an element height of 6 rows, or about 300 pixels. The minimum height is 1 row for dashboards with a preferred viewer parameter set to dashboards-next. The minimum height is 2 rows for dashboards with a preferred viewer parameter set to dashboards.

For example, the following code sets an element to be 12 rows tall, or twice as tall as other elements that are set to the default:

- dashboard: sales_overview
  layout: newspaper
  ...

  elements:
  - name: orders_by_date
    height: 12
    ...

width

This section refers to the width parameter that is part of a dashboard element.

width can also be used as part of a dashboard, described on the Dashboard parameters documentation page.

The width parameter defines the width of an element, in units of tile_size, for layout: tile and layout: static dashboards.

For example, the following code specifies tile_size: 100 and width: 4, making the orders_by_date element 400 pixels in width.

- dashboard: sales_overview
  tile_size: 100
  ...

  elements:
  - name: orders_by_date
    width: 4
    ...

The width parameter defines the width of an element, in units of columns, for layout: newspaper dashboards.

A dashboard with newspaper layout defaults to a width of 24 columns.

For example, the following code sets the element to half the width of the dashboard:

- dashboard: sales_overview
  layout: newspaper
  ...

  elements:
  - name: orders_by_date
    width: 12
    ...

top

The top parameter defines the top-to-bottom position of an element, in units of tile_size, for layout: static dashboards.

For example, the following code specifies tile_size: 100 and top: 4, positioning the top edge of the orders_by_date element 400 pixels from the top of the dashboard.

- dashboard: sales_overview
  tile_size: 100
  ...

  elements:
  - name: orders_by_date
    top: 4
    ...

left

The left parameter defines the left-to-right position of an element, in units of tile_size, for layout: static dashboards.

For example, the following code specifies tile_size: 100 and left: 4, positioning the left edge of the orders_by_date element 400 pixels from the left side of the dashboard.

- dashboard: sales_overview
  tile_size: 100
  ...

  elements:
  - name: orders_by_date
    left: 4
    ...

row

For layout: newspaper dashboards, the row parameter defines the row that the top edge of an element is placed on.

A dashboard begins with row 0 at the top of the dashboard. A dashboard with newspaper layout defaults to an element height of 6 rows, meaning the dashboard elements at the top of a dashboard (row: 0) would default to taking up rows 0-5.

Each row is 50 pixels tall, which means the default element height of 6 rows is 300 pixels.

For example, the following code sets an element to be set on the second row of elements in the dashboard, assuming elements are set at the default height:

- dashboard: sales_overview
  layout: newspaper
  ...

  elements:
  - name: orders_by_date
    row: 6
    ...

col

For layout: newspaper dashboards, the col parameter defines the column that the left edge of the element is placed on.

Dashboards are divided into 24 columns. A dashboard begins with column 0 at the left of the dashboard. A dashboard with newspaper layout defaults to an element width of 8 columns, meaning the dashboard elements at the left of a dashboard (col: 0) would default to taking up columns 0-7.

For example, the following code sets an element to be set in the third column of elements in the dashboard:

- dashboard: sales_overview
  layout: newspaper
  ...

  elements:
  - name: orders_by_date
    col: 16
    ...

refresh

This section refers to the refresh parameter that is part of a dashboard element.

refresh can also be used as part of a dashboard, described on the Dashboard parameters documentation page.

The refresh parameter allows an element to reload automatically on some periodic basis, thereby retrieving fresh data. This is often helpful in settings where a dashboard is constantly displayed, such as on an office TV. Note that the dashboard must be open in a browser window for this parameter to have an effect. This setting does not run in the background to "pre-warm" the dashboard cache.

The refresh rate can be any number (without decimals) of seconds, minutes, hours, or days. For example:

- name: orders_by_date
  refresh: 2 hours

Use caution when setting short refresh intervals. If the query behind the element is resource-intensive, certain elements may strain your database more than desired.

note_state

The note_state parameter defines whether a note will be collapsed or expanded if it is too big to fit on a single row within the element's width. If you choose collapsed and the note is too long, the note will end in a clickable ellipsis (...) that can be used to read the full note. If you choose expanded and the note is long, the note will run onto additional lines.

note_display

The note_display parameter defines where a note is displayed on an element. above places the note at the top of an element, below places it at the bottom of an element, and hover requires the user to hover their mouse over a ? icon to see the note.

note_text

The note_text parameter specifies the text displayed in an element note.

Query parameters

When defining a LookML dashboard element, you must specify values for at least the model and explore query parameters, and at least one field must be specified using the dimensions parameter, the measures parameter, or the fields parameter. You can also use the other query parameters that are described in this section to control the way data is displayed in a dashboard element.

model

The model parameter defines the model to use for the element query. If unspecified, it will default to the model where the dashboard resides.

- name: orders_by_date
  model: ecommerce

The model parameter accepts LookML constants. You can define a constant in the manifest file for your project, then use the syntax "@{constant_name}" to set the constant as the value for model. Using a constant lets you define the name of a model in one place, which is particularly useful if you're updating the name of a model that is used by multiple dashboard elements.

