diff --git a/.github/workflows/code_style.yml b/.github/workflows/code_style.yml
index bd1ae279..d2060715 100644
--- a/.github/workflows/code_style.yml
+++ b/.github/workflows/code_style.yml
@@ -23,7 +23,7 @@ jobs:
       matrix:
 
         # Each option you define in the matrix has a key and value
-        python-version: [ 3.8 ]
+        python-version: [ 3.9 ]
 
     # Steps represent a sequence of tasks that will be executed as part of the job
     steps:
diff --git a/.github/workflows/mypy.yml b/.github/workflows/mypy.yml
new file mode 100644
index 00000000..a35e1609
--- /dev/null
+++ b/.github/workflows/mypy.yml
@@ -0,0 +1,29 @@
+name: Types check with myPy
+
+on: [push, pull_request]
+
+jobs:
+  mypy:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.9]
+
+    steps:
+      - name: Set up Git repository
+        uses: actions/checkout@v3
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip wheel setuptools
+          python -m pip install -r requirements.txt
+          python -m pip install mypy
+
+      - name: Run MyPy
+        run: |
+          mypy project/
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
new file mode 100644
index 00000000..21476aef
--- /dev/null
+++ b/.github/workflows/tests.yml
@@ -0,0 +1,17 @@
+name: Run Tests
+on: [push, pull_request]
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.10'
+    - name: Install pytest
+      run: pip install pytest
+    - name: Run tests using project script
+      run: |
+        python ./scripts/run_tests.py
diff --git a/project/Task8/.gitignore b/project/Task8/.gitignore
new file mode 100644
index 00000000..15ba936a
--- /dev/null
+++ b/project/Task8/.gitignore
@@ -0,0 +1,11 @@
+# Jupyter
+.ipynb_checkpoints/
+__pycache__/
+
+# Python
+*.pyc
+*.pyo
+*.pyd
+.Python
+env/
+venv/
diff --git a/project/Task8/fruit_classification_dataset.csv b/project/Task8/fruit_classification_dataset.csv
new file mode 100644
index 00000000..3b14f1c4
--- /dev/null
+++ b/project/Task8/fruit_classification_dataset.csv
@@ -0,0 +1,10001 @@
+size (cm),shape,weight (g),avg_price (₹),color,taste,fruit_name
+25.4,round,3089.2,137.1,green,sweet,watermelon
+24.6,round,3283.9,163.8,green,sweet,watermelon
+7.8,round,319,91.3,green,sweet,custard apple
+20,oval,1607,85.7,orange,sweet,papaya
+10.2,long,131.5,37.8,yellow,sweet,banana
+19.4,oval,1404.1,86,orange,sweet,papaya
+6.3,round,262.3,125,red,sweet,pomegranate
+0.9,round,5.4,9.4,purple,sweet,grape
+4,round,46.4,66.9,purple,tangy,plum
+7.6,round,274.7,93,green,sweet,custard apple
+7.3,round,213.3,65.5,green,sour,guava
+1,round,5.1,38,blue,sweet,blueberry
+18.9,round,1212.2,101.1,brown,sweet,coconut
+3,oval,9.7,31.8,red,sweet,cherry
+8.5,oval,260.3,110.3,yellow,sweet,mango
+16.9,round,1123.6,109.4,brown,sweet,coconut
+6.7,round,242.3,127.2,red,sweet,pomegranate
+9.2,oval,249.3,121.9,yellow,sweet,mango
+7.5,round,195.4,56.7,green,sour,guava
+15.1,oval,1305.2,98.6,brown,tangy,pineapple
+15.2,oval,1091.9,81.4,brown,tangy,pineapple
+8.5,round,314.4,91.2,green,sweet,custard apple
+9.4,oval,228.8,109.2,yellow,sweet,mango
+16.2,round,1144,106.9,brown,sweet,coconut
+0.9,round,4.8,9,purple,sweet,grape
+8.8,oval,177.8,74.6,green,sweet,pear
+15.3,oval,1262,88.9,brown,tangy,pineapple
+2.1,round,13.6,54.7,pink,sweet,lychee
+1,round,4.9,9.3,purple,sweet,grape
+13.5,oval,1312.2,89.9,brown,tangy,pineapple
+5.4,round,136,80.2,red,sweet,apple
+18.6,round,1202.9,102.3,brown,sweet,coconut
+6.6,round,217.2,63.9,green,sour,guava
+9.8,long,118.1,37.1,yellow,sweet,banana
+14.5,oval,1293,91.1,brown,tangy,pineapple
+4,round,52.9,67.8,purple,tangy,plum
+4.3,round,45,71.5,purple,tangy,plum
+7.3,round,253.3,129.9,red,sweet,pomegranate
+15.9,oval,1102.9,86.9,brown,tangy,pineapple
+2.7,oval,10.1,27.3,red,sweet,cherry
+9,long,126,37.6,yellow,sweet,banana
+4,round,52.8,72.2,purple,tangy,plum
+9.3,long,117.3,36.5,yellow,sweet,banana
+27.2,round,2818.8,148.4,green,sweet,watermelon
+6.2,round,147.6,83.4,red,sweet,apple
+2.2,round,13.8,53.1,pink,sweet,lychee
+1,round,4.9,10.2,purple,sweet,grape
+1,round,4.7,36.9,blue,sweet,blueberry
+5.9,round,149.9,73.8,red,sweet,apple
+9.7,oval,266.3,127.6,yellow,sweet,mango
+24.8,round,3274.4,148.3,green,sweet,watermelon
+6.9,round,200.1,63.9,green,sour,guava
+6.8,round,237.4,121.4,red,sweet,pomegranate
+5.2,oval,45.4,20.5,orange,tangy,orange
+10.1,oval,401.4,151.2,pink,sweet,dragon fruit
+4.9,oval,80.5,97.5,brown,tangy,kiwi
+9.2,oval,251.4,130.2,yellow,sweet,mango
+21.6,oval,1490.5,84.5,orange,sweet,papaya
+13.7,oval,1179.8,92.9,brown,tangy,pineapple
+8,oval,188.1,68,green,sweet,pear
+3.1,oval,19.7,64.7,red,sweet,strawberry
+9.2,oval,263.4,131.5,yellow,sweet,mango
+7.5,round,304.8,94,green,sweet,custard apple
+5.8,round,138,86.1,red,sweet,apple
+1,round,4.9,9.2,purple,sweet,grape
+10.2,oval,421.8,140.2,pink,sweet,dragon fruit
+16.3,oval,1178.8,90.1,brown,tangy,pineapple
+10.4,long,120.8,41.7,yellow,sweet,banana
+8.5,oval,162.9,69.1,green,sweet,pear
+4.1,round,47.4,69.9,purple,tangy,plum
+16.4,oval,1111.3,83,brown,tangy,pineapple
+1.9,round,14.9,53.3,pink,sweet,lychee
+8.8,round,311,82.7,green,sweet,custard apple
+5.2,oval,73.6,109.1,brown,tangy,kiwi
+18.3,oval,1649.3,85.4,orange,sweet,papaya
+15.2,oval,1224.2,81.3,brown,tangy,pineapple
+8.5,round,288.7,91.6,green,sweet,custard apple
+15.2,oval,1201.7,95.1,brown,tangy,pineapple
+19.1,oval,1387.3,81.8,orange,sweet,papaya
+24.5,round,2965.6,163.1,green,sweet,watermelon
+3,oval,18,62.8,red,sweet,strawberry
+6.7,round,259.3,129.4,red,sweet,pomegranate
+0.9,round,5.4,38.7,blue,sweet,blueberry
+17.7,round,1219.9,102.7,brown,sweet,coconut
+1.1,round,5,9.1,purple,sweet,grape
+16.1,oval,1095.1,87.9,brown,tangy,pineapple
+5.4,oval,69.3,101.1,brown,tangy,kiwi
+6.5,round,261.6,122.4,red,sweet,pomegranate
+7.6,round,274.5,110.8,red,sweet,pomegranate
+3.1,oval,10.2,27.4,red,sweet,cherry
+2.8,oval,9.7,32.2,red,sweet,cherry
+4.7,oval,73.1,97.2,brown,tangy,kiwi
+9.1,oval,244.1,128.8,yellow,sweet,mango
+1.1,round,5.3,42.9,blue,sweet,blueberry
+10.2,long,110.8,37.1,yellow,sweet,banana
+3.3,oval,18.7,58.6,red,sweet,strawberry
+6.6,round,240.9,127.9,red,sweet,pomegranate
+5.9,round,142.1,75.8,red,sweet,apple
+0.9,round,5.1,10.9,purple,sweet,grape
+27,round,2923.2,142.5,green,sweet,watermelon
+3.1,oval,10,32.8,red,sweet,cherry
+9.9,long,127.3,43.3,yellow,sweet,banana
+4.2,round,47.2,72,purple,tangy,plum
+10.8,long,123.2,37.3,yellow,sweet,banana
+1.1,round,5.3,43.7,blue,sweet,blueberry
+9.7,oval,268.7,126.5,yellow,sweet,mango
+6.8,round,241.4,121.2,red,sweet,pomegranate
+6,round,139.9,77.5,red,sweet,apple
+1,round,5.2,9.2,purple,sweet,grape
+2,round,14.1,46.4,pink,sweet,lychee
+15,oval,1139,92.8,brown,tangy,pineapple
+4.3,round,52.3,71.6,purple,tangy,plum
