Lakeview dashboard visualization types

This article outlines the types of visualizations available to use in Lakeview dashboards, and shows you how to create an example of each visualization type. For a Lakeview dashboard quickstart, see Create and share visualizations using Lakeview dashboards.

Note

To optimize performance, charts can only render 10k elements on the canvas. Otherwise, visualizations may be truncated.

Bar visualization

Bar visualizations represent the change in metrics over time or to show proportionality, similar to a pie visualization.

Bar visualization example

Configuration values: For this bar visualization example, the following values were set:

  • Title: Total price and order month by order priority and clerk

  • X axis:

    • Field: o_orderdate

    • Transform: Monthly

    • Scale Type: Temporal

    • Axis title: Order month

  • Y axis:

    • Field: o_totalprice

    • Scale Type: Quantitative

    • Transform: Sum

    • Axis title: Total price

  • Group by:

    • Field: o_orderpriority

    • Legend title: Order priority

  • Filter

    • Field: TPCH orders.o_clerk

SQL query: For this bar visualization, the following SQL query was used to generate the data set named TPCH orders.

SELECT * FROM samples.tpch.orders

Line visualization

Line visualizations present the change in one or more metrics over time.

Line visualization example

Configuration values: For this line visualization example, the following values were set:

  • Title: Average price and order year by order priority and clerk

  • X axis:

    • Field: o_orderdate

    • Transform: Yearly

    • Scale Type: Temporal

    • Axis title: Order year

  • Y axis:

    • Field: o_totalprice

    • Transform: Average

    • Scale Type: Quantitative

    • Axis title: Average price

  • Group by:

    • Field: o_orderpriority

    • Legend title: Order priority

  • Filter

    • Field: TPCH orders.o_clerk

SQL query: For this bar visualization visualization, the following SQL query was used to generate the data set named TPCH orders.

SELECT * FROM samples.tpch.orders

Area visualization

Area visualizations combine the line and bar visualizations to show how one or more groups’ numeric values change over the progression of a second variable, typically that of time. They are often used to show sales funnel changes through time.

Area visualization example

Configuration values: For this area visualization example, the following values were set:

  • Title: Total price and order year by order priority and clerk

  • X axis:

    • Field: o_orderdate

    • Scale Type: Temporal

    • Transform: Yearly

    • Axis title: Order year

  • Y axis:

    • Field: o_totalprice

    • Axis title: Total price

    • Scale Type: Quantitative

    • Transform: Sum

  • Group by:

    • Field: o_orderpriority

    • Legend title: Order priority

  • Filter

    • Field: TPCH orders.o_clerk

SQL query: For this area visualization, the following SQL query was used to generate the data set named TPCH orders.

SELECT * FROM samples.tpch.orders

Pie visualization

Pie visualizations show proportionality between metrics. They are not meant for conveying time series data.

Pie visualization example

Configuration values: For this pie visualization example, the following values were set:

  • Title: Total price by order priority and clerk

  • Angle:

    • Field: o_totalprice

    • Transform: Sum

    • Axis title: Total price

  • Group by:

    • Field: o_orderpriority

    • Legend title: Order priority

  • Filter

    • Field: TPCH orders.o_clerk

SQL query: For this pie visualization, the following SQL query was used to generate the data set named TPCH orders.

SELECT * FROM samples.tpch.orders

Scatter visualization

Scatter visualizations are commonly used to show the relationship between two numerical variables. Additionally, a third dimension can be encoded with color to show how the numerical variables are different across groups.

Scatter example

Configuration values: For this scatter visualization example, the following values were set:

  • Title: Total price and quantity by ship mode and supplier

  • X axis:

    • Field: l_quantity

    • Axis title: Quantity

    • Scale type: Quantitative

    • Transform: None

  • Y axis:

    • Field: l_extendedprice

    • Scale type: Quantitative

    • Transform: None

    • Axis title: Price

  • Group by:

    • Field: l_shipmode

    • Legend title: Ship mode

  • Filter

    • Field: TPCH lineitem.l_supplierkey

SQL query: For this scatter visualization, the following SQL query was used to generate the data set named TPCH lineitem.

SELECT * FROM samples.tpch.lineitem

Counter visualization

Counters display a single value prominently, with an option to compare them against a target value. To use counters, specify which row of data to display on the counter visualization for the Value Column and Target Column.

Counter example

Configuration values: For this counter visualization example, the following values were set:

  • Title: Orders: Target amount vs. actual amount by date

  • Value:

    • Field: avg(o_totalprice)

    • Value row number: 1

  • Target:

    • Field: avg(o_totalprice)

    • Value row number: 2

  • Filter

    • Field: TPCH orders.o_orderdate

SQL query: For this counter visualization, the following SQL query was used to generate the data set named TPCH orders_target.

SELECT o_orderdate, avg(o_totalprice)
FROM samples.tpch.orders
GROUP BY 1
ORDER BY 1

Table visualization

The table visualization displays data in a standard table, but with the ability to manually reorder, hide, and format the data.

Table example

Configuration values: For this table visualization example, the following values were set:

  • Title: Line item summary by supplier

  • Columns:

    • Display row number: Enabled

    • Field: l_orderkey

    • Field: l_extendedprice

      • Display as: Number

      • Number format: $0.00

    • Field: l_discount

      • Display as: Number

      • Number format: %0.00

    • Field: l_tax

      • Display as: Number

      • Number format: %0.00

    • Field: l_shipdate

    • Field: l_shipmode

  • Filter

    • Field: TPCH lineitem.l_supplierkey

SQL query: For this table visualization, the following SQL query was used to generate the data set named TPCH lineitem.

SELECT * FROM samples.tpch.lineitem

Pivot visualization

A pivot visualization aggregates records from a query result into a tabular display. It’s similar to PIVOT or GROUP BY statements in SQL. You configure the pivot visualization with drag-and-drop fields.

Note

For performance reasons, pivot tables only support rendering 100 columns x 100 rows.

Pivot example

Configuration values: For this pivot visualization example, the following values were set:

  • Title: Line item quantity by return flag and ship mode by supplier

  • Rows:

    • Field: l_returnflag

  • Columns:

    • Field: l_shipmode

  • Cell

    • Dataset:

    • Field: l_quantity

    • Transform: Sum

  • Filter

    • Field: TPCH lineitem.l_supplierkey

SQL query: For this pivot visualization, the following SQL query was used to generate the data set named TPCH lineitem.

SELECT * FROM samples.tpch.lineitem