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Sliders can be used in Plotly to change the data displayed or style of a plot.
import plotly.graph_objects as go
import numpy as np
# Create figure
fig = go.Figure()
# Add traces, one for each slider step
for step in np.arange(0, 5, 0.1):
fig.add_trace(
go.Scatter(
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))))
# Make 10th trace visible
fig.data[10].visible = True
# Create and add slider
steps = []
for i in range(len(fig.data)):
step = dict(
method="update",
args=[{"visible": [False] * len(fig.data)},
{"title": "Slider switched to step: " + str(i)}], # layout attribute
)
step["args"][0]["visible"][i] = True # Toggle i'th trace to "visible"
steps.append(step)
sliders = [dict(
active=10,
currentvalue={"prefix": "Frequency: "},
pad={"t": 50},
steps=steps
)]
fig.update_layout(
sliders=sliders
)
fig.show()
The method determines which plotly.js function will be used to update the chart. Plotly can use several updatemenu methods to add the slider:
"update"
: modify data and layout attributes (as above)"restyle"
: modify data attributes"relayout"
: modify layout attributes"animate"
: start or pause an animation
Plotly Express provide sliders, but with implicit animation using the "animate"
method described above. The animation play button can be omitted by removing updatemenus
in the layout
:
import plotly.express as px
df = px.data.gapminder()
fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",
size="pop", color="continent", hover_name="country",
log_x=True, size_max=55, range_x=[100,100000], range_y=[25,90])
fig["layout"].pop("updatemenus") # optional, drop animation buttons
fig.show()
Check out https://plotly.com/python/reference/layout/updatemenus/ for more information!