For more information and an example of using constants with LookML dashboards, see the constant parameter documentation page.

explore

This section refers to the explore parameter that is part of a dashboard element.

explore can also be used as part of a model, described on the explore parameter documentation page.

explore can also be used as part of a dashboard filter, described on the Dashboard parameters documentation page.

The explore parameter defines the Explore to use for the element query.

- name: orders_by_date
  explore: order

The explore parameter accepts LookML constants. You can define a constant in the manifest file for your project, then use the syntax "@{constant_name}" to set the constant as the value for explore. Using a constant lets you define the name of an Explore in one place, which is particularly useful if you're updating the name of an Explore that is used by multiple dashboard elements.

For more information and an example of using constants with LookML dashboards, see the constant parameter documentation page.

fields

The fields parameter defines the fields to use for the element query. Use the syntax view_name.dimension_name to specify the fields.

## single field example
- name: orders_by_date
  fields: order.order_date

## multiple fields example
- name: orders_by_date
  fields: [order.order_date, order.order_count]

If you use the fields parameter, you do not need to use the dimensions and measures parameters.

dimensions

The dimensions parameter defines the dimension or dimensions to use for the element query. Use the syntax view_name.dimension_name to specify the dimension. Don't include dimensions if the query doesn't have any.

## single dimension example
- name: orders_by_date
  dimensions: order.order_date

## multiple dimension example
- name: orders_by_date
  dimensions: [order.order_date, customer.name]

measures

The measures parameter defines the measure or measures to use for the element query. Use the syntax view_name.measure_name to specify the measure. Don't include measures if the query doesn't have any.

## single measure example
- name: orders_by_date
  measures: order.count

## multiple measure example
- name: orders_by_date
  measures: [order.count, order_item.count]

sorts

The sorts parameter defines the sorts to be used for the element query. The primary sort is listed first, then the secondary sort, and so on. Use the syntax view_name.field_name to specify the dimension or measure. Don't include sorts if you want to use Looker's default sort order. Descending sorts are suffixed with desc; ascending sorts don't need a suffix.

## single sort example
- name: orders_by_date
  sorts: order.order_date desc

## multiple sort example
- name: orders_by_date
  sorts: [order.order_date desc, customer.name]

pivots

The pivots parameter defines the dimensions that should be pivoted for the element query. Use the syntax view_name.dimension_name to specify the dimension. Don't include pivots if the query doesn't have any.

## single pivot example
- name: orders_by_date
  pivots: customer.gender

## multiple pivot example
- name: orders_by_date
  pivots: [customer.gender, customer.age_tier]

fill_fields

The fill_fields parameter defines the dimensions that utilize the dimension fill option. Use the syntax view_name.dimension_name to specify the dimensions.

- name: orders_by_date
  fill_fields: [orders.created_date, orders.shipped_date]

subtotals

The subtotals parameter defines the dimensions that utilize the subtotals option. Use the syntax view_name.dimension_name to specify the dimensions.

subtotals: [products.department, distribution_centers.name]

total

The total parameter sets whether a totals row is shown at the bottom of the table. See Displaying totals for more information.

total: true | false

## default value: false

row_total

The row_total parameter sets whether a totals column is shown on the right or left of the table. Only works if a pivot is present. See Displaying Totals for more information.

row_total: right | left | false

## default value: false

limit

The limit parameter defines the row limit that should be used for the element query. The limit applies to the number of rows before any pivots are applied.

- name: orders_by_date
  limit: 100

column_limit

The column_limit parameter defines the column limit that should be used for the element query. The limit applies to the number of columns after any pivots are applied.

- name: orders_by_date
  column_limit: 100

filters

This section refers to the filters parameter that is part of a dashboard element.

filters can also be used as part of a dashboard, described on the Dashboard parameters documentation page.

filters can also be used as part of a measure, described on the filters parameter documentation page.

The filters parameter defines the non-changeable filters that should be used for the element's query. If you would like filters that a user can change in the dashboard, you should set up the filters using filters for dashboards, then apply them to the elements using listen.

The syntax for filters is:

- name: element_name
  filters:
    orders.created_date: 2020/01/10 for 3 days
    orders.status: Shipped
    # You can create multiple filter statements

Each filter can accept a Looker filter expression or a value constant. You can also use the _localization or _user_attributes Liquid variables in the filter expression for flexible filter values.

filter_expression

The filter_expression parameter defines a non-changeable custom filter for the element's query. If you would like filters that a user can change in the dashboard, you should set up the filters using filters for dashboards, then apply them to the elements using listen.

- name: element_name
  filter_expression:
  - diff_days(${users.created_date},${user_order_facts.first_order_date}) > 60

The Looker filter expressions documentation page lists the Looker filter expressions.

listen

Dashboard filters let viewers interactively refine the data that is shown in dashboard elements. Define dashboard filters with the filters parameter for LookML dashboards. Then, use the listen parameter to link dashboard elements to the dashboard filter.

The syntax for listen is as follows:

- name: element_name
  listen:
    filter_name_goes_here: dimension or measure on which to apply
                           the filter using view_name.field_name syntax
    # You can add more than one listen statement

Add the listen parameter to an element, and then provide the name of the filter followed by a colon and a reference to the field to which the filter should apply, using the view_name.field_name syntax. For example, you might create a filter called Date that requires a user to enter a date into the filter field in the UI. You could then apply the value that the user enters to the orders_by_date element like this:

- dashboard: sales_overview
  ...

  filters:
  - name: date
    type: date_filter

  elements:
 - name: orders_by_date
    listen:
      date: order.order_date
    ...

