Lollipop comparisons

Vertical and horizontal lollipop charts in a publication layout.

Why UltraPlot here?

UltraPlot adds lollipop plot methods that mirror bar plotting while exposing simple styling for stems and markers. This plot type is not built into Matplotlib.

Key functions: ultraplot.axes.PlotAxes.lollipop(), ultraplot.axes.PlotAxes.lollipoph().

See also

• 1D plot types

import numpy as np
import pandas as pd

import ultraplot as uplt

rng = np.random.default_rng(11)
categories = ["Alpha", "Beta", "Gamma", "Delta", "Epsilon", "Zeta"]
values = np.sort(rng.uniform(0.4, 1.3, len(categories)))
data = pd.Series(values, index=categories, name="score")

fig, axs = uplt.subplots(ncols=2, share=0, refwidth=2.8)
axs[0].lollipop(data, stemcolor="black", marker="o", color="C0")
axs[0].format(title="Vertical lollipop", xlabel="Category", ylabel="Score")

axs[1].lollipoph(data, stemcolor="black", marker="o", color="C1")
axs[1].format(title="Horizontal lollipop", xlabel="Score", ylabel="Category")

axs.format(abc=True, abcloc="ul", suptitle="Lollipop charts for ranked metrics")

fig.show()