Violin and Box Plots

Pair boxplots and violins to show summary stats and full distributions in one glance.

import matplotlib.pyplot as plt
import numpy as np

import dartwork_mpl as dm

# Apply scientific style
dm.style.use("scientific")

# Generate data
np.random.seed(10)
data = [np.random.normal(0, std, 100) for std in range(1, 5)]

fig = plt.figure(figsize=(dm.cm2in(15), dm.cm2in(8)), dpi=300)
gs = fig.add_gridspec(
    1, 2, left=0.08, right=0.98, top=0.92, bottom=0.12, wspace=0.3
)

# Box Plot
ax1 = fig.add_subplot(gs[0])
ax1.boxplot(
    data,
    patch_artist=True,
    boxprops={"facecolor": "oc.blue3", "color": "oc.blue7"},
    medianprops={"color": "white"},
    whiskerprops={"color": "oc.gray7"},
    capprops={"color": "oc.gray7"},
)
ax1.set_title("Box Plot", fontsize=dm.fs(1))
ax1.set_xlabel("Category", fontsize=dm.fs(0))
ax1.set_ylabel("Value", fontsize=dm.fs(0))

# Violin Plot
ax2 = fig.add_subplot(gs[1])
parts = ax2.violinplot(data, showmeans=False, showmedians=True)

# Customize violin plot colors
for pc in parts["bodies"]:
    pc.set_facecolor("oc.red5")
    pc.set_edgecolor("oc.red7")
    pc.set_alpha(0.7)

for partname in ("cbars", "cmins", "cmaxes", "cmedians"):
    vp = parts[partname]
    vp.set_edgecolor("oc.gray7")
    vp.set_linewidth(1)

ax2.set_title("Violin Plot", fontsize=dm.fs(1))
ax2.set_xlabel("Category", fontsize=dm.fs(0))
ax2.set_ylabel("Value", fontsize=dm.fs(0))

# Add subplot labels
for ax, label in zip([ax1, ax2], "ab", strict=False):
    offset = dm.make_offset(4, -4, fig)
    ax.text(
        0,
        1,
        label,
        transform=ax.transAxes + offset,
        weight="bold",
        va="top",
        fontsize=dm.fs(2),
    )

dm.simple_layout(fig, gs=gs)
plt.show()