For additional examples of using the filters parameter and the listen parameter to apply dashboard filters to individual dashboard elements, see Building LookML dashboards.

query_timezone

The query_timezone parameter specifies the time zone in which the query will be run. The time zone options are shown on the Values for timezone documentation page. If you want the query to run using the viewer's time zone, you can assign the value as user_timezone.

- name: orders_by_date
  query_timezone: America/Los Angeles

- name: orders_by_customer
  query_timezone: user_timezone

analysis_config

The analysis_config parameter and its subparameters describe any query analysis to use with the visualization, starting in Looker 21.14. The Forecasting Labs feature must be enabled to perform analyses on visualizations.

The following subparameters can be used to define analyses:

You can create a forecast using a syntax like this:


  analysis_config:
    - forecasting:
      confidence_interval: 0.95
      field_name: orders.count
      forecast_n: 14
      forecast_interval: day
      seasonality: 7

forecasting

forecasting is an analysis type that applies a forecast to a visualization. Forecasting lets analysts quickly add data projections to new or existing Explore queries to help users predict and monitor specific data points.

For more information, see the Forecasting in visualizations documentation page.

To add forecasts to visualizations, the Forecasting Labs feature must be enabled.

confidence_interval

confidence_interval sets the bounds of the forecasted data values, which are input as decimal expressions of percentages. confidence_interval is optional and is blank by default.


confidence_interval: 0.99 | 0.98 | 0.95 | 0.90 | 0.80

See the Prediction interval section on the Forecasting in visualizations documentation page.

To add forecasts to visualizations, the Forecasting Labs feature must be enabled.

field_name

field_name specifies the names of measures — up to five — to include in forecasts.


field_name: view_name.field_name

forecast_n

forecast_n specifies the length of the forecast.


forecast_n: N # An integer that represents the length of the forecast

See the Length section on the Forecasting in visualizations documentation page.

To add forecasts to visualizations, the Forecasting Labs feature must be enabled.

forecast_interval

forecast_interval sets the duration interval for which to forecast data values. forecast_interval is automatically populated based on the timeframe dimension in the Explore query.


forecast_interval: day | month # a timeframe with dimension fill

See the Length documentation page.

To add forecasts to visualizations, the Forecasting Labs feature must be enabled.

seasonality

seasonality lets analysts account for known cycles or repetitive data trends in a forecast. seasonality is optional and is blank by default.


seasonality: N # An integer that represents the number of rows over which a cycle or pattern repeats

The Automatic seasonality setting is represented as a blank seasonality value.

See the Seasonality section on the Forecasting in visualizations documentation page.

To add forecasts to visualizations, the Forecasting Labs feature must be enabled.

merged_queries

The merged_queries parameter lets you combine the results of multiple queries into a single dashboard element. Define each source query within the element's merged_queries parameter and use the join_fieldssubparameter to specify how the results should be merged.

The following sample LookML code creates a merged results element of type: looker_grid. In this example, the merged_queries parameter is used to create a dashboard element that combines data from two separate queries into a single table chart:

- name: merged_results_element
  title: Merged Results Tile
  type: looker_grid
  merged_queries:
  - model: ecommerce
    explore: users
    type: table
    fields: [users.state, users.count, users.city]
    sorts: [users.count desc 0]
    limit: 5000
    column_limit: 50
    query_timezone: UTC
    listen:
    - State: users.state
  - model: ecommerce
    explore: users
    type: table
    fields: [users.state, users.city]
    sorts: [users.state]
    limit: 500
    column_limit: 50
    query_timezone: UTC
    join_fields:
    - field_name: users.state
      source_field_name: users.state
    - field_name: users.city
      source_field_name: users.city
    listen:
    - State: users.state

In this example, the dashboard element combines data from two source queries that are based on the users Explore in the ecommerce model. The primary query includes the users.state, users.count, and users.city fields, and it sorts the results by the users.count field. The second source query includes the users.state and users.city fields and sorts the results by the users.state field.

The join_field parameter merges the source queries based on matching values in the users.state and users.city fields.

The listen parameter applies a State filter to both queries, which lets dashboard viewers refine the query results that are displayed in the dashboard tile by selecting a specific state.

