Last Updated : 22 Sep, 2020
A Plotly is a Python library that is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot, and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.
Creating Dropdown MenusA drop-down menu is a part of the menu-button which is displayed on a screen all the time. Every menu button is associated with a Menu widget that can display the choices for that menu button when clicked on it. In plotly, there are 4 possible methods to modify the charts by using updatemenu method.
Example 1: Restyle Dropdown
The data and data attributes of the graph can be modified.
Python3
import plotly.graph_objects as px
import numpy as np
# creating random data through randomint
# function of numpy.random
np.random.seed(42)
random_x = np.random.randint(1, 101, 100)
random_y = np.random.randint(1, 101, 100)
plot = px.Figure(data=[px.Scatter(
x=random_x,
y=random_y,
mode='markers',)
])
# Add dropdown
plot.update_layout(
updatemenus=[
dict(
buttons=list([
dict(
args=["type", "scatter"],
label="Scatter Plot",
method="restyle"
),
dict(
args=["type", "bar"],
label="Bar Chart",
method="restyle"
)
]),
direction="down",
),
]
)
plot.show()
Output:
Example 2:
Python3
import plotly.graph_objects as px
import numpy
# creating random data through randomint
# function of numpy.random
np.random.seed(42)
random_x = np.random.randint(1, 101, 100)
random_y = np.random.randint(1, 101, 100)
x = ['A', 'B', 'C', 'D']
plot = px.Figure(data=[go.Bar(
name='Data 1',
x=x,
y=[100, 200, 500, 673]
),
go.Bar(
name='Data 2',
x=x,
y=[56, 123, 982, 213]
)
])
# Add dropdown
plot.update_layout(
updatemenus=[
dict(
active=0,
buttons=list([
dict(label="Both",
method="update",
args=[{"visible": [True, True]},
{"title": "Both"}]),
dict(label="Data 1",
method="update",
args=[{"visible": [True, False]},
{"title": "Data 1",
}]),
dict(label="Data 2",
method="update",
args=[{"visible": [False, True]},
{"title": "Data 2",
}]),
]),
)
])
plot.show()
Output:
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