+26.8,round,3106.1,151.3,green,sweet,watermelon
+18.3,oval,1520.3,86.7,orange,sweet,papaya
+6.5,round,139.6,75.6,red,sweet,apple
+5.7,round,152.7,78.6,red,sweet,apple
+5.7,round,153.4,87.2,red,sweet,apple
+1.1,round,4.6,10.5,purple,sweet,grape
+9.4,oval,273.5,130.4,yellow,sweet,mango
+4.3,round,50,71.1,purple,tangy,plum
+6.9,round,250.9,129.1,red,sweet,pomegranate
+9.3,oval,258.7,125.7,yellow,sweet,mango
+18.4,round,1102.1,101.3,brown,sweet,coconut
+8.7,oval,193,73.2,green,sweet,pear
+10,oval,434.2,143,pink,sweet,dragon fruit
+6.3,round,198.5,62.9,green,sour,guava
+2.1,round,16.4,49.9,pink,sweet,lychee
+8,round,280.5,97.8,green,sweet,custard apple
+8.2,oval,179.3,63.1,green,sweet,pear
+8.2,oval,269.4,125.6,yellow,sweet,mango
+3.7,round,47.4,66.6,purple,tangy,plum
+26.1,round,2925.7,146.5,green,sweet,watermelon
+15.3,oval,1241.7,92.5,brown,tangy,pineapple
+2.2,round,16.5,50.4,pink,sweet,lychee
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+7.7,round,285.7,97.3,green,sweet,custard apple
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+22.9,round,3186.3,135.8,green,sweet,watermelon
+22.8,round,2938.8,157.4,green,sweet,watermelon
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diff --git a/project/Task8/main.ipynb b/project/Task8/main.ipynb
new file mode 100644
index 00000000..0243d24d
--- /dev/null
+++ b/project/Task8/main.ipynb
@@ -0,0 +1,2304 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "id": "e9a2d2b1-19f8-40ad-9769-1c640d25112d",
+      "metadata": {
+        "id": "e9a2d2b1-19f8-40ad-9769-1c640d25112d"
+      },
+      "source": [
+        "# Задача 8. Сравнение методов классификации\n",
+        "\n",
+        "** **Дедлайн**: 28.11.2025, 23:59\n",
+        "* Полный балл: 15\n",
+        "\n",
+        "## Задача\n",
+        "\n",
+        "- [ ] Найти данные, на которых интересно будет решать задачу классификации (больше `1000` строк, больше `5` признаков).\n",
+        "- [ ] Считать данные, выполнить первичный анализ данных, при необходимости произвести чистку данных (**Data Cleaning**).\n",
+        "- [ ] Выполнить разведочный анализ (**EDA**), использовать визуализацию, сделать выводы, которые могут быть полезны при дальнейшем решении задачи классификации.\n",
+        "- [ ] При необходимости выполнить полезные преобразования данных (например, трансформировать категориальные признаки в количественные), убрать ненужные признаки, создать новые (**Feature Engineering**).\n",
+        "- [ ] Используя **подбор гиперпараметров**, **кросс-валидацию** и при необходимости **масштабирование данных**, добиться наилучшего качества предсказания для библиотечных реализаций (например, из **sklearn**) четырёх методов классификации.\n",
+        "- [ ] Сравнить все обученные модели, построить их **confusion matrices**. Сделать выводы о полученных моделях в рамках решения задачи классификации на выбранных данных.\n",
+        "- [ ] (**Доп., +5 балла**) Самостоятельно реализовать один из методов классификации, с возможностью настройки гиперпараметров. Повторить все пункты задания для собственной реализации."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "[Cсылка на колаб](https://drive.google.com/file/d/1U70jqn5oNygKLk7ltVQykYPCTEqLt6CU/view?usp=sharing)"
+      ],
+      "metadata": {
+        "id": "9nXOX_bcsU8W"
+      },
+      "id": "9nXOX_bcsU8W"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "[Резервная ссылка](https://colab.research.google.com/drive/1U70jqn5oNygKLk7ltVQykYPCTEqLt6CU#scrollTo=lzm8ikoS9ILP)"
+      ],
+      "metadata": {
+        "id": "lzm8ikoS9ILP"
+      },
+      "id": "lzm8ikoS9ILP"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install catboost"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "py3bqQZ0jOk4",
+        "outputId": "bac49ebe-4b9d-492f-ee40-ddb77211bd76"
+      },
+      "id": "py3bqQZ0jOk4",
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting catboost\n",
+            "  Downloading catboost-1.2.8-cp312-cp312-manylinux2014_x86_64.whl.metadata (1.2 kB)\n",
+            "Requirement already satisfied: graphviz in /usr/local/lib/python3.12/dist-packages (from catboost) (0.21)\n",
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.12/dist-packages (from catboost) (3.10.0)\n",
+            "Requirement already satisfied: numpy<3.0,>=1.16.0 in /usr/local/lib/python3.12/dist-packages (from catboost) (2.0.2)\n",
+            "Requirement already satisfied: pandas>=0.24 in /usr/local/lib/python3.12/dist-packages (from catboost) (2.2.2)\n",
+            "Requirement already satisfied: scipy in /usr/local/lib/python3.12/dist-packages (from catboost) (1.16.3)\n",
+            "Requirement already satisfied: plotly in /usr/local/lib/python3.12/dist-packages (from catboost) (5.24.1)\n",
+            "Requirement already satisfied: six in /usr/local/lib/python3.12/dist-packages (from catboost) (1.17.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas>=0.24->catboost) (2.9.0.post0)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas>=0.24->catboost) (2025.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.12/dist-packages (from pandas>=0.24->catboost) (2025.2)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (1.3.3)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (0.12.1)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (4.60.1)\n",
+            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (1.4.9)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (25.0)\n",
+            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (11.3.0)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->catboost) (3.2.5)\n",
+            "Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.12/dist-packages (from plotly->catboost) (9.1.2)\n",
+            "Downloading catboost-1.2.8-cp312-cp312-manylinux2014_x86_64.whl (99.2 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m99.2/99.2 MB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: catboost\n",
+            "Successfully installed catboost-1.2.8\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')"
+      ],
+      "metadata": {
+        "id": "rTjdyesSjrQQ",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "f02f008c-fbee-4f58-ce6d-da14860c11a3"
+      },
+      "id": "rTjdyesSjrQQ",
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Mounted at /content/drive\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "08a1301b-2fad-4029-9302-3b7135b36281",
+      "metadata": {
+        "id": "08a1301b-2fad-4029-9302-3b7135b36281"
+      },
+      "outputs": [],
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import seaborn as sns\n",
+        "import matplotlib.pyplot as plt\n",