Example: Merging company data

Suppose you want to create a merged query that combines information about companies from two different Explores: company_info and companies. You want to join the queries on the ipo.stock_symbol, companies.name, and companies.contact_email fields from each Explore to create a query that returns results for company name, company contact email, IPO year, stock symbol, number of employees, and job count. You can define the merged query element in LookML as follows:

- name: merged_results_element
  title: Merged Results Tile
  merged_queries:
  - model: market_research
    explore: company_info
    fields: [companies.name, companies.contact_email, ipo.public_year, ipo.stock_symbol]
    filters:
      companies.contact_email: "-NULL"
      ipo.valuation_amount: NOT NULL
    sorts: [ipo.public_year desc]
  - model: company_data
    explore: companies
    fields: [companies.name, ipo.stock_symbol, companies.contact_email,
      companies.number_of_employees, jobs.job_count]
    filters:
      companies.number_of_employees: NOT NULL
      ipo.stock_symbol: "-NULL"
      companies.contact_email: "-NULL"
    sorts: [jobs.job_count desc]
    join_fields:
    - field_name: ipo.stock_symbol
      source_field_name: ipo.stock_symbol
    - field_name: companies.name
      source_field_name: companies.name
    - field_name: companies.contact_email
      source_field_name: companies.contact_email

Applying filters to merged query elements

The previous example of a merged query element demonstrates how to apply hard-coded filters directly within each source query by using the filters parameter. For example, the filters companies.contact_email: "-NULL" and ipo.valuation_amount: NOT NULL in the primary query restrict the results to companies that have valid contact emails and valuations. These query-level filters pre-filter the data before merging the queries and cannot be changed by the user.

You can also apply dashboard filters to merged query elements by using the listen parameter within the definition of each source query. For example, suppose you have a dashboard filter named Industry that you defined at the dashboard level by using the filters parameter for LookML dashboards:

filters:
- name: Industry
  title: Industry
  type: field_filter
  ui_config:
    type: dropdown_menu
    display: inline
  model: market_research
  explore: company_info
  field: companies.industry

To apply the Industry filter to the companies.industry field in both source queries, add the listen parameter to each of the merged query's source query definitions as follows:

listen:
  Industry: companies.industry

For example, the following sample code adds the Industry filter to both source queries in the merged results element from the previous example.

- name: merged_results_element
  title: Merged Results Tile
  merged_queries:
  - model: market_research
    explore: company_info
    fields: [companies.name, companies.contact_email, ipo.public_year, ipo.stock_symbol]
    filters:
      companies.contact_email: "-NULL"
      ipo.valuation_amount: NOT NULL
    sorts: [ipo.public_year desc]
    listen:
      Industry: companies.industry
  - model: company_data
    explore: companies
    fields: [companies.name, ipo.stock_symbol, companies.contact_email,
      companies.number_of_employees, jobs.job_count]
    filters:
      companies.number_of_employees: NOT NULL
      ipo.stock_symbol: "-NULL"
      companies.contact_email: "-NULL"
    sorts: [jobs.job_count desc]
    join_fields:
    - field_name: ipo.stock_symbol
      source_field_name: ipo.stock_symbol
    - field_name: companies.name
      source_field_name: companies.name
    - field_name: companies.contact_email
      source_field_name: companies.contact_email
    listen:
      Industry: companies.industry

With this addition, when a user interacts with the Industry dashboard filter, the corresponding source query in the merged query element will be filtered accordingly.

Column parameters

The following parameters correspond to the ability to move and pin columns in table charts.

auto_size_all_columns

The auto_size_all_columns parameter autosizes each table column to the width of its column heading or longest data value, whichever is wider. This parameter overrides the series_column_widths and size_to_fit parameters, if they are defined.

- name: orders_by_date
  auto_size_all_columns: true

column_order

The column_order parameter defines the order of the columns in the table chart.

- name: orders_by_date
  column_order: [customer.city, customer.state, customer.count]

pinned_columns

The pinned_columns parameter defines any columns that are pinned to the left of the table chart.

- name: orders_by_date
  pinned_columns:
    orders.created_date: left
    distribution_centers.name: left

Plot parameters

The following parameters correspond to the options in the Plot menu of the visualization editor for table charts.

table_theme

Use the table_theme parameter to apply one of the following table coloring options to a table element:

  • editable: The table has blue dimensions, orange measures, and green table calculations.
  • white: The table header is white, the data rows alternate between white and gray, and the text is black.
  • gray: The table header is gray, the data rows alternate between white and light gray, and the text is dark gray.
  • transparent: The table header is totally transparent, the data rows alternate between totally transparent and translucent gray, and the text color adjusts itself from black to white as needed according to the background color that shows through. Setting table_theme to transparent can be useful when you're using a customized embedded dashboard so that the tile background color shows through the visualization.
  • unstyled: The table header and data rows are white, and the text is black.

table_theme: editable | white | gray | transparent | unstyled

show_row_numbers

The show_row_numbers parameter sets whether a row number will be displayed at the beginning of each table row.


show_row_numbers: true | false

hide_totals

If your Explore includes column totals, hide_totals sets whether the visualization displays the totals.


hide_totals: true | false

hide_row_totals

If your Explore includes row totals, hide_row_totals sets whether the row totals will display in the visualization.


hide_row_totals: true | false

transpose

The transpose parameter lets you transpose table rows into columns. It accepts true or false.

