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0226ff4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 | """Draw the example charts in examples/. Run once after an edit; the PNGs are committed.
python make_examples.py
matplotlib is only needed here, not in the Space. Every company, place and number is made up.
"""
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt # noqa: E402
import numpy as np # noqa: E402
from matplotlib.patches import Polygon # noqa: E402
OUT = Path(__file__).parent / "examples"
SIZE, DPI = (10, 6.25), 110
def figure(bg="white"):
fig, ax = plt.subplots(figsize=SIZE, dpi=DPI, facecolor=bg)
ax.set_facecolor(bg)
fig.subplots_adjust(left=0.09, right=0.93, top=0.8, bottom=0.14)
for s in ("top", "right"):
ax.spines[s].set_visible(False)
return fig, ax
def titles(fig, title, sub, source, color="#111", sub_color="#555"):
fig.text(0.09, 0.93, title, fontsize=22, fontweight="bold", color=color)
fig.text(0.09, 0.87, sub, fontsize=13, color=sub_color)
fig.text(0.09, 0.03, source, fontsize=9.5, color=sub_color)
def save(fig, name):
fig.savefig(OUT / f"{name}.png", facecolor=fig.get_facecolor())
plt.close(fig)
def upside_down_deaths():
years = np.arange(2012, 2026)
deaths = [196, 188, 192, 185, 190, 183, 187, 191, 228, 251, 262, 280, 297, 311]
fig, ax = figure()
ax.fill_between(years, deaths, 0, color="#b3121f", alpha=0.95)
ax.plot(years, deaths, color="#7a0a14", lw=2)
ax.set_ylim(350, 0) # upside down: 0 at the top
ax.set_xlim(2012, 2025)
ax.set_yticks([0, 50, 100, 150, 200, 250, 300, 350])
ax.axvline(2019, color="white", lw=1.5, ls="--")
ax.text(2019.15, 30, "2019: speed-camera law", color="white", fontsize=12, fontweight="bold")
ax.set_ylabel("Road deaths per year")
titles(fig, "Road deaths in Norvale", "Yearly road deaths, 2012–2025", "Source: Norvale Transport Office")
save(fig, "upside-down-deaths")
def ice_cream_sharks():
years = np.arange(2015, 2026)
ice = [51.2, 51.9, 52.3, 53.4, 53.9, 54.1, 55.6, 56.2, 57.0, 57.4, 58.3]
sharks = [2, 3, 3, 5, 5, 6, 7, 8, 9, 9, 11]
fig, ax = figure()
ax.plot(years, ice, color="#e07b00", lw=4, marker="o", ms=8, label="Ice cream sales (€ million)")
ax.set_ylim(50, 59)
ax.set_ylabel("Ice cream sales (€ million)", color="#e07b00", fontsize=12)
ax.tick_params(axis="y", colors="#e07b00")
ax2 = ax.twinx()
ax2.plot(years, sharks, color="#1560bd", lw=4, marker="s", ms=8, label="Shark attacks")
ax2.set_ylim(0, 12)
ax2.set_ylabel("Shark attacks", color="#1560bd", fontsize=12)
ax2.tick_params(axis="y", colors="#1560bd")
ax2.spines["top"].set_visible(False)
ax.legend(handles=ax.get_lines() + ax2.get_lines(), loc="upper left", frameon=False, fontsize=12)
titles(fig, "Ice cream sales vs. shark attacks", "Coral Bay, 2015–2025. Left axis: sales. Right axis: attacks.",
"Source: Coral Bay Tourism Board, Coral Bay Lifeguard Service")
save(fig, "ice-cream-sharks")
def users_still_growing():
new = [1.9, 1.8, 1.7, 1.6, 1.4, 1.2, 1.0, 0.85, 0.7, 0.55, 0.45, 0.35]
total = np.cumsum(new)
months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
fig, ax = figure("#0f1b2d")
ax.bar(months, total, color="#39d98a", width=0.7)
for i, v in enumerate(total):
ax.text(i, v + 0.2, f"{v:.1f}M", ha="center", color="white", fontsize=11, fontweight="bold")
ax.set_ylim(0, 15)
ax.set_ylabel("Total users since launch (millions)", color="#c9d3e0")
ax.tick_params(colors="#c9d3e0")
for s in ("left", "bottom"):
ax.spines[s].set_color("#51607a")
titles(fig, f"Pingly: {total[-1]:.1f} million users and counting", "Cumulative sign-ups since launch, 2025",
"Pingly investor update, Q4 2025", color="white", sub_color="#c9d3e0")
save(fig, "users-still-growing")
def pie_3d():
shares = {"Brightwave": 24, "Kestrel": 29, "Novaline": 26, "Others": 21}
colors = {"Brightwave": "#ff5a1f", "Kestrel": "#6b7a8f", "Novaline": "#9aa7b8", "Others": "#c8d0da"}
fig, ax = plt.subplots(figsize=SIZE, dpi=DPI, facecolor="white")
ax.set_aspect("equal")
ax.axis("off")
