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Sliders in Python/v3

How to add slider controls to your plots in Python with Plotly.


Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.
The version 4 version of this page is here.
The version 4 version of this page is here.

New to Plotly?¶

Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

Version Check¶

Note: Sliders are available in version 1.12.6+
Run pip install plotly --upgrade to update your Plotly version

In [1]:
import plotly
plotly.__version__
Out[1]:
'3.1.0'

Simple Slider Control¶

Sliders can now be used in Plotly to change the data displayed or style of a plot!

In [2]:
import plotly.plotly as py
import numpy as np

data = [dict(
        visible = False,
        line=dict(color='#00CED1', width=6),
        name = '𝜈 = '+str(step),
        x = np.arange(0,10,0.01),
        y = np.sin(step*np.arange(0,10,0.01))) for step in np.arange(0,5,0.1)]
data[10]['visible'] = True

py.iplot(data, filename='Single Sine Wave')
Out[2]:
In [3]:
steps = []
for i in range(len(data)):
    step = dict(
        method = 'restyle',
        args = ['visible', [False] * len(data)],
    )
    step['args'][1][i] = True # Toggle i'th trace to "visible"
    steps.append(step)

sliders = [dict(
    active = 10,
    currentvalue = {"prefix": "Frequency: "},
    pad = {"t": 50},
    steps = steps
)]

layout = dict(sliders=sliders)

fig = dict(data=data, layout=layout)

py.iplot(fig, filename='Sine Wave Slider')
Out[3]:

Reference¶

Check out https://plotly.com/python/reference/#layout-updatemenus for more information!