- name: orders_by_date
  transpose: true

hidden_fields

The hidden_fields parameter indicates which fields, if any, are used in the query but hidden in the chart. Any hidden fields will appear in the data table section of an Explore.

hidden_fields: [inventory_items.count, distribution_centers.id]

limit_displayed_rows

The limit_displayed_rows parameter lets you show or hide rows in a visualization, based on their position in the results. For example, if your visualization displays a 7-day rolling average, you may want to hide the first 6 rows. Setting this to true lets you specify the values and positions in the visualization to which this applies using the limit_displays_rows_values parameter and its subparameters.

limit_displayed_rows: true
limit_displayed_rows_values:
  show_hide: hide | show
  first_last: first | last
  num_rows: '10'

limit_displayed_rows_values

Use the limit_displayed_rows_values parameter, and its subparameters show_hide, first_last, and num_rows, with limit_displayed_rows to specify which rows to show or hide in a visualization. See the limit_displayed_rows section for sample usage.

show_hide

The show_hide subparameter sets whether to hide certain rows from the visualization. Set show_hide to show to display only a limited number of rows in the visualization, and set show_hide to hide to exclude certain rows from the visualization.

first_last

The first_last subparameter sets whether the rows to be hidden or shown will be the first or last rows in the result set. Setting first_last to first shows or hides the first rows, while set first_last to last shows or hides the last rows.

num_rows

The num_rows subparameter sets the number of rows to be hidden or shown. For example, num_rows: '10' will show or hide either the first or last 10 rows of the result set from the visualization.

Series parameters

The following parameters correspond to the options in the Series menu of the visualization editor for table charts.

truncate_text

The truncate_text parameter sets whether column headers and text inside data cells should be shortened with an ellipsis (…).


truncate_text: true | false

show_view_names

The show_view_names parameter determines whether view names are displayed in chart labels, such as axis names and column names.

show_view_names: true | false

## default value: true

size_to_fit

The size_to_fit parameter sets whether to size the widths of all columns so that the table perfectly fits the width of the element in which it is being viewed. If the auto_size_all_columns parameter is set to true, it overrides size_to_fit.


size_to_fit: true | false

dynamic_fields

The dynamic_fields parameter and its subparameters describe any table calculations or custom fields to use with the visualization. You must have permission to create custom fields to add a description of up to 255 characters or to use calculation_type for custom groups or custom bins. You must have permission to create table calculations to add a description of up to 255 characters to table calculations or to use calculation_type for shortcut calculations.

The following subparameters can be used to define dynamic fields:

You can create a table calculation using a syntax like this:

dynamic_fields:
  - table_calculation: running_total
    label: Running Total of Items
    expression: running_total(${inventory_items.count})
    value_format_name: decimal_0
    description: your description of up to 255 characters here
    _kind_hint: measure
    _type_hint: number
    is_disabled: false

You can create shortcut calculations for several calculation types using a syntax like this:

dynamic_fields:
- category: table_calculation
  description: your description of up to 255 characters here
  label: Percent of Orders Count
  value_format:
  value_format_name: percent_0
  calculation_type: percent_of_column_sum
  table_calculation: percent_of_orders_count
  args:
  - orders.count
  _kind_hint: measure
  _type_hint: number
- category: table_calculation
  description: your description of up to 255 characters here
  label: Percent of previous - Orders Count
  value_format:
  value_format_name: percent_0
  calculation_type: percent_of_previous
  table_calculation: percent_of_previous_orders_count
  args:
  - orders.count
  _kind_hint: measure
  _type_hint: number
- category: table_calculation
  description: your description of up to 255 characters here
  label: Percent change from previous - Orders Count
  value_format:
  value_format_name: percent_0
  calculation_type: percent_difference_from_previous
  table_calculation: percent_change_from_previous_orders_count
  args:
  - orders.count
  _kind_hint: measure
  _type_hint: number
- category: table_calculation
  description: your description of up to 255 characters here
  label: Rank of Orders Count
  value_format: ## this field is optional
  value_format_name: ## this field is optional
  calculation_type: rank_of_column
  table_calculation: rank_of_orders_count
  args:
  - orders.count
  _kind_hint: measure
  _type_hint: number
- category: table_calculation
  description: your description of up to 255 characters here
  label: Running total of Orders Count
  value_format: ## this field is optional
  value_format_name: ## this field is optional
  calculation_type: running_total
  table_calculation: running_total_of_orders_count
  args:
  - orders.count
  _kind_hint: measure
  _type_hint: number

You can create a custom measure to use in your visualization using a syntax like this:

dynamic_fields:
  - measure: avg_sale_price
    label: Average Sale Price
    based_on: products.sale_price
    type: average
    value_format_name: usd
    description: your description of up to 255 characters here
    _kind_hint: measure
    _type_hint: number

You can create a filtered custom measure to use in your visualization using a syntax like this:

dynamic_fields:
  - measure: order_count_for_25_47_year_olds
    based_on: order_items.order_count
    type: count_distinct
    label: Order Count for 25- to 47-Year-Olds
    description: your description of up to 255 characters here
    value_format: 00#
    _kind_hint: measure
    _type_hint: number
    filter_expression: "${users.age} >= 25 AND ${users.age} <= 47"

You can create a custom dimension to use in your visualization using a syntax like this:

dynamic_fields:
  - dimension: user_city_state
    label: User City and State
    expression: concat(${users.city}, ", ", ${users.state})
    description: your description of up to 255 characters here
    _kind_hint: dimension
    _type_hint: string

You can create custom groups for a dimension to use in your visualization using a syntax like this:

