diff --git a/soninrv/docs/data/lab1/plots.py b/soninrv/docs/data/lab1/plots.py
new file mode 100644
index 0000000..6c0df6e
--- /dev/null
+++ b/soninrv/docs/data/lab1/plots.py
@@ -0,0 +1,49 @@
+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)
+ 
+STRUCTS = ["LinkedList", "HashTable", "BST"]
+MODE_MAP = {"shuffled": "случайный", "sorted": "отсортированный"}
+OPS = [("insert", "Вставка"), ("find", "Поиск"), ("delete", "Удаление")]
+ 
+def stats(structure, mode, operation):
+    vals = [float(r["time_sec"]) for r in rows
+            if r["structure"] == structure and r["mode"] == mode and r["operation"] == operation]
+    if not vals:
+        return 0.0, 0.0
+    return statistics.mean(vals), statistics.stdev(vals) if len(vals) > 1 else 0.0
+ 
+fig, axes = plt.subplots(1, 3, figsize=(15, 5))
+fig.suptitle("Среднее время операций (сек, лог-шкала, N=10 000, 5 повторений)")
+ 
+x = np.arange(len(STRUCTS))
+WIDTH = 0.35
+ 
+for ax, (op_key, op_title) in zip(axes, OPS):
+    for i, mode in enumerate(["shuffled", "sorted"]):
+        avgs, stds = [], []
+        for s in STRUCTS:
+            avg, std = stats(s, mode, op_key)
+            avgs.append(avg)
+            stds.append(std)
+        offset = (i - 0.5) * WIDTH
+        ax.bar(x + offset, avgs, WIDTH, label=MODE_MAP[mode])
+        ax.errorbar(x + offset, avgs, yerr=stds, fmt="none", capsize=4)
+    ax.set_yscale("log")
+    ax.set_title(op_title)
+    ax.set_xticks(x)
+    ax.set_xticklabels(STRUCTS)
+    ax.set_ylabel("Время (сек)")
+    ax.yaxis.grid(True, which="both", linestyle="--", alpha=0.5)
+    ax.set_axisbelow(True)
+    ax.legend()
+ 
+plt.tight_layout()
+plt.savefig("../../performance_comparison.png", dpi=150)
+plt.show()
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