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.

Basic line example

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

Create a line chart of <Y> over <X>.

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

Create a line chart of average weight by created date (daily).

Color by category

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

Create a line chart of <Y> over <X>, color by <Column>.

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

Create a line chart of average weight by created date (daily), color by defect.

Control markers

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

Create a line chart of <Y> over <X>. Hide 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:

Create a line chart of average weight by created date (daily). Hide markers.

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.

Create a line chart of <Y> over <X>.
Facet vertically by <Column>.
Hide axes, gridlines, and 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:

Create a line chart of average weight by created date (daily).
Facet vertically by factory location.
Hide axes, gridlines, and subplot labels.

Styled line plots

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

Create a line chart of <Y> over <X>, color by <Column>.
Use different dash patterns for each <Column>.

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

Create a line chart of average weight by created date (daily), color by defect.
Use different dash patterns for defect and no defect.

Line shape interpolation

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

Create a line chart of <Y> over <X>. Use <line_shape> lines.

SplineLinearHVVHHVHVHV

Create a line chart of average weight by created date (daily).
Use spline lines.

Create a line chart of average weight by created date (daily).
Use linear lines.

Create a line chart of average weight by created date (daily).
Use hv lines.

Create a line chart of average weight by created date (daily).
Use vh lines.

Create a line chart of average weight by created date (daily).
Use hvh lines.

Create a line chart of average weight by created date (daily).
Use vhv lines.

Adding annotations

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

Create a line chart of <Y> over <X>, color by <Column>.
Add annotation "<text>" at <location>.

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

Create a line chart of average weight by created date (daily), color by defect.
Add annotation "Highest point" at the highest point.

Interactive controls

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

Create a line chart of average weight by created date (daily), color by defect.
Add a dropdown to select factory
(All, Osaka, Seoul, Singapore, Los Angeles, Montreal, Randstad) - Default All.
Add a date range picker to filter by date range - Default last 90 days.

Prompt keywords reference

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

Chart

Here are some keyword suggestions to create and customize a chart:

Keyword/Phrase	Description	Example
X	The column to show on the horizontal axis	created date
Y	The column to show on the vertical axis	average weight
Color	Create separate colored lines for different groups	color by factory location
Facet rows	Create multiple plots stacked vertically by group	facet vertically by factory location
Facet columns	Create multiple plots side-by-side by group	facet by defect

Data

Specify data instructions in your prompt to transform, filter, or aggregate your data before visualization.

Calculate average weight by created date (daily).
Calculate shipping days as the difference between
shipped date and created date in days.

Here are some keyword suggestions:

Keyword/Phrase	Description	Example
Aggregation	Specify how to aggregate data	average weight by created date (daily)
Computed field	Create new calculated fields from existing data	calculate shipping days 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

Specify options in your prompt to add interactive controls that allow users to dynamically filter, transform, and visualize data without regenerating the chart.

Add a dropdown to select factory (All, Osaka, Seoul, Singapore) - Default All.
Add a date range picker to filter by date range - Default last 90 days.

Here are some keyword suggestions. See App Controls for a complete list of control types and additional examples.

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

Chart styles

Specify chart styles in your prompt to control the visual appearance and formatting of your line chart.

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

Here are some keyword suggestions:

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