Line Charts

Line charts are useful for showing trends and changes over time or across ordered categories. You can create separate lines for different groups using color, and apply styles and customizations like line width, markers, and annotations.

Writing prompts for Plotly Studio

You can create charts in Plotly Studio using natural language in different ways:

Ask a question - great for exploring your data:

Which factory produces the heaviest products?

Use a quick one-line prompt - concise and conversational:

Compare average weight by factory

Write structured detailed prompts - precise control and consistency:

Average Weight by Factory

Chart:
- Type: bar
- X: Factory location
- Y: Average weight

Data:
- Aggregation: average of weight by Factory location

Structured detailed prompts give you more control over chart type, data mappings, aggregations, and styling. Most examples on this page use this format.

Basic line example

Here's an example of how to structure a prompt to show how a value changes over time.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>

The following example shows the average weight over time using the built-in Plotly Studio dataset:

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Line chart example

Color by category

Create separate colored lines for different groups in your data to compare trends across categories.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>
- Color: <Column Name>

The following example uses this prompt structure with the weight, created_date, and defect columns from the built-in Plotly Studio dataset:

Average Weight Over Time by Defect

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Color: Defect

Data:
- Aggregation: average of weight by Created date (daily)

Line chart with color by category example

Control markers

Show or hide markers on your line chart to highlight individual data points along the line.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>

Chart styles:
- Hide markers # Or: Show markers

The following example uses this prompt structure with the weight and created_date columns from the built-in Plotly Studio dataset to show data points along the trend line

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Hide markers

Line chart with markers example

Sparklines

Sparklines are small, minimal line charts that show trends at a glance. Create sparklines by using separate rows for each category and hiding axes and gridlines.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>
- Facet rows: <Column Name>

Chart styles:
- Hide axes and gridlines
- Hide subplot labels

The following example uses this prompt structure with the weight, created_date, and factory_location columns from the built-in Plotly Studio dataset to create sparklines

Weight Trends by Factory Location

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Facet rows: Factory location

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Hide axes and gridlines
- Hide subplot labels

Sparklines example

Styled line plots

Customize the appearance of your line charts with colors and dash patterns.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>
- Color: <Column Name>

Chart styles:
- Use different dash patterns for each <Column Name>

The following example shows customized line styling using the built-in Plotly Studio dataset:

Product Weight Trends

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Color: Defect

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use different dash patterns for defect and no defect

Styled line chart example

Line shape interpolation

Control how lines connect data points using different interpolation methods like linear, spline (curved), or step patterns.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>

Chart styles:
- Use <line_shape> lines

SplineLinearHVVHHVHVHV

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use spline lines

Spline line chart

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use linear lines

Linear line chart

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use hv lines

HV line chart

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use vh lines

VH line chart

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use hvh lines

HVH line chart

Average Weight Over Time

Chart:
- Type: line
- X: Created date
- Y: Average weight

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Use vhv lines

VHV line chart

Adding annotations

Add text annotations to highlight specific points or trends in your line chart.

<Chart Title>

Chart:
- Type: line
- X: <Column Name>
- Y: <Column Name>
- Color: <Column Name>

Chart styles:
- Add annotation "<text>" at <location>

The following example shows an annotated line chart using the built-in Plotly Studio dataset:

Average Weight Over Time by Defect

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Color: Defect

Data:
- Aggregation: average of weight by Created date (daily)

Chart styles:
- Add annotation "Highest point" at the highest point

Line chart with annotations example

Interactive controls

Add dropdowns and other controls to make your line charts interactive. Controls let users filter and explore the data dynamically.

Average Weight Over Time by Defect

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Color: Defect

Data:
- Aggregation: average of weight by Created date (daily)

Options:
- Dropdown to select factory (All, Osaka, Seoul, Singapore, Los Angeles, Montreal, Randstad) - Default All
- Date range picker to filter by date range - Default last 90 days

Line chart with interactive controls

Prompt keywords reference

Use these keywords and phrases in your prompts to customize your line chart.