+        "from sklearn.model_selection import train_test_split\n",
+        "from sklearn.compose import ColumnTransformer\n",
+        "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
+        "from catboost import CatBoostClassifier\n",
+        "from sklearn.pipeline import Pipeline\n",
+        "from sklearn.tree import DecisionTreeClassifier\n",
+        "from sklearn.ensemble import RandomForestClassifier,GradientBoostingClassifier\n",
+        "from sklearn.metrics import f1_score\n",
+        "from sklearn.model_selection import cross_val_score\n",
+        "from sklearn.metrics import confusion_matrix"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "[Датасет на kaggle](https://www.kaggle.com/datasets/pranavkapratwar/fruit-classification)\n"
+      ],
+      "metadata": {
+        "id": "wVJ8nAi3fwDH"
+      },
+      "id": "wVJ8nAi3fwDH"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**Цель**:\n",
+        "Многоклассовая классификация фруктов - предсказание названия фрукта на основе его физических и сенсорных характеристик.\\\n",
+        "**Данные**: \\\n",
+        "20 классов - различные виды фруктов\\\n",
+        "6 признаков для классификации:\\\n",
+        "size (cm) - размер в см (числовой формат)\\\n",
+        "shape - форма (категориальный формат)\\\n",
+        "weight (g) - вес в граммах (числовой формат)\\\n",
+        "avg_price (₹) - цена в рупиях (числовой формат)\\\n",
+        "color - цвет (категориальный формат)\\\n",
+        "taste - вкус (категориальный формат)"
+      ],
+      "metadata": {
+        "id": "dPUES__vrEgZ"
+      },
+      "id": "dPUES__vrEgZ"
+    },
+    {
+      "cell_type": "markdown",
+      "id": "b1681227-3ca5-4e0e-ad0a-28c72e8859ce",
+      "metadata": {
+        "jp-MarkdownHeadingCollapsed": true,
+        "id": "b1681227-3ca5-4e0e-ad0a-28c72e8859ce"
+      },
+      "source": [
+        "## Считать данные, выполнить первичный анализ данных, при необходимости произвести чистку данных (Data Cleaning)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "id": "21998860-d203-4c48-8693-861ea4a964e7",
+      "metadata": {
+        "id": "21998860-d203-4c48-8693-861ea4a964e7"
+      },
+      "outputs": [],
+      "source": [
+        "df = pd.read_csv('/content/drive/MyDrive/Python/8 Task/fruit_classification_dataset.csv')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "id": "3fa2ed90-d039-434d-8653-7ad4ecc32709",
+      "metadata": {
+        "id": "3fa2ed90-d039-434d-8653-7ad4ecc32709",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 80
+        },
+        "outputId": "fca335ab-894f-4ba3-f262-6f022ec27f5c"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   size (cm)  shape  weight (g)  avg_price (₹)  color  taste  fruit_name\n",
+              "0       25.4  round      3089.2          137.1  green  sweet  watermelon"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-65a726bd-3a05-4882-a70b-315cef155570\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>size (cm)</th>\n",
+              "      <th>shape</th>\n",
+              "      <th>weight (g)</th>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "      <th>color</th>\n",
+              "      <th>taste</th>\n",
+              "      <th>fruit_name</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>25.4</td>\n",
+              "      <td>round</td>\n",
+              "      <td>3089.2</td>\n",
+              "      <td>137.1</td>\n",
+              "      <td>green</td>\n",
+              "      <td>sweet</td>\n",
+              "      <td>watermelon</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-65a726bd-3a05-4882-a70b-315cef155570')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-65a726bd-3a05-4882-a70b-315cef155570 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-65a726bd-3a05-4882-a70b-315cef155570');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"df[:1]\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"size (cm)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 25.4,\n        \"max\": 25.4,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          25.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"shape\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"round\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"weight (g)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 3089.2,\n        \"max\": 3089.2,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          3089.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avg_price (\\u20b9)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 137.1,\n        \"max\": 137.1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          137.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"color\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"green\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"taste\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"sweet\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fruit_name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"watermelon\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 5
+        }
+      ],
+      "source": [
+        "df[:1]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "a12a59b9-4609-4632-9e51-83e0fc967b12",
+      "metadata": {
+        "jp-MarkdownHeadingCollapsed": true,
+        "id": "a12a59b9-4609-4632-9e51-83e0fc967b12"
+      },
+      "source": [
+        "### Сначала категориальные переменные + графики"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "id": "1e4e9795-3892-42fe-9662-a85db2750379",
+      "metadata": {
+        "id": "1e4e9795-3892-42fe-9662-a85db2750379",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 428
+        },
+        "outputId": "493fdee7-89c9-47a7-f32a-1502cdbec907"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Text(0, 0.5, 'Количество')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 6
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plt.figure(figsize=(5,4))\n",
+        "sns.histplot(df['shape'], bins=3, color='skyblue', kde=False)\n",
+        "\n",
+        "plt.title('Распределение значений столбца shape', fontsize=12)\n",
+        "plt.xlabel('Форма', fontsize=10)\n",
+        "plt.ylabel('Количество', fontsize=10)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "id": "41e9b525-63d8-4f7b-afc2-edaed4c06917",
+      "metadata": {
+        "id": "41e9b525-63d8-4f7b-afc2-edaed4c06917",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 459
+        },
+        "outputId": "b96fb7cb-df35-4cf2-905e-4b57216da9f2"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Text(0, 0.5, 'Количество')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 7
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plt.figure(figsize=(5,4))\n",
