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feat(seaborn): implement slope-basic (#5639)
## Implementation: `slope-basic` - python/seaborn Implements the **python/seaborn** version of `slope-basic`. **File:** `plots/slope-basic/implementations/python/seaborn.py` **Parent Issue:** #981 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25177206954)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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‎plots/slope-basic/implementations/python/seaborn.py‎

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""" pyplots.ai
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""" anyplot.ai
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slope-basic: Basic Slope Chart (Slopegraph)
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Library: seaborn 0.13.2 | Python 3.13.11
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Quality: 91/100 | Created: 2025-12-23
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Library: seaborn 0.13.2 | Python 3.13.13
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Quality: 83/100 | Updated: 2026-04-30
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"""
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import os
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import matplotlib.pyplot as plt
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import pandas as pd
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import seaborn as sns
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from matplotlib.lines import Line2D
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# Data - Tech company revenue growth comparison Q1 vs Q4
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# Values spaced to avoid label overlap
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# Theme tokens
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THEME = os.getenv("ANYPLOT_THEME", "light")
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PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
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ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
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INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
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INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
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COLOR_INCREASE = "#009E73" # Okabe-Ito position 1
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COLOR_DECREASE = "#D55E00" # Okabe-Ito position 2
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sns.set_theme(
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style="ticks",
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rc={
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"figure.facecolor": PAGE_BG,
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"axes.facecolor": PAGE_BG,
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"axes.edgecolor": INK_SOFT,
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"axes.labelcolor": INK,
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"text.color": INK,
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"xtick.color": INK_SOFT,
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"ytick.color": INK_SOFT,
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"grid.color": INK,
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"grid.alpha": 0.10,
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"legend.facecolor": ELEVATED_BG,
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"legend.edgecolor": INK_SOFT,
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},
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)
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# Data — tech company revenue comparison Q1 vs Q4 (four rank crossings)
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data = {
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"entity": ["TechCorp", "DataFlow", "CloudNine", "NetWorks", "CodeBase", "ByteSize", "LogicPro", "SoftEdge"],
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"Q1 Revenue ($M)": [145, 72, 215, 52, 178, 98, 125, 162],
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"Q4 Revenue ($M)": [192, 108, 178, 72, 225, 82, 155, 138],
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"entity": ["StreamPeak", "DataCore", "CloudSync", "NetPulse", "CodeBase", "ByteFlow", "LogicGrid", "TechVault"],
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"Q1 ($M)": [50, 110, 165, 220, 275, 325, 378, 430],
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"Q4 ($M)": [95, 60, 230, 178, 335, 268, 415, 368],
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}
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df = pd.DataFrame(data)
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# Calculate change for color coding
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df["change"] = df["Q4 Revenue ($M)"] - df["Q1 Revenue ($M)"]
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df["change"] = df["Q4 ($M)"] - df["Q1 ($M)"]
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df["direction"] = df["change"].apply(lambda x: "Increase" if x > 0 else "Decrease")
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df = df.sort_values("Q1 ($M)").reset_index(drop=True)
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# Sort by Q1 value for better visual layout
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df = df.sort_values("Q1 Revenue ($M)").reset_index(drop=True)
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# Create figure
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fig, ax = plt.subplots(figsize=(16, 9))
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sns.set_style("whitegrid")
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# Define colors - Python palette
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colors = {"Increase": "#306998", "Decrease": "#FFD43B"}
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# Reshape data for seaborn
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df_melted = df.melt(
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id_vars=["entity", "direction"],
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value_vars=["Q1 Revenue ($M)", "Q4 Revenue ($M)"],
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var_name="Period",
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value_name="Revenue",
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id_vars=["entity", "direction"], value_vars=["Q1 ($M)", "Q4 ($M)"], var_name="Period", value_name="Revenue ($M)"
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)
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df_melted["period_num"] = df_melted["Period"].map({"Q1 ($M)": 0, "Q4 ($M)": 1})
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# Plot
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fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
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ax.set_facecolor(PAGE_BG)
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palette = {"Increase": COLOR_INCREASE, "Decrease": COLOR_DECREASE}
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sns.lineplot(
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data=df_melted,
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x="period_num",
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y="Revenue ($M)",
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hue="direction",
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units="entity",
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estimator=None,
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palette=palette,
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linewidth=3.5,
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marker="o",
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markersize=12,
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alpha=0.85,
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legend=False,
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ax=ax,
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)