Chart

Use a Chart: section in your prompt to define the basic structure of your line chart, including the chart type and how columns map to visual properties.

Chart:
- Type: line
- X: Created date
- Y: Average weight
- Color: Factory location
- Facet columns: Defect

Here are some keyword suggestions to use in this section:

Keyword/Phrase	Description	Example
Type	Specify the chart type as line	`Type: line`
X	The column to show on the horizontal axis	`X: Created date`
Y	The column to show on the vertical axis	`Y: Average weight`
Color	Create separate colored lines for different groups	`Color: Factory location`
Facet rows	Create multiple plots stacked vertically by group	`Facet rows: Factory location`
Facet columns	Create multiple plots side-by-side by group	`Facet columns: Defect`

Data

Use a Data: section in your prompt to specify how to transform, filter, or aggregate your data before visualization.

Data:
- Aggregation: average of weight by Created date
- Computed field: Shipping days calculated as the difference between Shipped date and Created date in days

Here are some keyword suggestions to use in this section:

Keyword/Phrase	Description	Example
Aggregation	Specify how to aggregate data	`Aggregation: average of weight by Created date`
Computed field	Create new calculated fields from existing data	`Computed field: Shipping days calculated as the difference between Shipped date and Created date in days`
Filter	Filter data to show only specific records	`Filter to show only defect = true`

Options

Use an Options: section in your prompt to add interactive controls that allow users to dynamically filter, transform, and visualize data without regenerating the chart.

Options:
- Dropdown to select factory (All, Osaka, Seoul, Singapore) - Default All
- Date range picker to filter by date range - Default last 90 days

Here are some keyword suggestions to use with this section. See Chart Controls for a complete list of control types and additional examples.

Keyword/Phrase	Description	Example
Dropdown	Add a dropdown menu to filter by categories	`Dropdown to select factory (All, Osaka, Seoul) - Default All`
Date range picker	Add a date range selector	`Date range picker to filter by date range - Default last 90 days`

Chart styles

Use a Chart styles: section in your prompt to control the visual appearance and formatting of your line chart.

Chart styles:
- Use custom colors: #FF5733, #33FF57
- Set line width to 3
- Use spline lines
- Show markers

Here are some keyword suggestions to use in this section:

Keyword/Phrase	Description	Example
Custom colors	Specify exact colors for lines	`Use custom colors: #FF5733, #33FF57`
Hover text	What to show when hovering over points	`Show Serial number on hover`
Axis labels	Customize the text shown on the axes	`Label x-axis as "Production Date"` `Label y-axis as "Average Weight (kg)"`
Background color	Set the background color of the plot	`Set background color to lightgray`
Grid lines	Show or hide grid lines on the plot	`Hide grid lines`
Color scale	Specify color scale for continuous color mapping. See built-in color scales	`Use Viridis color scale`
Line width	Set the thickness of the line	`Set line width to 3`
Dash patterns	Use different line styles (solid, dashed, dotted)	`Use different dash patterns for each defect`
Line shape	Control how lines connect points (linear, spline, step)	`Use spline lines`
Markers	Show or hide markers on the line to highlight data points	`Show markers` `Hide markers`
Marker size	Set a fixed size for all markers	`Set marker size to 12`
Marker symbol	Set a specific shape for all markers. See marker style options	`Use square markers`
Marker opacity	How see-through the markers are (0=invisible, 1=solid)	`Set marker opacity to 0.5`
Text on points	Display text labels directly on data points	`Show Average weight as text on points`
Logarithmic scale	Use log scale for large ranges (useful for exponential data)	`Use logarithmic scale for the y-axis`
Axis range	Set minimum and maximum values for axes	`Set x-axis range from 0 to 100`
Legend	Control legend display and position	`Show legend at top right`
Annotations	Add text labels to highlight specific points or trends	`Add annotation "Highest point" at the highest point`