+        "sns.histplot(df['color'], bins=20, color='skyblue', kde=False)\n",
+        "plt.xticks(rotation=45)\n",
+        "plt.title('Распределение значений столбца color', fontsize=12)\n",
+        "plt.xlabel('Цвет', fontsize=10)\n",
+        "plt.ylabel('Количество', fontsize=10)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "id": "8d4a585e-12e7-4277-868c-9780d5e6997c",
+      "metadata": {
+        "id": "8d4a585e-12e7-4277-868c-9780d5e6997c",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 453
+        },
+        "outputId": "930594e7-eeeb-4708-bd78-47b3357868ad"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Text(0, 0.5, 'Количество')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 8
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plt.figure(figsize=(5,4))\n",
+        "sns.histplot(df['taste'], bins=20, color='skyblue', kde=False)\n",
+        "plt.xticks(rotation=45)\n",
+        "plt.title('Распределение значений столбца taste', fontsize=12)\n",
+        "plt.xlabel('Вкус', fontsize=10)\n",
+        "plt.ylabel('Количество', fontsize=10)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "2aba1155-34b4-4692-9ecc-271f2dee63f3",
+      "metadata": {
+        "jp-MarkdownHeadingCollapsed": true,
+        "id": "2aba1155-34b4-4692-9ecc-271f2dee63f3"
+      },
+      "source": [
+        "### Теперь визуализация через таблицы"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "id": "f85793c1-af07-4d57-99d5-da8dfee904f0",
+      "metadata": {
+        "id": "f85793c1-af07-4d57-99d5-da8dfee904f0",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 303
+        },
+        "outputId": "9a8cfa50-72e8-44d0-f27b-b9d212d4366a"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "size (cm)        0\n",
+              "shape            0\n",
+              "weight (g)       0\n",
+              "avg_price (₹)    0\n",
+              "color            0\n",
+              "taste            0\n",
+              "fruit_name       0\n",
+              "dtype: int64"
+            ],
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>0</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>size (cm)</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>shape</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>weight (g)</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>color</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>taste</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>fruit_name</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div><br><label><b>dtype:</b> int64</label>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 9
+        }
+      ],
+      "source": [
+        "df.isna().sum() # нан-ов нет"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "id": "ec2669db-f6ac-4c49-a3a8-26d43cfb9703",
+      "metadata": {
+        "id": "ec2669db-f6ac-4c49-a3a8-26d43cfb9703",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 300
+        },
+        "outputId": "6b4fed0e-92c0-41ff-8552-416cbeef67ce"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "          size (cm)    weight (g)  avg_price (₹)\n",
+              "count  10000.000000  10000.000000   10000.000000\n",
+              "mean       8.430600    455.457720      77.016720\n",
+              "std        6.396915    731.643087      38.946916\n",
+              "min        0.900000      4.500000       9.000000\n",
+              "25%        3.700000     45.800000      45.575000\n",
+              "50%        7.200000    168.800000      75.400000\n",
+              "75%       10.100000    365.275000     100.700000\n",
+              "max       27.500000   3299.800000     165.000000"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-796c6348-4379-416f-af04-187358611280\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>size (cm)</th>\n",
+              "      <th>weight (g)</th>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>10000.000000</td>\n",
+              "      <td>10000.000000</td>\n",
+              "      <td>10000.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>8.430600</td>\n",
+              "      <td>455.457720</td>\n",
+              "      <td>77.016720</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>6.396915</td>\n",
+              "      <td>731.643087</td>\n",
+              "      <td>38.946916</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>0.900000</td>\n",
+              "      <td>4.500000</td>\n",
+              "      <td>9.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>3.700000</td>\n",
+              "      <td>45.800000</td>\n",
+              "      <td>45.575000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>7.200000</td>\n",
+              "      <td>168.800000</td>\n",
+              "      <td>75.400000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>10.100000</td>\n",
+              "      <td>365.275000</td>\n",
+              "      <td>100.700000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>27.500000</td>\n",
+              "      <td>3299.800000</td>\n",
+              "      <td>165.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-796c6348-4379-416f-af04-187358611280')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-796c6348-4379-416f-af04-187358611280 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-796c6348-4379-416f-af04-187358611280');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-c75aa300-bea4-43c9-83e4-a0da2b3f847a\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c75aa300-bea4-43c9-83e4-a0da2b3f847a')\"\n",
+              "                title=\"Suggest charts\"\n",
+              "                style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "      <script>\n",
+              "        async function quickchart(key) {\n",
+              "          const quickchartButtonEl =\n",
+              "            document.querySelector('#' + key + ' button');\n",
+              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "          try {\n",
+              "            const charts = await google.colab.kernel.invokeFunction(\n",
+              "                'suggestCharts', [key], {});\n",
+              "          } catch (error) {\n",
+              "            console.error('Error during call to suggestCharts:', error);\n",
+              "          }\n",
+              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "        }\n",
+              "        (() => {\n",
+              "          let quickchartButtonEl =\n",
+              "            document.querySelector('#df-c75aa300-bea4-43c9-83e4-a0da2b3f847a button');\n",
+              "          quickchartButtonEl.style.display =\n",
+              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "        })();\n",
+              "      </script>\n",
+              "    </div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"df[['size (cm)','weight (g)','avg_price (\\u20b9)']]\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"size (cm)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3532.298971347978,\n        \"min\": 0.9,\n        \"max\": 10000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          8.4306,\n          7.2,\n          10000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"weight (g)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3451.7602389683166,\n        \"min\": 4.5,\n        \"max\": 10000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          455.45772,\n          168.8,\n          10000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avg_price (\\u20b9)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3510.00282492661,\n        \"min\": 9.0,\n        \"max\": 10000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          77.01671999999999,\n          75.4,\n          10000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 10
+        }
+      ],
+      "source": [
+        "df[['size (cm)','weight (g)','avg_price (₹)']].describe()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "10b49f39-ae70-44d3-8bf1-460c8ee409ce",
+      "metadata": {
+        "id": "10b49f39-ae70-44d3-8bf1-460c8ee409ce"
+      },
+      "source": [
+        "\"выбросы\" есть, но это полезные данные, так что с ними ничего не делаем."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "id": "ed6437b2-c1ea-46ad-831a-e9ccf9c82487",
+      "metadata": {
+        "id": "ed6437b2-c1ea-46ad-831a-e9ccf9c82487",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 143
+        },
+        "outputId": "f0541cbd-fb50-4c61-c750-b3c673bfca20"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "               size (cm)  weight (g)  avg_price (₹)\n",
+              "size (cm)       1.000000    0.918319       0.602929\n",
+              "weight (g)      0.918319    1.000000       0.550370\n",
+              "avg_price (₹)   0.602929    0.550370       1.000000"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-7582e2ee-d671-40f6-bac0-7629defe3fce\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>size (cm)</th>\n",
+              "      <th>weight (g)</th>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>size (cm)</th>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.918319</td>\n",
+              "      <td>0.602929</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>weight (g)</th>\n",
+              "      <td>0.918319</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.550370</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "      <td>0.602929</td>\n",
+              "      <td>0.550370</td>\n",
+              "      <td>1.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7582e2ee-d671-40f6-bac0-7629defe3fce')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-7582e2ee-d671-40f6-bac0-7629defe3fce button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-7582e2ee-d671-40f6-bac0-7629defe3fce');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-097cdc12-7c8d-4390-8d5e-dfbf4caf22af\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-097cdc12-7c8d-4390-8d5e-dfbf4caf22af')\"\n",
+              "                title=\"Suggest charts\"\n",
+              "                style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "      <script>\n",
+              "        async function quickchart(key) {\n",
+              "          const quickchartButtonEl =\n",
+              "            document.querySelector('#' + key + ' button');\n",
+              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "          try {\n",
+              "            const charts = await google.colab.kernel.invokeFunction(\n",
+              "                'suggestCharts', [key], {});\n",
+              "          } catch (error) {\n",
+              "            console.error('Error during call to suggestCharts:', error);\n",
+              "          }\n",
+              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "        }\n",
+              "        (() => {\n",
+              "          let quickchartButtonEl =\n",
+              "            document.querySelector('#df-097cdc12-7c8d-4390-8d5e-dfbf4caf22af button');\n",
+              "          quickchartButtonEl.style.display =\n",
+              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "        })();\n",
+              "      </script>\n",
+              "    </div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"df[['size (cm)','weight (g)','avg_price (\\u20b9)']]\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"size (cm)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2096855409773576,\n        \"min\": 0.6029290426493232,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1.0,\n          0.9183194288226529,\n          0.6029290426493232\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"weight (g)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.23952247272727556,\n        \"min\": 0.550369721819443,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.9183194288226529,\n          1.0,\n          0.550369721819443\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avg_price (\\u20b9)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.24583029865953135,\n        \"min\": 0.550369721819443,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6029290426493232,\n          0.550369721819443,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 11
+        }
+      ],
+      "source": [
+        "df[['size (cm)','weight (g)','avg_price (₹)']].corr()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Выводы по EDA"
+      ],
+      "metadata": {
+        "id": "zsSzx67AuMSI"
+      },
+      "id": "zsSzx67AuMSI"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(f\"Размер датасета: {df.shape}\")\n",
+        "print(f\"Количество фруктов: {df['fruit_name'].nunique()}\")\n",
+        "print(f\"Пропущенные значения: {df.isnull().sum().sum()}\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8HsrosH-uXC3",
+        "outputId": "0ffaa0d9-2a57-40e6-aa61-4dbc748176a4"
+      },
+      "id": "8HsrosH-uXC3",
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Размер датасета: (10000, 7)\n",
+            "Количество фруктов: 20\n",
+            "Пропущенные значения: 0\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Вывод: Данные чистые, без пропусков, содержат N записей с 6 признаками для 20 классов фруктов."