tilt, depth = 0.42, 0.22
# Brightwave sits in front (around 270°) and is pulled out toward the viewer.
start = 270 - shares["Brightwave"] * 3.6 / 2
wedges = []
for name, pct in shares.items():
a0, a1 = start, start + pct * 3.6
start = a1
mid = np.radians((a0 + a1) / 2)
off = 0.22 if name == "Brightwave" else 0.0
wedges.append((name, pct, a0, a1, off * np.cos(mid), off * np.sin(mid) * tilt))
def rim(a0, a1, dx, dy, dz=0.0):
t = np.radians(np.linspace(a0, a1, 80))
return np.column_stack([dx + np.cos(t), dy + tilt * np.sin(t) - dz])
def shade(c, f):
r, g, b = matplotlib.colors.to_rgb(c)
return (r * f, g * f, b * f)
# back to front: wedges whose middle is further up are drawn first
for name, pct, a0, a1, dx, dy in sorted(wedges, key=lambda w: -np.sin(np.radians((w[2] + w[3]) / 2))):
top = rim(a0, a1, dx, dy)
side = np.vstack([top, rim(a1, a0, dx, dy, depth)])
ax.add_patch(Polygon(side, color=shade(colors[name], 0.7), lw=0))
ax.add_patch(Polygon(np.vstack([[dx, dy], top]), color=colors[name], ec="white", lw=1.5))
mid = np.radians((a0 + a1) / 2)
big = name == "Brightwave"
ax.text(dx + 0.62 * np.cos(mid), dy + 0.62 * tilt * np.sin(mid) - (0.05 if big else 0), f"{name}\n{pct}%",
ha="center", va="center", fontsize=20 if big else 11, fontweight="bold",
color="white" if big else "#222")
ax.set_xlim(-1.5, 1.5)
ax.set_ylim(-0.95, 0.75)
fig.subplots_adjust(left=0.02, right=0.98, top=0.82, bottom=0.08)
titles(fig, "Smart speaker market share", "Eastland, 2025 unit sales", "Source: Brightwave marketing team")
save(fig, "pie-3d")
def revenue_from_98():
q = ["Q1 2025", "Q2 2025", "Q3 2025", "Q4 2025"]
rev = [98.4, 98.9, 99.3, 100.6]
fig, ax = figure("#101828")
ax.bar(q, rev, color=["#475467"] * 3 + ["#fdb022"], width=0.6)
for i, v in enumerate(rev):
ax.text(i, v + 0.05, f"${v:.1f}M", ha="center", color="white", fontsize=15, fontweight="bold")
ax.set_ylim(98, 101)
ax.set_yticks([98, 98.5, 99, 99.5, 100, 100.5, 101])
ax.tick_params(colors="#d0d5dd", labelsize=12)
for s in ("left", "bottom"):
ax.spines[s].set_color("#475467")
ax.set_ylabel("Revenue ($ million)", color="#d0d5dd")
titles(fig, "Q4: record revenue", "Halvorsen Logistics, quarterly revenue", "Halvorsen Logistics Q4 2025 earnings deck",
color="white", sub_color="#d0d5dd")
save(fig, "revenue-from-98")
def best_three_months():
rng = np.random.default_rng(7)
days = np.arange(92)
walk = rng.normal(0, 0.12, 92).cumsum()
price = 41 + 7.4 * days / 91 + walk - walk[-1] * days / 91 # ends at exactly $48.40
fig, ax = figure()
ax.plot(days, price, color="#12b76a", lw=2.5)
ax.fill_between(days, price, 0, color="#12b76a", alpha=0.12)
ax.set_ylim(0, 55)
ax.set_xlim(0, 91)
ax.set_xticks([0, 30, 61, 91], ["1 Jul", "31 Jul", "31 Aug", "30 Sep"])
ax.yaxis.tick_right()
ax.spines["left"].set_visible(False)
ax.spines["right"].set_visible(True)
ax.set_yticks(range(0, 51, 10), [f"${v}" for v in range(0, 51, 10)])
for i, r in enumerate(["1M", "3M", "1Y", "5Y"]):
sel = r == "3M"
fig.text(0.62 + i * 0.075, 0.87, r, fontsize=13, fontweight="bold", ha="center",
color="white" if sel else "#667085",
bbox=dict(boxstyle="round,pad=0.35", fc="#12b76a" if sel else "#f2f4f7", ec="none"))
fig.text(0.09, 0.87, "HRBR $48.40 +18.0% (3M)", fontsize=14, color="#12b76a", fontweight="bold")
# the 5-year view the post left out: flat, with the last 3 months shaded
t = np.arange(60)
five = 41 + np.sin(t / 4.0) * 3.5 + rng.normal(0, 0.6, 60)
five[-3:] = [43.5, 46, 48.4]
five[0] = 47.8
