Interactive NotebookOpenAI-Inspired Matplotlib Styling: Modern Data Visualization in Python

1import pandas as pd
2import numpy as np
3import matplotlib.pyplot as plt
4import seaborn as sns

1# Matplotlib rcParams for OpenAI-inspired style
2from pathlib import Path
3from textwrap import dedent
4import numpy as np
5import matplotlib.pyplot as plt
6from matplotlib.ticker import PercentFormatter
7
8
9import matplotlib as mpl
10
11mpl.rcParams.update(
12    {
13        "figure.facecolor": "white",
14        "figure.autolayout": False,
15        "figure.dpi": 160,
16        "savefig.transparent": True,
17        "savefig.bbox": "tight",
18        "savefig.pad_inches": 0.05,
19        "font.family": "DejaVu Sans",
20        "font.size": 12,
21        "text.color": "black",
22        "axes.titlesize": 18,
23        "axes.titleweight": 700,
24        "axes.titlepad": 14,
25        "axes.labelsize": 13,
26        "axes.linewidth": 0.8,
27        "axes.edgecolor": "gainsboro",
28        "axes.facecolor": "white",
29        "axes.spines.top": False,
30        "axes.spines.right": False,
31        "xtick.color": "dimgray",
32        "ytick.color": "dimgray",
33        "xtick.labelsize": 12,
34        "ytick.labelsize": 12,
35        "xtick.major.size": 0,
36        "ytick.major.size": 0,
37        "xtick.major.pad": 6,
38        "ytick.major.pad": 6,
39        "axes.grid": True,
40        "axes.grid.axis": "y",
41        "grid.linestyle": "-",
42        "grid.linewidth": 1.0,
43        "grid.color": "lightgray",
44        "legend.frameon": False,
45        "legend.fontsize": 12,
46        "legend.loc": "upper left",
47        "lines.linewidth": 2,
48        "patch.edgecolor": "none",
49    }
50)

1def label_bars(ax, rects, fmt="{:.1f}%", dy=3, fontsize=12, weight="600"):
2    for r in rects:
3        h = r.get_height()
4        ax.annotate(
5            fmt.format(h),
6            (r.get_x() + r.get_width() / 2, h),
7            xytext=(0, dy),
8            textcoords="offset points",
9            ha="center",
10            va="bottom",
11            fontsize=fontsize,
12            fontweight=weight,
13        )
14
15
16def tweak_axes(ax, top_margin=0.15):
17    ax.set_axisbelow(True)
18    ax.margins(y=top_margin)
19    for s in ("top", "right"):
20        ax.spines[s].set_visible(False)
21
22
23def circular_legend(ax, labels, colors):
24    from matplotlib.lines import Line2D
25
26    handles = [
27        Line2D(
28            [0],
29            [0],
30            marker="o",
31            color="w",
32            markerfacecolor=c,
33            markersize=10,
34            linewidth=0,
35        )
36        for c in colors
37    ]
38    ax.legend(
39        handles,
40        labels,
41        ncol=len(labels),
42        frameon=False,
43        bbox_to_anchor=(0, 1.06),
44        loc="lower left",
45    )
46
47
48# Light/bold paired palette (you can swap these)
49COLORS = ["#C8D7FF", "#4D61D6"]  # light indigo, bold indigo
50
51# ---------------------------------------------------------
52# 3) Demo 1 — Incorrect comments (percent bars + error bars)

