Chart Types versus Trace Types¶
Plotly's figure data structure supports defining subplots of various types (e.g. cartesian, polar, 3-dimensional, maps etc) with attached traces of various compatible types (e.g. scatter, bar, choropleth, surface etc). This means that Plotly figures are not constrained to representing a fixed set of "chart types" such as scatter plots only or bar charts only or line charts only: any subplot can contain multiple traces of different types.
Multiple Trace Types with Plotly Express¶
Plotly Express exposes a number of functions such as
px.choropleth() which generally speaking only contain traces of the same type, with exceptions made for trendlines and marginal distribution plots.
Figures produced with Plotly Express functions support the
add_trace() method documented below, just like figures created with graph objects so it is easy to start with a Plotly Express figure containing only traces of a given type, and add traces of another type.
import plotly.express as px fruits = ["apples", "oranges", "bananas"] fig = px.line(x=fruits, y=[1,3,2], color=px.Constant("This year"), labels=dict(x="Fruit", y="Amount", color="Time Period")) fig.add_bar(x=fruits, y=[2,1,3], name="Last year") fig.show()
import plotly.graph_objects as go fig = go.Figure() fig.add_trace( go.Scatter( x=[0, 1, 2, 3, 4, 5], y=[1.5, 1, 1.3, 0.7, 0.8, 0.9] )) fig.add_trace( go.Bar( x=[0, 1, 2, 3, 4, 5], y=[1, 0.5, 0.7, -1.2, 0.3, 0.4] )) fig.show()
import plotly.graph_objects as go # Load data import json import urllib response = urllib.request.urlopen( "https://raw.githubusercontent.com/plotly/datasets/master/steepest.json") data = json.load(response) # Create figure fig = go.Figure() fig.add_trace( go.Contour( z=data["contour_z"], y=data["contour_y"], x=data["contour_x"], ncontours=30, showscale=False ) ) fig.add_trace( go.Scatter( x=data["trace_x"], y=data["trace_y"], mode="markers+lines", name="steepest", line=dict( color="black" ) ) ) fig.show()
What About Dash?¶
Learn about how to install Dash at https://dash.plot.ly/installation.
Everywhere in this page that you see
fig.show(), you can display the same figure in a Dash application by passing it to the
figure argument of the
Graph component from the built-in
dash_core_components package like this:
import plotly.graph_objects as go # or plotly.express as px fig = go.Figure() # or any Plotly Express function e.g. px.bar(...) # fig.add_trace( ... ) # fig.update_layout( ... ) import dash import dash_core_components as dcc import dash_html_components as html app = dash.Dash() app.layout = html.Div([ dcc.Graph(figure=fig) ]) app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter