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diff --git a/lomakinae/docs/data/01/src/plot.py b/lomakinae/docs/data/01/src/plot.py
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+++ b/lomakinae/docs/data/01/src/plot.py
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+import pandas as pd
+import matplotlib.pyplot as plt
+from pathlib import Path
+
+BASE_DIR = Path(__file__).resolve().parent.parent
+DATA_PATH = BASE_DIR / "results.csv"
+ATTACHMENTS_DIR = BASE_DIR / "attachments"
+
+
+def shuffled_sorted_plots(structures, df):
+    for mode in ['shuffled', 'sorted']:
+        mode_title = 'перемешанные данные' if mode == 'shuffled' else 'отсортированные данные'
+        fig, axes = plt.subplots(1, 3, figsize=(15, 6))
+        fig.suptitle(f'Производительность — {mode_title}')
+    
+        for ax, op in zip(axes, ['insert', 'find', 'delete']):
+            subset = df[(df['mode'] == mode) & (df['operation'] == op)]
+            structures_average = subset.groupby('structure')['time_sec'].mean()
+            means = [structures_average[s] for s in structures]
+            
+            bars = ax.bar(structures, means, color=['#4C72B0', '#55A868', '#C44E52'])
+            ax.set_title(op)
+            ax.set_ylabel('t (с)')
+            ax.set_yscale('log')
+            ax.grid(True, axis='y', alpha=0.3)
+    
+            for bar, val in zip(bars, means):
+                label = f'{val:.5f}' if val > 0.0001 else f'{val:.1e}'
+                ax.text(bar.get_x() + bar.get_width() / 2, bar.get_height(),
+                        label, ha='center', va='bottom', fontsize=9)
+    
+        plt.tight_layout()
+        save_path = ATTACHMENTS_DIR / f'plot_{mode}.png'
+        plt.savefig(save_path, dpi=300)
+        plt.close()
+        print(f'Saved: {save_path.name}')
+
+
+def bst_shuffled_vs_sorted(df):
+    fig, ax = plt.subplots(figsize=(7, 5))
+    fig.suptitle('Производительность bst_insert(): перемешанные и упорядоченные данные')
+    
+    bst_insert = df[(df['structure'] == 'BST') & (df['operation'] == 'insert')]
+    modes_average = bst_insert.groupby('mode')['time_sec'].mean()
+    modes = ['shuffled', 'sorted']
+    means = [modes_average[m] for m in modes]
+    
+    bars = ax.bar(modes, means, color=['#4C72B0', '#C44E52'])
+    ax.set_ylabel('t (c)')
+    ax.set_yscale('log')
+    ax.grid(True, axis='y', alpha=0.3)
+    
+    for bar, val in zip(bars, means):
+        label = f'{val:.5f}' if val > 0.0001 else f'{val:.1e}'
+        ax.text(bar.get_x() + bar.get_width() / 2, bar.get_height(),
+                label, ha='center', va='bottom', fontsize=10)
+    
+    plt.tight_layout()
+    save_path = ATTACHMENTS_DIR / 'plot_bst_comparison.png'
+    plt.savefig(save_path, dpi=300)
+    plt.close()
+    print(f'Saved: {save_path.name}')
+
+
+def build_plots():
+    ATTACHMENTS_DIR.mkdir(exist_ok=True)
+    
+    if not DATA_PATH.exists():
+            raise ValueError(f"File not found: {DATA_PATH}")
+    
+    df = pd.read_csv(DATA_PATH)
+    
+    STRUCTURES = ['LinkedList', 'HashTable', 'BST']
+    
+    shuffled_sorted_plots(STRUCTURES, df)
+    bst_shuffled_vs_sorted(df)
+
+
+if __name__ == "__main__":
+    build_plots()