  - category: dimension
  description: 'States by region'
  label: State Groups
  value_format: ## this field is optional
  value_format_name: ## this field is optional
  calculation_type: group_by
  dimension: state_groups
  args:
  - users.state
  - - label: Pacific Northwest
      filter: Oregon,Idaho,Washington
  - Other
  _kind_hint: dimension
  _type_hint: string

You can create custom bins for a dimension to use in your visualization using a syntax like this:

- category: dimension
  description: Order item sale prices, in tiers of 10
  label: Sale Price Bins
  value_format:
  value_format_name:
  calculation_type: bin
  dimension: sale_price_bins
  args:
  - order_items.sale_price
  - '10'
  - '0'
  - '100'
  -
  - classic
  _kind_hint: dimension
  _type_hint: string

You can add multiple dynamic fields to your element. You do not need to add table calculations to the fields parameter for them to appear in the visualization, but you do need to add other types of dynamic fields to fields in order for them to appear.

table_calculation

If you are defining a table calculation, the table_calculation subparameter names the table calculation. This is the name to use when you reference the table calculation in LookML.

measure

The measure subparameter defines the name for a custom measure or a filtered custom measure. This is the name you use to reference the measure in LookML.

dimension

The dimension subparameter defines the name for a custom dimension. This is the name to use to reference the dimension in LookML.

label

The label subparameter defines the title of the dynamic field as you'd like it to appear in the visualization. This may be the same as or different than the name given in the table_calculation, measure, or dimension subparameters.

based_on

If you are using a custom measure or a filtered custom measure, the based_on subparameter identifies the measure it is based on, using the view_name.field_name sytax.

type

If you are using a custom measure, the type subparameter identifies the type of aggregation. It accepts count_distinct, sum, average, min, max, or median.

description

You can add a description of up to 255 characters to any custom field or table calculation with the description subparameter. Looker displays the description when the user clicks on the information icon to the right of the field name in the field picker, and when the user hovers over the column name in a table or table chart visualization in an Explore, a dashboard, or a Look.

expression

If you are using a table calculation, the expression subparameter defines the Looker expression used to create the table calculation.

filter_expression

If you are using a custom filtered measure, the filter_expression subparameter defines the Looker expression used to filter the measure.

value_format

The optional value_format subparameter defines the value format for a dynamic field when you're using custom formatting. If you want to use a default Looker format, use value_format_name instead.

value_format_name

The optional value_format_name subparameter applies a default format to the dynamic field. If you want to use a custom format, use value_format instead.

calculation_type

The calculation_typesubparameter defines the type of Shortcut Calculation or Group function to create a table calculation, or to create a custom group for a dimension:

Custom fields calculation_type options:

  • group_by — Groups dimension values under custom fixed labels, based on a specified custom condition. Similar to CASE WHEN in SQL, or the LookML case field parameter.
  • bin — Groups values in custom bins, or tiers, for numeric type dimensions and custom dimensions. Similar to the LookML tier dimension type.

Table calculations calculation_type options:

  • percent_of_column_sum — A row value divided by the sum of values in the column. This calculation only includes values that are in the data table when the query row limit has been reached.
  • percent_of_previous — A current row's value divided by the value of the following row.
  • percent_difference_from_previous — The difference between the current row's value and the value of the following row, divided by the value of the following row.
  • rank_of_column — The rank of a row's value among all values in the column. This calculation only includes values that are in the data table when the query row limit has been reached.
  • running_total — The cumulative sum of the current row's value and all previous row values in the column.
  • percent_of_previous_column — For pivoted fields, the current column's value divided by the value of the column to its left.
  • percent_change_from_previous_column — For pivoted fields, the difference between the current column's value and the value of the column to the left, divided by the value of the column to the left.
  • percent_of_row — For pivoted fields, the percent of the current column's value divided by the row sum of that field.
  • running_row_total — For pivoted fields, the cumulative sum of the current column and all previous columns in this row.

args for custom groups

If you are using custom groups for a dimension, args specifies the arguments for applying fixed labels to dimension values. args takes the following format:

args:
- view_name.field_name
  - label: specified custom label
    filter: condition for values
  - label: another specified custom label
    filter: a different condition for values
- Other ## An optional customizable group label for values that do not meet specified conditions.

You can add as many label and filter conditions as needed, depending on the number of groups desired.

See the previous example for reference.

args for custom bins

If you are using custom bins for a numeric dimension, args specifies the arguments for applying fixed tiers to dimension values. args takes the following format:

  args:
  - view_name.field_name
  - bin_size ## The numeric interval on which to base each bin, in single quotes
  - min ## The numeric value of the minimum bin size, in single quotes
  - max ## The numeric value of the maximum bin size, in single quotes
  - override ## A value will only appear when a custom bin uses a Custom-sized bin type.
  - style ## The bin display style. Currently, only classic is supported.

See the previous example for reference.

args for shortcut calculations

The args subparameter is where you specify the names of the numeric fields that you are using for a Shortcut Calculation. An argument takes the following format:

- args:
  - view_name.field_name   ## the field on which the calculation is based

See the previous example for reference.

_kind_hint

The optional _kind_hint subparameter identifies whether the dynamic field returns a dimension or measure. It accepts the values dimension and measure.

