plot_probly.py

"""
probly dataset
=================

In this example, we will be replicating the first ridgeline plot example in
`this _from Data to Viz_ post <https://www.data-to-viz.com/graph/ridgeline.html>`_
, which uses the _probly_ dataset. You can find the _plobly_ dataset on
multiple sources like in the
`bokeh <https://raw.githubusercontent.com/bokeh/bokeh/main/bokeh/sampledata/_data/probly.csv>`_
python interactive visualization library. I'll be using the
`same source <https://raw.githubusercontent.com/zonination/perceptions/master/probly.csv>`_
used in the original post.
"""

from __future__ import annotations

import numpy as np
import plotly.io as pio

from ridgeplot import ridgeplot
from ridgeplot.datasets import load_probly

# %%
# Load the probly dataset
df = load_probly()

# %%
# Let's grab the subset of columns used in the example
column_names = [
    "Almost Certainly",
    "Very Good Chance",
    "We Believe",
    "Likely",
    "About Even",
    "Little Chance",
    "Chances Are Slight",
    "Almost No Chance",
]
df = df[column_names]

# %%
# Not only does :func:`~ridgeplot.ridgeplot()` come configured with sensible defaults
# but is also fully configurable to your own style and preference!

fig = ridgeplot(
    # Get your samples in the correct format
    samples=df.to_numpy().T,
    # We can specify the bandwidth used for KDE
    bandwidth=4,
    # and the range of points for which the KDE is evaluated
    kde_points=np.linspace(-12.5, 112.5, 500),
    # You can pass any plotly color scale here
    colorscale="viridis",
    # In the example, the distributions seem to be colored the
    # row's index. Have a look at the other available options!
    colormode="row-index",
    # Set the transparency level
    opacity=0.65,
    # Always label your plots! Don't be evil...
    labels=column_names,
    # Adjust the vertical spacing between the distributions
    spacing=5 / 9,
)

# %%
# And you can still update and extend the final
# Plotly Figure using standard Plotly methods
fig.update_layout(
    height=560,
    width=800,
    font_size=16,
    plot_bgcolor="white",
    xaxis_tickvals=[-12.5, 0, 12.5, 25, 37.5, 50, 62.5, 75, 87.5, 100, 112.5],
    xaxis_ticktext=["", "0", "", "25", "", "50", "", "75", "", "100", ""],
    xaxis_gridcolor="rgba(0, 0, 0, 0.1)",
    yaxis_gridcolor="rgba(0, 0, 0, 0.1)",
    yaxis_title=dict(text="Assigned Probability (%)", font_size=13),
    showlegend=False,
)

# %%
# Show us the work!
pio.show(fig)