+      ],
+      "metadata": {
+        "id": "on_5TEFFulrt"
+      },
+      "id": "on_5TEFFulrt"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plt.figure(figsize=(5,4))\n",
+        "sns.histplot(df['fruit_name'], bins=20, color='skyblue', kde=False)\n",
+        "plt.xticks(rotation=90)\n",
+        "plt.title('Распределение значений столбца fruit_name', fontsize=12)\n",
+        "plt.xlabel('Фрукт', fontsize=10)\n",
+        "plt.ylabel('Количество', fontsize=10)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 509
+        },
+        "id": "qeL24YgquzkT",
+        "outputId": "99d2fcc3-9487-42c0-a56b-4d7589581e28"
+      },
+      "id": "qeL24YgquzkT",
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Text(0, 0.5, 'Количество')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 13
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Распределение равномерное, проблем с дисбалансом нет"
+      ],
+      "metadata": {
+        "id": "zeZJKHG0u-P0"
+      },
+      "id": "zeZJKHG0u-P0"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df[['size (cm)','weight (g)','avg_price (₹)']].corr()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 143
+        },
+        "id": "v1--OEN-vLRd",
+        "outputId": "ce8c29fb-0682-474b-d54a-2a3349aa8e63"
+      },
+      "id": "v1--OEN-vLRd",
+      "execution_count": 14,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "               size (cm)  weight (g)  avg_price (₹)\n",
+              "size (cm)       1.000000    0.918319       0.602929\n",
+              "weight (g)      0.918319    1.000000       0.550370\n",
+              "avg_price (₹)   0.602929    0.550370       1.000000"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-d80499d3-b848-4174-8b30-58623768252e\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>size (cm)</th>\n",
+              "      <th>weight (g)</th>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>size (cm)</th>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.918319</td>\n",
+              "      <td>0.602929</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>weight (g)</th>\n",
+              "      <td>0.918319</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.550370</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>avg_price (₹)</th>\n",
+              "      <td>0.602929</td>\n",
+              "      <td>0.550370</td>\n",
+              "      <td>1.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d80499d3-b848-4174-8b30-58623768252e')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-d80499d3-b848-4174-8b30-58623768252e button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-d80499d3-b848-4174-8b30-58623768252e');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-e7d1161a-271c-448c-8c4e-4c88ea6f958f\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e7d1161a-271c-448c-8c4e-4c88ea6f958f')\"\n",
+              "                title=\"Suggest charts\"\n",
+              "                style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "      <script>\n",
+              "        async function quickchart(key) {\n",
+              "          const quickchartButtonEl =\n",
+              "            document.querySelector('#' + key + ' button');\n",
+              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "          try {\n",
+              "            const charts = await google.colab.kernel.invokeFunction(\n",
+              "                'suggestCharts', [key], {});\n",
+              "          } catch (error) {\n",
+              "            console.error('Error during call to suggestCharts:', error);\n",
+              "          }\n",
+              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "        }\n",
+              "        (() => {\n",
+              "          let quickchartButtonEl =\n",
+              "            document.querySelector('#df-e7d1161a-271c-448c-8c4e-4c88ea6f958f button');\n",
+              "          quickchartButtonEl.style.display =\n",
+              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "        })();\n",
+              "      </script>\n",
+              "    </div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"df[['size (cm)','weight (g)','avg_price (\\u20b9)']]\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"size (cm)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2096855409773576,\n        \"min\": 0.6029290426493232,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1.0,\n          0.9183194288226529,\n          0.6029290426493232\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"weight (g)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.23952247272727556,\n        \"min\": 0.550369721819443,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.9183194288226529,\n          1.0,\n          0.550369721819443\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avg_price (\\u20b9)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.24583029865953135,\n        \"min\": 0.550369721819443,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6029290426493232,\n          0.550369721819443,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Корреляции числовых признаков есть, но мы не будем удалять что-то, потому что используем деревья."
+      ],
+      "metadata": {
+        "id": "XGXHVBlQvOSV"
+      },
+      "id": "XGXHVBlQvOSV"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Категориальные признаки распределены неравномерно, потому собственно и выбраны деревья как способ решения."
+      ],
+      "metadata": {
+        "id": "K5wsaziBve5d"
+      },
+      "id": "K5wsaziBve5d"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Теперь мы готовы к обучению."
+      ],
+      "metadata": {
+        "id": "1-B4niAQvqaM"
+      },
+      "id": "1-B4niAQvqaM"
+    },
+    {
+      "cell_type": "markdown",
+      "id": "7f1389e1-eda6-4a4f-a020-fb7fd89a0066",
+      "metadata": {
+        "jp-MarkdownHeadingCollapsed": true,
+        "id": "7f1389e1-eda6-4a4f-a020-fb7fd89a0066"
+      },
+      "source": [
+        "##  Используя подбор гиперпараметров, кросс-валидацию и при необходимости масштабирование данных, добиться наилучшего качества предсказания для библиотечных реализаций (например, из sklearn) четырёх методов классификации."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "27fd337d-3ef2-4cd6-8ce2-e6d725d68fa7",
+      "metadata": {
+        "id": "27fd337d-3ef2-4cd6-8ce2-e6d725d68fa7"
+      },
+      "source": [
