.create_distplot()

The .create_distplot() function is part of Plotly’s figure_factory module.

It generates distribution plots that combine histograms and Kernel Density Estimates (KDE), allowing for a clear visualization of a dataset’s distribution.

Syntax

fig = figure_factory.create_distplot( hist_data, group_labels, ...)

• hist_data: A list of datasets to plot. Each dataset is represented as a separate group in the distribution plot.
• group_labels: List of strings corresponding to each dataset in hist_data. These labels are used to distinguish the different groups in the plot.

Note: The ellipsis (…) in the syntax represents several optional parameters, which are automatically set to their default values, such as bin_size=None, curve_type='kde', colors=None, histnorm='', show_hist=True, show_curve=True, and show_rug=True.

Example

This is a basic distribution plot that generates 2 datasets with normal distributions using default settings:

import plotly.figure_factory as ff
import numpy as np
from scipy import stats

# Generate sample data.
x1 = np.random.randn(200)    # Dataset 1
x2 = np.random.randn(200) + 2    # Dataset 2

hist_data = [x1, x2]
group_labels = ['Dataset 1', 'Dataset 2']

# Create the distribution plot.
fig = ff.create_distplot(hist_data, group_labels)

# Display the plot.
fig.show()

The resulting output looks as follows: