Time Series Comparison

Compare several series with dual axes, panel splits, and color harmonies meant for dashboards.

import matplotlib.pyplot as plt
import numpy as np

import dartwork_mpl as dm

dm.style.use("scientific")

# Generate time series
np.random.seed(42)
n = 100
t = np.arange(n)
ts1 = 50 + np.cumsum(np.random.randn(n) * 2)
ts2 = 45 + np.cumsum(np.random.randn(n) * 2)
ts3 = 55 + np.cumsum(np.random.randn(n) * 2)

fig = plt.figure(figsize=(dm.cm2in(16), dm.cm2in(12)), dpi=300)
gs = fig.add_gridspec(
    nrows=2,
    ncols=2,
    left=0.08,
    right=0.98,
    top=0.95,
    bottom=0.08,
    wspace=0.3,
    hspace=0.4,
)

# Panel A: Multiple series
ax1 = fig.add_subplot(gs[0, 0])
ax1.plot(t, ts1, color="oc.red5", lw=0.7, label="Series A")
ax1.plot(t, ts2, color="oc.blue5", lw=0.7, label="Series B")
ax1.plot(t, ts3, color="oc.green5", lw=0.7, label="Series C")
ax1.set_xlabel("Time", fontsize=dm.fs(0))
ax1.set_ylabel("Value", fontsize=dm.fs(0))
ax1.set_title("Multiple Time Series", fontsize=dm.fs(1))
ax1.legend(loc="best", fontsize=dm.fs(-1))

# Panel B: Stacked area
ax2 = fig.add_subplot(gs[0, 1])
ax2.fill_between(t, 0, ts1 - 40, color="oc.red5", alpha=0.6, label="Series A")
ax2.fill_between(
    t,
    ts1 - 40,
    ts1 - 40 + ts2 - 40,
    color="oc.blue5",
    alpha=0.6,
    label="Series B",
)
ax2.fill_between(
    t,
    ts1 - 40 + ts2 - 40,
    ts1 - 40 + ts2 - 40 + ts3 - 40,
    color="oc.green5",
    alpha=0.6,
    label="Series C",
)
ax2.set_xlabel("Time", fontsize=dm.fs(0))
ax2.set_ylabel("Cumulative value", fontsize=dm.fs(0))
ax2.set_title("Stacked Area", fontsize=dm.fs(1))
ax2.legend(loc="best", fontsize=dm.fs(-2))

# Panel C: Normalized comparison
ax3 = fig.add_subplot(gs[1, 0])
ts1_norm = (ts1 - ts1[0]) / ts1[0] * 100
ts2_norm = (ts2 - ts2[0]) / ts2[0] * 100
ts3_norm = (ts3 - ts3[0]) / ts3[0] * 100
ax3.plot(t, ts1_norm, color="oc.red5", lw=0.7, label="Series A")
ax3.plot(t, ts2_norm, color="oc.blue5", lw=0.7, label="Series B")
ax3.plot(t, ts3_norm, color="oc.green5", lw=0.7, label="Series C")
ax3.axhline(y=0, color="k", lw=0.3, linestyle="--")
ax3.set_xlabel("Time", fontsize=dm.fs(0))
ax3.set_ylabel("Change from baseline (%)", fontsize=dm.fs(0))
ax3.set_title("Normalized Comparison", fontsize=dm.fs(1))
ax3.legend(loc="best", fontsize=dm.fs(-2))

# Panel D: Difference plot
ax4 = fig.add_subplot(gs[1, 1])
diff_ab = ts1 - ts2
diff_ac = ts1 - ts3
ax4.plot(t, diff_ab, color="oc.violet5", lw=0.7, label="A - B")
ax4.plot(t, diff_ac, color="oc.orange5", lw=0.7, label="A - C")
ax4.axhline(y=0, color="k", lw=0.3, linestyle="--")
ax4.fill_between(
    t,
    0,
    diff_ab,
    where=(diff_ab > 0),
    color="oc.violet5",
    alpha=0.2,
    interpolate=True,
)
ax4.fill_between(
    t,
    0,
    diff_ab,
    where=(diff_ab < 0),
    color="oc.violet5",
    alpha=0.2,
    interpolate=True,
)
ax4.set_xlabel("Time", fontsize=dm.fs(0))
ax4.set_ylabel("Difference", fontsize=dm.fs(0))
ax4.set_title("Difference Analysis", fontsize=dm.fs(1))
ax4.legend(loc="best", fontsize=dm.fs(-1))

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