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# Plot lines for each entity using seaborn
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for entity in df["entity"]:
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entity_data = df_melted[df_melted["entity"] == entity]
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direction = entity_data["direction"].iloc[0]
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sns.lineplot(
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data=entity_data,
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x="Period",
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y="Revenue",
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color=colors[direction],
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linewidth=3.5,
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alpha=0.85,
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marker="o",
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markersize=14,
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ax=ax,
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)
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# Add entity labels at both ends
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for _idx, row in df.iterrows():
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color = colors[row["direction"]]
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q1_val = row["Q1 Revenue ($M)"]
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q4_val = row["Q4 Revenue ($M)"]
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# Endpoint labels at both axes
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for _, row in df.iterrows():
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color = palette[row["direction"]]
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q1_val = int(row["Q1 ($M)"])
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q4_val = int(row["Q4 ($M)"])
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# Left labels (Q1)
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ax.annotate(
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f"{row['entity']} ({q1_val})",
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xy=(0, q1_val),
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xytext=(-12, 0),
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xytext=(-14, 0),
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textcoords="offset points",
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fontsize=15,
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fontsize=14,
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color=color,
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ha="right",
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va="center",
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fontweight="bold",
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)
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# Right labels (Q4)
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ax.annotate(
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f"({q4_val}) {row['entity']}",
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xy=(1, q4_val),
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xytext=(12, 0),
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xytext=(14, 0),
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textcoords="offset points",
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fontsize=15,
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fontsize=14,
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color=color,
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ha="left",
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va="center",
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fontweight="bold",
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)
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# Style adjustments
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# Style
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ax.set_xticks([0, 1])
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ax.set_xticklabels(["Q1 Revenue ($M)", "Q4 Revenue ($M)"], fontsize=16, color=INK_SOFT)
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ax.set_xlabel("")
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ax.set_ylabel("Revenue ($M)", fontsize=20)
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ax.set_title("slope-basic · seaborn · pyplots.ai", fontsize=24, fontweight="bold", pad=20)
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ax.tick_params(axis="both", labelsize=16)
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ax.set_ylabel("Revenue ($M)", fontsize=20, color=INK)
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ax.set_title("slope-basic · seaborn · anyplot.ai", fontsize=24, fontweight="bold", pad=20, color=INK)
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ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
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ax.set_xlim(-0.15, 1.15)
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# Add padding to y-axis for labels
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y_min = min(df["Q1 Revenue ($M)"].min(), df["Q4 Revenue ($M)"].min())
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y_max = max(df["Q1 Revenue ($M)"].max(), df["Q4 Revenue ($M)"].max())
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y_padding = (y_max - y_min) * 0.08
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y_min = min(df["Q1 ($M)"].min(), df["Q4 ($M)"].min())
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y_max = max(df["Q1 ($M)"].max(), df["Q4 ($M)"].max())
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y_padding = (y_max - y_min) * 0.10
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ax.set_ylim(y_min - y_padding, y_max + y_padding)
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ax.grid(True, alpha=0.3, linestyle="--")
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ax.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK)
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ax.spines["top"].set_visible(False)
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ax.spines["right"].set_visible(False)
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for spine in ("left", "bottom"):
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ax.spines[spine].set_color(INK_SOFT)
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# Add legend for direction
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# Legend
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legend_elements = [
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Line2D([0], [0], color="#306998", linewidth=3.5, marker="o", markersize=10, label="Increase"),
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Line2D([0], [0], color="#FFD43B", linewidth=3.5, marker="o", markersize=10, label="Decrease"),
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Line2D([0], [0], color=COLOR_INCREASE, linewidth=3.5, marker="o", markersize=10, label="Increase"),
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Line2D([0], [0], color=COLOR_DECREASE, linewidth=3.5, marker="o", markersize=10, label="Decrease"),
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]
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ax.legend(handles=legend_elements, loc="lower right", fontsize=16, framealpha=0.9)
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ax.legend(
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handles=legend_elements, loc="lower right", fontsize=16, framealpha=0.9, facecolor=ELEVATED_BG, edgecolor=INK_SOFT
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)
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plt.tight_layout()
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plt.subplots_adjust(left=0.22, right=0.78)
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plt.savefig("plot.png", dpi=300, bbox_inches="tight")
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plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

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