5 Best Ways to Save Multiple Plots into a Single HTML File in Python Plotly

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💡 Problem Formulation: In data analysis, it’s often necessary to visualize multiple plots to draw comprehensive insights. However, managing numerous plot files can be cumbersome. This article explains how to consolidate multiple Plotly plots into a single HTML file using Python, simplifying data presentation and sharing. This is particularly useful for analysts and developers who need to present multiple interactive visualizations without toggling between separate plot files. The desired output is a single HTML file containing multiple Plotly plots.

Method 1: Using Plotly’s plot() Function with Subplots

Plotly’s plot() function combined with subplots is a straightforward method to save multiple plots in a single HTML file. You can create a subplot for each plot and then use the plot() function specifying the output filename with an ‘.html’ extension. This method ensures that multiple, individual plots are positioned in a single grid within the HTML document.

Here’s an example:

import plotly.graph_objs as go
from plotly.subplots import make_subplots

# Create figure with 2x1 subplots
fig = make_subplots(rows=2, cols=1)

# Add traces
fig.append_trace(go.Scatter(y=[4, 2, 1]), row=1, col=1)
fig.append_trace(go.Bar(y=[2, 3, 1]), row=2, col=1)

# Save as HTML
fig.write_html('multiple_plots.html')

The output of this code is an HTML file named multiple_plots.html that contains one scatter plot above a bar chart.

This code snippet creates two separate plots—a scatter plot and a bar chart—and positions them within a single Plotly subplot layout before rendering them into an HTML file. This method provides an easy way to organize multiple plots and is highly customizable in terms of layout and design.

Method 2: Stacking Figures with plotly.io.write_html()

Another method to save multiple plots into a single HTML file is by stacking figures using plotly.io.write_html(). This function writes figures to an HTML file, which allows stacking figures by repeated calls or by creating a figure that stacks other figures vertically or horizontally.

Here’s an example:

import plotly.graph_objs as go
import plotly.io as pio

# Create two figures
fig1 = go.Figure(data=go.Scatter(y=[1, 3, 2]))
fig2 = go.Figure(data=go.Bar(y=[2, 1, 3]))

# Save both figures into the same HTML file
with open('stacked_plots.html', 'a') as f:
    f.write(pio.to_html(fig1, full_html=False))
    f.write(pio.to_html(fig2, full_html=False))

The output of this code is an HTML file named stacked_plots.html that contains a scatter plot above a bar chart vertically stacked.

This code snippet demonstrates writing two separate figures into an HTML file one after the other. By setting full_html=False, we avoid duplicating HTML headers and body tags for each plot, resulting in a cleaner stacking within the single HTML file.

Method 3: Combining HTML Strings with plotly.io.to_html()

Combining HTML strings using plotly.io.to_html() is a flexible method when handling multiple plots. This function generates HTML strings for each plot, which can then be concatenated in any preferred order and format before being written to an HTML file.

Here’s an example:

import plotly.graph_objs as go
import plotly.io as pio

# Create multiple plots
fig1 = go.Figure(data=go.Scatter(x=[1, 2, 3], y=[3, 1, 6]))
fig2 = go.Figure(data=go.Bar(x=[1, 2, 3], y=[2, 5, 3]))

# Convert plots to HTML strings
html_string1 = pio.to_html(fig1, full_html=False)
html_string2 = pio.to_html(fig2, full_html=False)

# Combine HTML strings and write to file
combined_html = html_string1 + html_string2
with open('combined_plots.html', 'w') as file:
    file.write(combined_html)

The output of this code is an HTML file named combined_plots.html that contains both a scatter plot and a bar chart displayed in sequence.

In this snippet, we generate HTML strings for each plot using to_html() with full_html=False, and then concatenate these strings to form the body of the HTML file. This method allows for easy customization of the combined HTML content.

Method 4: Utilizing Plotly’s Dash Framework

Plotly’s Dash framework is designed for creating web applications, but it can also be used to save multiple interactive plots to a single HTML file. With Dash, you create a layout with multiple plots which can be easily exported to an HTML file.

Here’s an example:

import dash
import dash_core_components as dcc
import dash_html_components as html

# Initialize the Dash app
app = dash.Dash(__name__)

# Create some Plotly figures
fig1 = dcc.Graph(figure={'data': [{'y': [1, 2, 3]}]})
fig2 = dcc.Graph(figure={'data': [{'y': [3, 1, 2]}]})

# Define the app layout with your figures
app.layout = html.Div(children=[fig1, fig2])

# Run the app and save to an HTML file
if __name__ == '__main__':
    app.run_server(debug=True)

While this code will not output a static HTML file directly, it will start a local server that hosts a web page displaying both plots. You can save this webpage as an HTML file using your web browser’s “Save Page” functionality.

This code snippet sets up a Dash web application that includes multiple Plotly figures within its layout. The application is served on a local web server, after which the interactive content can be saved as a static HTML file from a web browser.

Bonus One-Liner Method 5: Using Plotly’s write_html() Function in a Loop

For a quick and efficient one-liner, you can loop through a list of figures and use Plotly’s write_html() function with the include_plotlyjs='cdn' argument to append each figure to an HTML file without re-including the Plotly.js library each time.

Here’s an example:

import plotly.graph_objs as go
from plotly.offline import plot

# Create a list of figures
figures = [go.Figure(data=[go.Scatter(y=[1, 3, 2])]),
           go.Figure(data=[go.Bar(y=[2, 1, 3])])]

# Loop and save each figure to the HTML file
for i, fig in enumerate(figures):
    plot(fig, filename='one_liner_plots.html', auto_open=False, include_plotlyjs=(i == 0))

The output will be an HTML file that contains all figures stacked in the order they are in the list, with only the first figure including the Plotly.js library.

This succinct method loops through a list of Plotly figures and writes them to an HTML file. The include_plotlyjs parameter ensures that the Plotly.js library is only included once in the final HTML, making the file more lightweight and efficient.

Summary/Discussion

  • Method 1: Using Plotly’s plot() Function with Subplots. Strengths: streamlined and easy to use within Plotly’s API. Weaknesses: can be less flexible for very complex layouts.
  • Method 2: Stacking Figures with plotly.io.write_html(). Strengths: customizable and straightforward. Weaknesses: might require additional adjustments for complex layouts and design.
  • Method 3: Combining HTML Strings with plotly.io.to_html(). Strengths: offers flexibility in the arrangement and customization of HTML content. Weaknesses: may require deeper understanding of HTML to customize effectively.
  • Method 4: Utilizing Plotly’s Dash Framework. Strengths: highly interactive and suitable for web applications. Weaknesses: not a direct method for saving static HTML files; involves extra steps to save the page manually.
  • Bonus One-Liner Method 5: Using Plotly’s write_html() Function in a Loop. Strengths: concise and minimizes file size by including Plotly.js library only once. Weaknesses: less control over the specific layout of the stacked plots.