_type_hint

The optional _type_hint subparameter identifies the data type the dynamic field's expression should produce.

is_disabled

The optional is_disabled subparameter specifies whether a table calculation appears in the visualization and its underlying Explore. It accepts the values true and false.

series_labels

Set the labels of one or more series based on the series name, using name: label pairs.

For a pivoted chart, the series names are the pivot names.

series_labels:
  'Yes': iOS Users
  'No': Android Users

For a chart with multiple measures, the series names are the measure field names.

series_labels:
  inventory_items.count: Inventory
  orders.count: Orders

series_column_widths

Set the widths of one or more columns based on the series name. If the auto_size_all_columns parameter is set to true, it overrides series_column_widths.

series_column_widths:
  order_times.shipping_time: 50
  orders.count: 60

series_cell_visualizations

Specify whether one or more columns use the Cell Visualization option by indicating series name using the view_name.field_name format. series_cell_visualizations has the subparameters is_active, palette, and value_display.

series_cell_visualizations:
  order_items.count:
    is_active: true
    palette:
      palette_id: my-custom-colors-sequential-0
      collection_id: my-custom-colors
    value_display: true

is_active

The optional is_active subparameter accepts true or false to indicate whether bar visualizations are enabled for that series. If is_active is not defined, it defaults to true.

palette

The palette subparameter is optional. If it is not used, the palette will default to a diverging palette in the instance's default color collection.

If palette is used, the child parameters palette_id and collection_id apply the colors from a specific palette to the bar visualizations. For palette_id, you must use the ID of a sequential or diverging palette. For more on palette IDs and color collection IDs, see the color_application section.

palette has an alternate child parameter, custom_colors, that sets two to five custom colors to use for the bars:

series_cell_visualizations:
  order_items.count:
    palette:
      custom_colors:
      - orange
      - "#0000ff"
      - red

value_display

The optional value_display subparameter accepts true or false to indicate whether the values for each data cell are shown along with the cell visualization. If value_display is not defined, it defaults to true.

series_text_format

The series_text_format parameter and its subparameters specify cell text layout for each column. The series to be formatted is indicated using the view_name.field_name syntax, and the subparameters describe the formatting.

All subparameters are optional; only use the ones you need.

  series_text_format:
    order_items.shipping_time:
      align: right
    order_items.shipped_date:
      align: center
      fg_color: "#EA8A2F"
      bg_color: "#64518A"
      bold: true
      italic: true

fg_color

The fg_color subparameter indicates the font color for cell text. The color value can take a hex string, such as #2ca6cd, or a CSS named color string, such as mediumblue.

bg_color

The bg_color subparameter indicates the cell background color. The color value can take a hex string, such as #2ca6cd, or a CSS named color string, such as mediumblue.

bold

The bold subparameter indicates whether the cell text is bold and accepts true or false.

italic

The italic subparameter indicates whether the cell text is italic and accepts true or false.

align

The align subparameter indicates the alignment of cell text and accepts left, center, or right.

series_collapsed

The series_collapsed parameter defines whether to collapse or expand the subtotals for a particular series. Identify the series using view_name.field_name syntax and true or false.

series_collapsed:
  users.city: false
  users.state: true

If the column is collapsed, the individual elements that make up the subtotal will be displayed by clicking the arrow on the left side of the data cell.

series_value_format

The series_value_format parameter specifies the formatting to apply to a series, independent of any formatting applied to the underlying dimension or measure. If series_value_format is not specified, the value is displayed in the format of the underlying dimension or measure.

Identify the series to be formatted using the view_name.field_name syntax.

The format_string subparameter lets you define the format for the series, using Excel-style formatting.

series_value_format:
  products.retail_price:
    format_string: "$#,##0.00"

You can also define the formatting like this:


series_value_format:
  order_items.count: "00#"

The formatting used in the format_string subparameter is the same as formatting used with the value_format LookML parameter. You can read about how to specify these formats on the Adding custom formatting to numeric fields documentation page.

Formatting parameters

The following parameters correspond to the options in the Formatting menu of the visualization editor for table charts.

color_application

The color_application parameter, and its subparameters collection_id and palette_id, can be used to apply a specific color collection and palette to a dashboard element. For an overview of Looker's native color collections, see the Color collections documentation page.

If you have the collection ID and palette ID for the palette you want to use, you can enter those IDs into the collection_id and palette_id subparameters. A collection ID or a palette ID may be an alphanumeric code or be based on the name of the color collection. Alphanumeric codes are used for Looker's native collections. They are instance-specific and look like this:


color_application:
  collection_id: 1297dk12-86a7-4xe0-8dfc-82de20b3806a
  palette_id: 93c8aeb7-3f8a-4ca7-6fee-88c3617516a1

Custom color collections use collection and palette IDs based on the name of the color collection, which are portable across instances and look like this:


color_application:
  collection_id: blue-tone-collection
  palette_id: blue-tone-collection-categorical-0

You can also use the UI to find the colors, collections, or palettes that you want and generate the LookML to add them to your dashboard. Navigate to a piece of user-defined content (like a Look, a dashboard, or an Explore), and apply the colors, collection, or palette that you want to that content's visualization using the UI. Once you've done that, you can follow the steps to get dashboard LookML, copy the LookML that was produced, and paste it in the color_application section.

header_font_color

The header_font_color parameter applies a font color to column headers.