1# ---------------------------------------------------------
2labels = ["GPT-5 (high)", "GPT-5-Codex (high)"]
3vals = np.array([13.7, 4.4])
4errs = np.array([1.6, 1.2])
5x = np.arange(len(labels))
6w = 0.55
7
8fig, ax = plt.subplots(figsize=(6.8, 4.2))
9bars = ax.bar(
10    x,
11    vals,
12    yerr=errs,
13    width=w,
14    capsize=3,
15    color=COLORS,
16    zorder=3,
17    edgecolor="dimgray",  # solid border color
18    linewidth=1.5,  # border thickness
19)
20
21# Round the edges of the bars (simulate rounded corners by overlaying a rectangle with rounded edges)
22for bar in bars:
23    bar.set_linewidth(1.5)
24    bar.set_edgecolor("dimgray")
25    bar.set_zorder(3)
26    # set_capstyle and set_joinstyle are for lines, not patches, so we use path effects for a stylized look
27    import matplotlib.patheffects as pe
28
29    bar.set_path_effects([pe.Stroke(linewidth=1.5, foreground="dimgray"), pe.Normal()])
30    bar.set_antialiased(True)
31    # Simulate rounded corners by overlaying a FancyBboxPatch
32    from matplotlib.patches import FancyBboxPatch
33
34    bbox = bar.get_bbox()
35    fancy = FancyBboxPatch(
36        (bbox.x0, bbox.y0),
37        bbox.width,
38        bbox.height,
39        boxstyle="round,pad=0.02,rounding_size=0.3",
40        linewidth=1.5,
41        edgecolor="dimgray",
42        facecolor=bar.get_facecolor(),
43        zorder=bar.get_zorder() + 1,
44        mutation_aspect=1,
45    )
46    ax.add_patch(fancy)
47    bar.set_visible(False)  # Hide the original bar
48
49ax.set_title("Incorrect comments", fontsize=14)
50ax.set_ylabel("% of comments")
51ax.set_xticks(x, labels, rotation=20, ha="right")
52ax.yaxis.set_major_formatter(PercentFormatter())
53label_bars(ax, bars, fmt="{:.1f}%")
54circular_legend(ax, labels, COLORS)
55tweak_axes(ax)
56fig.tight_layout()
57fig.savefig("demo_incorrect_comments.png")

1# ---------------------------------------------------------
2# 4) Demo 2 — High-impact comments
3# ---------------------------------------------------------
4vals2 = np.array([39.4, 52.4])
5errs2 = np.array([1.7, 2.2])
6fig, ax = plt.subplots(figsize=(6.8, 4.2))
7bars = ax.bar(x, vals2, yerr=errs2, width=w, capsize=3, color=COLORS, zorder=3)
8ax.set_title("High-impact comments")
9ax.set_ylabel("% of comments")
10ax.set_xticks(x, labels, rotation=20, ha="right")
11ax.yaxis.set_major_formatter(PercentFormatter())
12label_bars(ax, bars, fmt="{:.1f}%")
13circular_legend(ax, labels, COLORS)
14tweak_axes(ax)
15fig.tight_layout()
16
17# ---------------------------------------------------------
18# 5) Demo 3 — Comments per PR (avg)
19# ---------------------------------------------------------
20vals3 = np.array([1.32, 0.93])
21fig, ax = plt.subplots(figsize=(6.8, 4.2))
22bars = ax.bar(x, vals3, width=w, color=COLORS, zorder=3)
23ax.set_title("Comments per PR (avg)")
24ax.set_ylabel("# of comments")
25ax.set_xticks(x, labels, rotation=20, ha="right")
26label_bars(ax, bars, fmt="{:.2f}", dy=4)
27circular_legend(ax, labels, COLORS)
28tweak_axes(ax, top_margin=0.22)
29fig.tight_layout()
30
31# ---------------------------------------------------------
32# 6) Demo 4 — Stacked bar, “Economically important tasks”
33# ---------------------------------------------------------
34models = ["GPT-5", "ChatGPT agent", "OpenAI o3"]
35wins = np.array([41.0, 36.5, 27.5])
36ties = np.array([6.1, 7.0, 6.0])
37
38fig, ax = plt.subplots(figsize=(7.0, 4.6))
39x = np.arange(len(models))
40w = 0.55
41p1 = ax.bar(x, wins, width=w, color="#B07CFF", label="Wins", zorder=3)
42p2 = ax.bar(x, ties, width=w, bottom=wins, color="#E7D2FF", label="Ties", zorder=3)
43
44ax.set_title("Economically important tasks")
45ax.set_ylabel("%")
46ax.set_xticks(x, models, rotation=20, ha="right")
47ax.set_ylim(0, 60)
48ax.axhline(50, color="gray", linestyle="--", linewidth=1)
49ax.text(ax.get_xlim()[0], 50.5, "Industry expert baseline", fontsize=11)
50
51for a, b in zip(p1, p2):
52    total = a.get_height() + b.get_height()
53    ax.annotate(
54        f"{total:.1f}",
55        (a.get_x() + a.get_width() / 2, total),
56        ha="center",
57        va="bottom",
58        fontsize=11,
59        fontweight="600",
60        xytext=(0, 3),
61        textcoords="offset points",
62    )
63
64ax.legend(ncol=2, bbox_to_anchor=(0, 1.06), loc="lower left")
65tweak_axes(ax)
66fig.tight_layout()