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.

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.

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.

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.

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.

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.

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.

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.

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