Figure Factories in Python

Figure Factories are dedicated functions for creating very specific types of plots.


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

plotly.figure_factory

The plotly.figure_factory module contains dedicated functions for creating very specific types of plots that were at the time of their creation difficult to create with plotly.graph_objects and prior to the existence of Plotly Express. As new functionality gets added to Plotly.js and to Plotly Express, certain Figure Factories become unecessary and are therefore deprecated as "legacy", but remain in the module for backwards-compatibility reasons.

The following types of plots are still difficult to create with Graph Objects or Plotly Express and therefore the corresponding Figure Factories are not deprecated:

Deprecated "legacy" Figure Factories include:

Reference

For more information about the contents of plotly.figure_factory, including deprecated methods, please refer to our API Reference documentation.

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

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