How to Hide Axis Titles in Plotly Express Figure with Facets in Python?

Plotly Express is a powerful data visualization library in Python that creates interactive plots with ease. When working with faceted plots (subplots), you may want to hide axis titles to create cleaner visualizations. This article explores different methods to hide axis titles in Plotly Express figures with facets.

Syntax

Here's the basic syntax for creating faceted plots in Plotly Express ?

import plotly.express as px

fig = px.scatter(data_frame, x="x_column", y="y_column", 
                 facet_row="row_column", facet_col="col_column")

Sample Data Setup

Let's create sample data to demonstrate the techniques ?

import pandas as pd
import plotly.express as px

# Create sample dataset
data = {
    'x_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
    'y_values': [10, 15, 12, 18, 14, 20, 16, 22, 18, 25, 21, 28],
    'category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'],
    'region': ['North', 'North', 'South', 'South', 'North', 'North', 
               'South', 'South', 'North', 'North', 'South', 'South']
}

df = pd.DataFrame(data)
print(df.head())

   x_values  y_values category region
0         1        10        A  North
1         2        15        B  North
2         3        12        A  South
3         4        18        B  South
4         5        14        A  North

Method 1: Using update_layout()

The simplest approach is to modify the figure's layout to hide axis titles ?

import pandas as pd
import plotly.express as px

# Create sample data
data = {
    'x_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
    'y_values': [10, 15, 12, 18, 14, 20, 16, 22, 18, 25, 21, 28],
    'category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'],
    'region': ['North', 'North', 'South', 'South', 'North', 'North', 
               'South', 'South', 'North', 'North', 'South', 'South']
}

df = pd.DataFrame(data)

# Create faceted scatter plot
fig = px.scatter(df, x="x_values", y="y_values", 
                 facet_col="category", facet_row="region")

# Hide axis titles
fig.update_layout(
    xaxis_title="",
    yaxis_title=""
)

print("Axis titles hidden using update_layout method")
fig.show()

Axis titles hidden using update_layout method

Method 2: Iterating Through All Axes

For more control over individual subplot axes, iterate through all axis objects ?

import pandas as pd
import plotly.express as px

# Create sample data
data = {
    'x_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
    'y_values': [10, 15, 12, 18, 14, 20, 16, 22, 18, 25, 21, 28],
    'category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'],
    'region': ['North', 'North', 'South', 'South', 'North', 'North', 
               'South', 'South', 'North', 'North', 'South', 'South']
}

df = pd.DataFrame(data)

# Create faceted scatter plot
fig = px.scatter(df, x="x_values", y="y_values", 
                 facet_col="category", facet_row="region")

# Hide axis titles for all subplots
for axis_name in fig.layout:
    if axis_name.startswith("xaxis") or axis_name.startswith("yaxis"):
        fig.layout[axis_name].title = ""

print("All subplot axis titles hidden")
fig.show()

All subplot axis titles hidden

Method 3: Using update_xaxes() and update_yaxes()

A more explicit approach using dedicated axis update methods ?

import pandas as pd
import plotly.express as px

# Create sample data
data = {
    'x_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
    'y_values': [10, 15, 12, 18, 14, 20, 16, 22, 18, 25, 21, 28],
    'category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'],
    'region': ['North', 'North', 'South', 'South', 'North', 'North', 
               'South', 'South', 'North', 'North', 'South', 'South']
}

df = pd.DataFrame(data)

# Create faceted scatter plot
fig = px.scatter(df, x="x_values", y="y_values", 
                 facet_col="category", facet_row="region")

# Hide axis titles using update methods
fig.update_xaxes(title_text="")
fig.update_yaxes(title_text="")

print("Axis titles hidden using update_xaxes/update_yaxes methods")
fig.show()

Axis titles hidden using update_xaxes/update_yaxes methods

Comparison

Conclusion

Use update_xaxes() and update_yaxes() with title_text="" for the cleanest approach to hide axis titles in faceted Plotly Express plots. For complex layouts, iterate through the layout object to target specific axes individually.