diff --git a/soninrv/docs/data/lab2/plots.py b/soninrv/docs/data/lab2/plots.py
new file mode 100644
index 0000000..42591c7
--- /dev/null
+++ b/soninrv/docs/data/lab2/plots.py
@@ -0,0 +1,63 @@
+import csv
+import statistics
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+rows = []
+with open("results.csv", encoding="utf-8") as f:
+    for r in csv.DictReader(f):
+        rows.append(r)
+
+MAZES    = ["small_10x10", "medium_50x50", "large_100x100",
+            "empty_30x30", "no_exit_20x20", "weighted_40x40"]
+STRATS   = ["BFS", "DFS", "A*", "Dijkstra"]
+MAZE_RU  = {
+    "small_10x10":   "10×10",
+    "medium_50x50":  "50×50",
+    "large_100x100": "100×100",
+    "empty_30x30":   "30×30 пустой",
+    "no_exit_20x20": "20×20 без выхода",
+    "weighted_40x40":"40×40 взвешенный",
+}
+
+def avg(maze, strat, metric):
+    vals = [float(r[metric]) for r in rows
+            if r["maze"] == maze and r["strategy"] == strat]
+    return statistics.mean(vals) if vals else 0.0
+
+def std(maze, strat, metric):
+    vals = [float(r[metric]) for r in rows
+            if r["maze"] == maze and r["strategy"] == strat]
+    return statistics.stdev(vals) if len(vals) > 1 else 0.0
+
+
+fig, axes = plt.subplots(1, 3, figsize=(16, 5))
+fig.suptitle("Сравнение алгоритмов (среднее, 7 запусков)")
+
+x = np.arange(len(MAZES))
+W = 0.18
+offsets = np.linspace(-(len(STRATS)-1)/2, (len(STRATS)-1)/2, len(STRATS)) * W
+
+for ax, (metric, ylabel, title) in zip(axes, [
+    ("time_ms",       "Время (мс)",      "Время выполнения"),
+    ("visited_cells", "Посещено клеток", "Посещённые клетки"),
+    ("path_length",   "Длина пути",      "Длина найденного пути"),
+]):
+    for i, strat in enumerate(STRATS):
+        vals = [avg(m, strat, metric) for m in MAZES]
+        errs = [std(m, strat, metric) for m in MAZES]
+        ax.bar(x + offsets[i], vals, W * 0.95, label=strat, yerr=errs, capsize=3)
+    ax.set_title(title)
+    ax.set_xticks(x)
+    ax.set_xticklabels([MAZE_RU[m] for m in MAZES], fontsize=7, rotation=15)
+    ax.set_ylabel(ylabel)
+    ax.legend(fontsize=8)
+    ax.yaxis.grid(True, linestyle="--", alpha=0.5)
+    ax.set_axisbelow(True)
+    if metric == "time_ms":
+        ax.set_yscale("log")
+
+plt.tight_layout()
+plt.savefig("../../performance_plot.png", dpi=150)
+plt.close()
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