5 Best Ways to Hide the Y-Axis Tick Labels on a Chart in Python Plotly

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πŸ’‘ Problem Formulation: When visualizing data using charts, certain design choices can make a plot more readable or emphasize particular aspects of the data. Sometimes, you might want to remove or hide the tick labels on the y-axis to create a cleaner look or to prevent distraction from the main content of the chart. In Python, using Plotly, there are multiple ways to manipulate the tick labels. This article describes how to hide y-axis tick labels, assuming a reader has a Plotly chart object and wishes to hide the corresponding tick labels for aesthetic or design purposes.

Method 1: Using the ‘update_yaxes’ Function

Plotly offers the update_yaxes function to customize axes properties extensively. To hide y-axis tick labels, showticklabels attribute can be set to False. This method is clear and straightforward and applies to the entire axis.

Here’s an example:

import plotly.graph_objects as go

fig = go.Figure(data=go.Bar(y=[2, 3, 1]))

Output: A bar chart is displayed with the y-axis having no tick labels.

This code creates a simple bar chart and then calls the update_yaxes method to modify the y-axis. By setting showticklabels to False, it effectively hides all the tick labels on the y-axis when the figure is rendered.

Method 2: Setting ‘tickvals’ to an Empty List

Setting the tickvals parameter to an empty list for the y-axis properties in Plotly will result in no tick marks being drawn, and hence, no labels either. This tactic might be a little less intuitive, but it is equally effective.

Here’s an example:

import plotly.graph_objects as go

fig = go.Figure(data=go.Bar(y=[4, 1, 3]))

Output: A bar chart is shown without any tick marks or labels on the y-axis.

The code creates a bar chart, then uses the update_layout function to modify the y-axis properties. The tickvals argument is an empty list which tells Plotly not to include any ticks on the y-axis, thereby also removing the labels.

Method 3: Using ‘update_layout’ and ‘yaxis_showticklabels’

This technique involves setting the update_layout method’s yaxis_showticklabels property directly to False. Similar to Method 1, it focuses on removing the labels while maintaining any other axis features.

Here’s an example:

import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(y=[1, 4, 2]))

Output: A scatter plot appears with the y-axis stripped of its tick labels.

By simply creating a scatter plot and updating the layout with yaxis_showticklabels=False, this code instructs Plotly not to display any tick labels on the y-axis, making for a cleaner-looking plot.

Method 4: Setting the ‘ticktext’ to an Empty List

If you wish to keep tick marks but remove text, setting ticktext to an empty list can achieve this. This way, Plotly will draw the ticks with no accompanying labels.

Here’s an example:

import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(y=[10, 15, 12]))
fig.update_yaxes(tickvals=[1,2,3], ticktext=[])

Output: A scatter plot is shown with tick marks on the y-axis but no labels.

In this code snippet, the update_yaxes method is used again But instead of hiding the tick marks completely, we are setting ticktext to an empty list which preserves the mark locations (tickvals) without any labels alongside.

Bonus One-Liner Method 5: Using ‘visible’ Attribute

A concise one-liner using the visible attribute of the y-axis can also be employed. Setting this to False will hide the entire axis, both ticks and labels.

Here’s an example:

import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(y=[2, 5, 7]))

Output: A scatter plot with the y-axis completely hidden.

This method is a drastic one since it removes the entire y-axis. However, it is the most straightforward way to hide all aspects of the y-axis with one property. The example demonstrates the removal of the y-axis before showing the plot.


  • Method 1: Using ‘update_yaxes’. Strengths: Direct, clear, and idiomatic. Weaknesses: Only affects tick labels, not axis lines or other related elements.
  • Method 2: Setting ‘tickvals’. Strengths: Removes both the ticks and labels. Weaknesses: May not be intuitive that removing tick marks also removes labels.
  • Method 3: Using ‘update_layout’. Strengths: Applies the change to all axes in the layout succinctly. Weaknesses: Not as granular as Method 1.
  • Method 4: Setting ‘ticktext’. Strengths: Allows keeping the tick marks while removing the labels. Weaknesses: Requires manually setting of ‘tickvals’ for proper alignment.
  • Bonus Method 5: Using ‘visible’ Attribute. Strengths: Quick and removes the entire axis for complete minimalism. Weaknesses: Too extreme for just removing labels, as it affects the whole axis.