💡 Problem Formulation: When visualizing data with Python’s Plotly library, you may sometimes need to highlight areas of a chart to indicate regions of significance, such as shading above a specific Y-value. This could be useful, for instance, when you want to emphasize values exceeding a certain threshold, like highlighting temperature regions above 30°C on a climate graph. This article provides methods for adding such highlights with Plotly.
Method 1: Using Shapes to Create a Background Highlight
Creating a shaded area in Plotly can be achieved by using shapes to add a semi-transparent layer over the chart. The shape is defined by its type, here we’ll use a Rectangle, and by the coordinates of its corners, essentially ‘drawing’ the area above the desired y-value. This overlay approach is advantageous due to its simplicity and flexibility, allowing the creation of multiple highlighted areas if necessary.
Here’s an example:
import plotly.graph_objs as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 1, 6]))
fig.update_layout(shapes=[
{
'type': 'rect',
'xref': 'paper',
'yref': 'y',
'x0': 0,
'y0': 5,
'x1': 1,
'y1': 6,
'fillcolor': 'LightSkyBlue',
'opacity': 0.5,
'line': {
'width': 0,
}
}
])
fig.show()
This code generates a scatter plot with a shaded region that extends from y=5 to y=6. The rectangle is created by defining the points of the rectangle’s corners in data space (x0, y0) to (x1, y1). The ‘paper’ reference for the x-axis ensures the rectangle spans the entire width of the plot.
Method 2: Adding a Shaded Area to a Line Chart with fill=’tonexty’
Shading above a specific y-value in a line chart can be achieved by using an area chart with the fill='tonexty' option. This method draws a filled area between the line (or specified points) and the next data series, in this case, a defined threshold line. It’s a quick solution for emphasizing parts of a plot above a certain level in line charts.
Here’s an example:
import plotly.graph_objs as go fig = go.Figure() fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 1, 6], mode='lines')) fig.add_trace(go.Scatter(x=[1, 2, 3], y=[5, 5, 5], mode='lines', fill='tonexty')) fig.show()
The output is a line chart with the area above y=5 filled in. This is done by adding a line at y=5 across the chart and setting fill='tonexty' on the series to fill the area between that line and the actual data series. It creates a visual emphasis efficiently.
Method 3: Utilizing a Scatter Plot Fill to Emphasize Above Threshold Values
Emphasizing data points above a specific threshold can also be accomplished by creating a scatter plot with a filled area. In this approach, data points below the threshold are plotted normally, while those above the threshold are connected with a filled area using fill='tozeroy' and fillcolor to specify the shade.
Here’s an example:
import plotly.graph_objs as go y_values = [4, 1, 6] threshold = 5 filled_area = [y if y > threshold else threshold for y in y_values] fig = go.Figure() fig.add_trace(go.Scatter(x=[1, 2, 3], y=y_values, mode='lines')) fig.add_trace(go.Scatter(x=[1, 2, 3], y=filled_area, mode='lines', fill='tozeroy')) fig.show()
The resulting plot shows the data with a highlighted area above y=5. Any point above this threshold connects with an area shaded down to y=0, creating a visual distinction for these higher values.
Method 4: Shading Above Threshold Using add_hrect()
In Plotly version 4.12 and later, you can use the add_hrect() function to add horizontal rectangles directly, simplifying the creation of shaded regions above a given y-value. This function is syntactically simpler and more intuitive for newcomers to data visualization with Plotly, allowing for straightforward highlighting.
Here’s an example:
import plotly.graph_objs as go
fig = go.Figure(data=go.Scatter(x=[1, 2, 3], y=[4, 1, 6]))
fig.add_hrect(y0=5, y1=fig.layout.yaxis.range[1],
line_width=0, fillcolor="red", opacity=0.2)
fig.show()
In this code, the add_hrect() function adds a horizontal rectangle starting at y=5 and extending to the top of the y-axis. This highlights the specified region above the threshold, making it clearly visible in the resulting chart.
Bonus One-Liner Method 5: Single Line Shading with an Area Chart
For those who prefer a compact one-liner, a quick and elegant way to shade above a certain y-value in an area chart is by using the Plotly Express area function with appropriate parameters to define the baseline and fill color for the region of interest.
Here’s an example:
import plotly.express as px
df = px.data.gapminder().query("country=='Canada'")
fig = px.area(df, x="year", y="pop", line_shape="spline",
base=150000000000000000, fillcolor="limegreen", opacity=0.3)
fig.show()
This single line of code creates an area chart with a specified baseline far beneath the plotted values, effectively resulting in the entire area above the actual data to be shaded. This method is excellent for terse but effective highlighting.
Summary/Discussion
- Method 1: Using Shapes to Create a Background Highlight. Offers precise control over the shaded region’s size and location. Can be visually layered with other plot elements. The method requires more manual coordination of coordinates.
- Method 2: Adding a Shaded Area to a Line Chart with fill=’tonexty’. Perfect for simply highlighting above a straight line threshold on line charts. Not suitable for more complex or irregular highlighting needs.
- Method 3: Utilizing a Scatter Plot Fill to Emphasize Above Threshold Values. Highly customizable for different scenarios. May require additional data processing for desired visual effects.
- Method 4: Shading Above Threshold Using add_hrect(). Streamlines the inclusion of shaded areas using built-in functionality. Limited to horizontal rectangles which may not be flexible enough for all use cases.
- Method 5: Single Line Shading with an Area Chart. Quick and straightforward, excellent for when the entire area above a dataset needs highlighting. Less customizable compared to other methods.