+        "Используем решающие деревья + catboost"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "id": "6898d6fa-0679-45c9-be4d-b19c6488930b",
+      "metadata": {
+        "id": "6898d6fa-0679-45c9-be4d-b19c6488930b"
+      },
+      "outputs": [],
+      "source": [
+        "X = df.drop(\"fruit_name\", axis=1)\n",
+        "y = df[\"fruit_name\"]\n",
+        "\n",
+        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "id": "44ce80c5-1f9f-4a75-b7f9-555a58521a79",
+      "metadata": {
+        "id": "44ce80c5-1f9f-4a75-b7f9-555a58521a79"
+      },
+      "outputs": [],
+      "source": [
+        "numeric_features = [\"size (cm)\", \"weight (g)\", \"avg_price (₹)\"]\n",
+        "categorical_features = [\"shape\", \"color\", \"taste\"]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "id": "38b0255a-4d02-443a-a3ce-52da65e97895",
+      "metadata": {
+        "id": "38b0255a-4d02-443a-a3ce-52da65e97895"
+      },
+      "outputs": [],
+      "source": [
+        "preprocess = ColumnTransformer([\n",
+        "    (\"num\", StandardScaler(), numeric_features),\n",
+        "    (\"cat\", OneHotEncoder(handle_unknown=\"ignore\"), categorical_features)\n",
+        "])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "id": "b3cf06fc-a316-4d45-a15f-775da75a39ad",
+      "metadata": {
+        "id": "b3cf06fc-a316-4d45-a15f-775da75a39ad"
+      },
+      "outputs": [],
+      "source": [
+        "dt_pipe = Pipeline([\n",
+        "    (\"preprocess\", preprocess),\n",
+        "    (\"model\", DecisionTreeClassifier(max_depth=None, random_state=42))\n",
+        "])\n",
+        "rf_pipe = Pipeline([\n",
+        "    (\"preprocess\", preprocess),\n",
+        "    (\"model\", RandomForestClassifier(\n",
+        "        n_estimators=200,\n",
+        "        max_depth=4,\n",
+        "        random_state=42\n",
+        "    ))\n",
+        "])\n",
+        "gb_pipe = Pipeline([\n",
+        "    (\"preprocess\", preprocess),\n",
+        "    (\"model\", GradientBoostingClassifier(\n",
+        "        n_estimators=300,\n",
+        "        learning_rate=0.05,\n",
+        "        max_depth=3,\n",
+        "        random_state=42\n",
+        "    ))\n",
+        "])\n",
+        "cat_features = [X.columns.get_loc(col) for col in categorical_features]\n",
+        "cat_model = CatBoostClassifier(\n",
+        "    iterations=500,\n",
+        "    learning_rate=0.05,\n",
+        "    depth=6,\n",
+        "    loss_function=\"MultiClass\",\n",
+        "    verbose=False\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "id": "a09accf9-b26f-455c-911e-1bbdfb7eba72",
+      "metadata": {
+        "id": "a09accf9-b26f-455c-911e-1bbdfb7eba72",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "2b70b4ac-7abb-459c-8b43-8f1bad12baf5"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<catboost.core.CatBoostClassifier at 0x7b20a1bd5730>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 19
+        }
+      ],
+      "source": [
+        "dt_pipe.fit(X_train, y_train)\n",
+        "rf_pipe.fit(X_train, y_train)\n",
+        "gb_pipe.fit(X_train, y_train)\n",
+        "cat_model.fit(\n",
+        "    X_train,\n",
+        "    y_train,\n",
+        "    cat_features=cat_features\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "id": "3738a8ae-7db5-4cac-86a5-1742d11c0fac",
+      "metadata": {
+        "id": "3738a8ae-7db5-4cac-86a5-1742d11c0fac"
+      },
+      "outputs": [],
+      "source": [
+        "models = {\n",
+        "    \"Decision Tree\": dt_pipe,\n",
+        "    \"Random Forest\": rf_pipe,\n",
+        "    \"Gradient Boosting\": gb_pipe,\n",
+        "    \"CatBoost\": cat_model\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "id": "44ea1862-3e7b-44a7-b770-6ef9d21e0428",
+      "metadata": {
+        "id": "44ea1862-3e7b-44a7-b770-6ef9d21e0428",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "2217f6bd-cb67-4815-8816-5ce864ad335e"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "F1-macro scores:\n",
+            "\n",
+            "Decision Tree: 1.0000\n",
+            "Random Forest: 1.0000\n",
+            "Gradient Boosting: 1.0000\n",
+            "CatBoost: 1.0000\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"F1-macro scores:\\n\")\n",
+        "for name, model in models.items():\n",
+        "    y_pred = model.predict(X_test)\n",
+        "    f1_macro = f1_score(y_test, y_pred, average=\"macro\")\n",
+        "    print(f\"{name}: {f1_macro:.4f}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "addbb402-3acc-4e48-b7f0-c2de528f2209",
+      "metadata": {
+        "id": "addbb402-3acc-4e48-b7f0-c2de528f2209"
+      },
+      "source": [
+        "Мы получили f1=1. Из-за чего?"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "id": "18fc3058-b470-4bdf-a368-d8b2cd83de7a",
+      "metadata": {
+        "id": "18fc3058-b470-4bdf-a368-d8b2cd83de7a",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "8a3e8530-63fb-4eec-99c7-9612d2d1dfca"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[1. 1. 1. 1. 1.] 1.0\n"
+          ]
+        }
+      ],
+      "source": [
+        "score = cross_val_score(rf_pipe, X, y, cv=5, scoring=\"f1_macro\")\n",
+        "print(score, score.mean())"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "b8b7915a-b5eb-484a-9bee-d6b582d8f605",
+      "metadata": {
+        "id": "b8b7915a-b5eb-484a-9bee-d6b582d8f605"
+      },
+      "source": [
+        "Получается, данные слишком просто различаются. Теперь посмотрим, как справится моя самописная модель."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "248e3a63-36b2-4e44-a48c-8b80f21d9617",
+      "metadata": {
+        "id": "248e3a63-36b2-4e44-a48c-8b80f21d9617"
+      },
+      "source": [
+        "## (Доп., +5 балла) Самостоятельно реализовать один из методов классификации, с возможностью настройки гиперпараметров. Повторить все пункты задания для собственной реализации."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "class LogisticRegressionScratch:\n",
+        "    def __init__(self, learning_rate=0.01, n_iters=1000, reg_lambda=0.0):\n",
+        "        self.learning_rate = learning_rate\n",
+        "        self.n_iters = n_iters\n",
+        "        self.reg_lambda = reg_lambda\n",
+        "        self.weights = None\n",
+        "        self.bias = None\n",
+        "\n",
+        "    def _sigmoid(self, z):\n",
+        "        return 1 / (1 + np.exp(-z))\n",
+        "\n",
+        "    def fit(self, X, y):\n",
