Plotly Subplots: Customizing X-Axis Ticks and Labels

This guide demonstrates how to control the x-axis ticks and labels for each subplot within a Plotly subplot figure. This is achieved by leveraging the xaxis parameter when adding traces and the update_xaxes method.

Code Example:

import plotly.subplots as sp
import plotly.graph_objects as go

fig = sp.make_subplots(rows=len(year), cols=3, subplot_titles=[])
# , subplot_titles=feature_list
for i, _year in enumerate(year):
    _df = fig_df[fig_df['compound_name'] == _year].copy()
    fig.add_trace(
        go.Bar(x=_df['因子参数'].values, y=_df['累积净值'], name='_year'),
        row=i + 1,
        col=1,
        xaxis='x'+str(i+1),
    )

    fig.update_xaxes(
        tickvals=[1, 2, 3, 4], # 设置刻度值
        ticktext=['a', 'b', 'c', 'd'], # 设置标签值
        row=i+1,
        col=1,
    )

Explanation:

Assign a Unique X-Axis: When adding a trace, use xaxis='x'+str(i+1) to assign a unique x-axis identifier to each subplot. This allows for independent customization.
Update X-Axes: Use fig.update_xaxes to modify the tick values and labels for each subplot.
- tickvals: Sets the numerical values for the ticks.
- ticktext: Specifies the labels to be displayed at the corresponding tick values.

By applying these techniques, you gain precise control over the x-axis presentation of each individual subplot within your Plotly figure.

Plotly Subplots: Customizing X-Axis Ticks and Labels