inset = fig.add_axes([0.14, 0.2, 0.42, 0.3], facecolor="white")
inset.plot(t, five, color="#98a2b3", lw=1.8)
inset.axvspan(57, 59, color="#12b76a", alpha=0.3)
inset.set_ylim(30, 55)
inset.set_xticks([0, 59], ["2021", "2026"], fontsize=9)
inset.set_yticks([])
for s in ("top", "right", "left"):
inset.spines[s].set_visible(False)
inset.set_title("Same stock over 5 years: +1.2%", fontsize=13, fontweight="bold", color="#344054", loc="left")
inset.text(58, 51, "these\n3 months", fontsize=9.5, color="#067647", ha="right", va="top")
fig.text(0.09, 0.93, "Harbor Bank", fontsize=22, fontweight="bold", color="#111")
fig.text(0.09, 0.03, "Share price, last 3 months · 2026", fontsize=9.5, color="#555")
save(fig, "best-three-months")
def log_flattening():
weeks = np.arange(1, 21)
cases = np.round(3 * np.exp(np.cumsum(np.linspace(0.7, 0.12, 20)))).astype(int)
fig, ax = figure()
ax.plot(weeks, cases, color="#7a5af8", lw=3.5, marker="o", ms=6)
ax.set_yscale("log")
ax.set_ylim(1, 100000)
ax.set_yticks([1, 10, 100, 1000, 10000, 100000], ["1", "10", "100", "1,000", "10,000", "100,000"])
ax.minorticks_off()
ax.set_xticks([1, 5, 10, 15, 20])
ax.set_xlabel("Week of outbreak")
ax.set_ylabel("Total measles cases")
ax.axvspan(16, 20, color="#7a5af8", alpha=0.08)
ax.text(18, 1.6, "last month", ha="center", color="#7a5af8", fontsize=11)
titles(fig, "Measles in Ostmark County", f"Total confirmed cases: {cases[-1]:,}", "Source: Ostmark County Health Department")
save(fig, "log-flattening")
def crime_totals():
cities = ["Riverton\npop. 2,100,000", "Millbrook\npop. 310,000", "Ashby\npop. 95,000", "Elm Falls\npop. 38,000"]
burglaries = [8400, 2100, 610, 420]
fig, ax = figure()
ax.bar(cities, burglaries, color=["#d92d20", "#98a2b3", "#98a2b3", "#98a2b3"], width=0.6)
for i, v in enumerate(burglaries):
ax.text(i, v + 150, f"{v:,}", ha="center", fontsize=15, fontweight="bold")
ax.set_ylim(0, 9500)
ax.set_ylabel("Reported burglaries, 2025")
ax.tick_params(axis="x", labelsize=12)
titles(fig, "Where are the most break-ins?", "Reported burglaries by city, 2025", "Source: State Police annual report")
save(fig, "crime-totals")
def honest_library():
years = ["2021", "2022", "2023", "2024", "2025"]
loans = [41, 49, 58, 70, 83]
fig, ax = figure()
ax.bar(years, loans, color="#2e90fa", width=0.6)
for i, v in enumerate(loans):
ax.text(i, v + 1.5, f"{v}k", ha="center", fontsize=14, fontweight="bold")
ax.set_ylim(0, 100)
ax.set_ylabel("Books loaned (thousands)")
titles(fig, "Tallow Creek Library loans", "Books loaned per year", "Source: Tallow Creek Public Library")
save(fig, "honest-library")
def honest_tram():
periods = ["2024\nbefore the tram", "2025\nafter the tram"]
commute = [32.1, 29.0]
fig, ax = figure()
ax.bar(periods, commute, color=["#98a2b3", "#0e9384"], width=0.5)
for i, v in enumerate(commute):
ax.text(i, v + 0.8, f"{v:.1f} min", ha="center", fontsize=16, fontweight="bold")
ax.set_ylim(0, 40)
ax.set_ylabel("Average one-way commute (minutes)")
ax.tick_params(axis="x", labelsize=13)
titles(fig, "Commute times in Larkspur", "Average one-way commute, the year before and after the new tram line",
"Source: Larkspur City Travel Survey")
save(fig, "honest-tram")
if __name__ == "__main__":
OUT.mkdir(exist_ok=True)
for draw in (upside_down_deaths, ice_cream_sharks, users_still_growing, pie_3d, revenue_from_98,
best_three_months, log_flattening, crime_totals, honest_library, honest_tram):
draw()
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