The color value can take a hex string, such as #2ca6cd, or a CSS named color string, such as mediumblue.


header_font_color: purple

The default color depends on the table theme defined using the table_theme parameter.

header_background_color

The header_background_color parameter applies a color to the background column headers.

The color value can take a hex string, such as #2ca6cd, or a CSS named color string, such as mediumblue.


header_background_color: #add8e6

The default color depends on the table theme defined using the table_theme parameter.

header_text_alignment

The header_text_alignment parameter applies left, right, or center alignment to column headers.


header_text_alignment: center

The default alignment is left.

header_font_size

The header_font_size parameter applies a font size from 1 through 99 to column headers.


header_font_size: 16

The default size for header and row fonts is 12.

rows_font_size

The rows_font_size parameter applies a font size from 1 through 99 to text inside data cells, but not to column headers.


rows_font_size: 8

The default size for header and row fonts is 12.

enable_conditional_formatting

Setting enable_conditional_formatting to true lets you define rules that color code your table visualization, either on a scale or by specifying values of interest.


enable_conditional_formatting: true | false

conditional_formatting_include_totals

If enable_conditional_formatting is set to true, conditional_formatting_include_totals specifies whether totals are included in the color coding scheme.


conditional_formatting_include_totals: true | false

conditional_formatting_include_nulls

If enable_conditional_formatting is set to true, conditional_formatting_include_nulls specifies whether null values should be represented as zeroes.


conditional_formatting_include_nulls: true | false

conditional_formatting

With enable_conditional_formatting set to true, use the conditional_formatting parameter to define the rules that color code your table visualization. For each conditional formatting rule, you can specify settings with the following parameters:

The following is an example of a conditional formatting rule:


conditional_formatting: [{type: less than, value: 20, background_color: "#9fdee0",
  font_color: "#b15928", bold: true, italic: false, strikethrough: false,
  fields: [order_items.count], color_application: {collection_id: my-custom-colors,
  palette_id: my-custom-colors-sequential-0}}]

type

The type parameter specifies whether to color code values along a scale or based on a logical condition.

If you are color coding values on a scale, you can set type to along a scale....

If you are color coding values based on a logical condition, you can specify one of the following values for type, along with a value for value:

  • equal to: The rule applies to values equal to the number specified for value.
  • not equal to: The rule applies to values that are not equal to the number specified for value.
  • greater than: The rule applies to values that are greater than the number specified for value.
  • less than: The rule applies to values that are less than than the number specified for value.
  • between: The rule applies to values that are between the two numbers specified for value.
  • not between: The rule applies to values that are not between the two numbers specified for value.
  • 'null': The rule applies only to null values.
  • not null: The rule applies only to values that are not null.

type: along a scale... | equal to | not equal to | less than | between | not between | 'null' | not null

value

If you are color coding values based on a logical condition other than 'null' or not null, specify the value to which the rule applies. The value parameter takes a single number or, when type is set to between or not between, a set of two numbers.


value: N | [N, N]

background_color

If your color coding is based on a logical condition (type is set to anything other than along a scale...), use the background_color parameter to specify a background color for the values to which your rule applies.


background_color: "#49cec1"

font_color

If your color coding is based on a logical condition (type is set to anything other than along a scale...), use the font_color parameter to specify a font color for the values to which your rule applies.


font_color: "#1f3e5a"

color_application

The color_application parameter, and its subparameters collection_id, palette_id, and options, can be used to apply a specific color collection and palette to a conditional formatting rule.

You can add colors to a LookML dashboard by collection ID and palette ID, if you have them. You can also use the UI to find the colors you want and generate the LookML to add them to your dashboard. Navigate to a piece of user-defined content (like a Look, a dashboard, or an Explore), and apply the colors you want to that content's visualization using the UI. Once you've done that, you can follow the steps to get dashboard LookML, copy the LookML that was produced, and paste it in the color_application section. For an overview of Looker's predefined color collections, see the Color collections documentation page.

The options subparameter can be used when you have set type to along a scale.... It has the following child parameters:

  • steps: This parameter limits the number of colors used to the value given and separates the data into that number of groups. When this parameter is not used, the data is colored according to a gradient covering the entire palette. It accepts values from 2 through 100.
  • mirror: When set to true, this parameter applies equal color shifts on either side of the color palette for equal values on either side of a defined center point. It accepts true or false.
  • constraints: This parameter sets the data range that conditional formatting applies to and sets a center point to be used for palette application. It accepts the following syntax: constraints: {min: {type: number, value: 3}, max: {type: percentile, value: 99}, mid: {type: average}}
  • reverse: This parameter determines whether to reverse the color palette during color application. It accepts true or false.

bold

When color coding based on a logical condition, set whether to bold the values to which your rule applies.


bold: true | false

italic

When color coding based on a logical condition, set whether to italicize the values to which your rule applies.


italic: true | false

strikethrough

When color coding based on a logical condition, set whether to apply strikethrough formatting to the values for your rule.


strikethrough: true | false

fields

Specify the fields to which your rule should apply. By default, the rule applies to all numeric fields.


fields: [ view_name.field_name ]