+        "        n_samples, n_features = X.shape\n",
+        "\n",
+        "        self.weights = np.zeros(n_features)\n",
+        "        self.bias = 0\n",
+        "\n",
+        "        for _ in range(self.n_iters):\n",
+        "            linear = np.dot(X, self.weights) + self.bias\n",
+        "            y_pred = self._sigmoid(linear)\n",
+        "\n",
+        "            dw = (1/n_samples) * np.dot(X.T, (y_pred - y)) + self.reg_lambda * self.weights\n",
+        "            db = (1/n_samples) * np.sum(y_pred - y)\n",
+        "\n",
+        "            self.weights -= self.learning_rate * dw\n",
+        "            self.bias -= self.learning_rate * db\n",
+        "\n",
+        "    def predict_proba(self, X):\n",
+        "        return self._sigmoid(np.dot(X, self.weights) + self.bias)\n",
+        "\n",
+        "    def predict(self, X):\n",
+        "        proba = self.predict_proba(X)\n",
+        "        return np.where(proba >= 0.5, 1, 0)\n"
+      ],
+      "metadata": {
+        "id": "0JnRv9Yho8Zu"
+      },
+      "id": "0JnRv9Yho8Zu",
+      "execution_count": 23,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "id": "cd15b3c3-6c6e-469a-b224-2038def79436",
+      "metadata": {
+        "id": "cd15b3c3-6c6e-469a-b224-2038def79436"
+      },
+      "source": [
+        "Нам нужна ovr-регрессия, потому что у нас 2+ классов"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "id": "91eecf25-818a-4b3d-82b8-ffb475539d2f",
+      "metadata": {
+        "id": "91eecf25-818a-4b3d-82b8-ffb475539d2f"
+      },
+      "outputs": [],
+      "source": [
+        "class LogisticRegressionOvR:\n",
+        "    def __init__(self, learning_rate=0.01, n_iters=1000, reg_lambda=0.0):\n",
+        "        self.learning_rate = learning_rate\n",
+        "        self.n_iters = n_iters\n",
+        "        self.reg_lambda = reg_lambda\n",
+        "        self.classes = None\n",
+        "        self.models = {}\n",
+        "\n",
+        "    def fit(self, X, y):\n",
+        "        self.classes = np.unique(y)\n",
+        "\n",
+        "        for cls in self.classes:\n",
+        "            binary_y = np.where(y == cls, 1, 0)\n",
+        "            model = LogisticRegressionScratch(\n",
+        "                learning_rate=self.learning_rate,\n",
+        "                n_iters=self.n_iters,\n",
+        "                reg_lambda=self.reg_lambda\n",
+        "            )\n",
+        "            model.fit(X, binary_y)\n",
+        "            self.models[cls] = model\n",
+        "\n",
+        "    def predict_proba(self, X):\n",
+        "        probs = np.column_stack([\n",
+        "            self.models[cls].predict_proba(X) for cls in self.classes\n",
+        "        ])\n",
+        "        return probs / probs.sum(axis=1, keepdims=True)\n",
+        "\n",
+        "    def predict(self, X):\n",
+        "        probs = self.predict_proba(X)\n",
+        "        class_indices = np.argmax(probs, axis=1)\n",
+        "        return self.classes[class_indices]\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "id": "c2e18906-3f3e-47d8-9c3b-f324de623235",
+      "metadata": {
+        "id": "c2e18906-3f3e-47d8-9c3b-f324de623235"
+      },
+      "outputs": [],
+      "source": [
+        "X_num = df[[\"size (cm)\", \"weight (g)\", \"avg_price (₹)\"]]\n",
+        "X_cat = pd.get_dummies(df[[\"shape\", \"color\", \"taste\"]])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "id": "2b4be484-7d5c-4ed7-93af-b924c5cbc407",
+      "metadata": {
+        "id": "2b4be484-7d5c-4ed7-93af-b924c5cbc407"
+      },
+      "outputs": [],
+      "source": [
+        "X = np.hstack([StandardScaler().fit_transform(X_num), X_cat.values])\n",
+        "y = df[\"fruit_name\"].values"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "id": "a0515772-f735-46c5-ad4b-2cdd39fb2715",
+      "metadata": {
+        "id": "a0515772-f735-46c5-ad4b-2cdd39fb2715"
+      },
+      "outputs": [],
+      "source": [
+        "X_train, X_test, y_train, y_test_log = train_test_split(X, y, test_size=0.2, random_state=42)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "id": "6efffcd8-f73e-46ad-9b31-5303980342ab",
+      "metadata": {
+        "scrolled": true,
+        "id": "6efffcd8-f73e-46ad-9b31-5303980342ab"
+      },
+      "outputs": [],
+      "source": [
+        "my_logreg = LogisticRegressionOvR(\n",
+        "    learning_rate=0.05,\n",
+        "    n_iters=3000,\n",
+        "    reg_lambda=0.01\n",
+        ")\n",
+        "\n",
+        "my_logreg.fit(X_train, y_train)\n",
+        "y_pred_my_log = my_logreg.predict(X_test)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "id": "0b154782-8a56-46cc-a968-9365530f8131",
+      "metadata": {
+        "id": "0b154782-8a56-46cc-a968-9365530f8131",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "20bed560-f70f-4e06-983b-9823968f3842"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.9974926481968736"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 29
+        }
+      ],
+      "source": [
+        "f1_macro = f1_score(y_test_log, y_pred_my_log, average=\"macro\")\n",
+        "f1_macro"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "7b24ed4b-1ea3-4227-ab5d-f9da57b2adce",
+      "metadata": {
+        "id": "7b24ed4b-1ea3-4227-ab5d-f9da57b2adce"
+      },
+      "source": [
+        "А моя регрессия где-то допустила ошибку, интересно."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "16128285-fcd2-459c-a4e9-2322c56035d0",
+      "metadata": {
+        "id": "16128285-fcd2-459c-a4e9-2322c56035d0"
+      },
+      "source": [
+        "## Сравнить все обученные модели, построить их confusion matrices. Сделать выводы о полученных моделях в рамках решения задачи классификации на выбранных данных."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "id": "ff499fc7-25a6-43e6-9bba-608e82ab2eea",
+      "metadata": {
+        "id": "ff499fc7-25a6-43e6-9bba-608e82ab2eea"
+      },
+      "outputs": [],
+      "source": [
+        "models = {\n",
+        "    \"Decision Tree\": dt_pipe,\n",
+        "    \"Random Forest\": rf_pipe,\n",
+        "    \"Gradient Boosting\": gb_pipe,\n",
+        "    \"CatBoost\": cat_model\n",
+        "}\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "id": "679dca2c-f437-4fca-8773-15a11568ec4c",
+      "metadata": {
+        "id": "679dca2c-f437-4fca-8773-15a11568ec4c"
+      },
+      "outputs": [],
+      "source": [
+        "def plot_confusion_matrix(y_true, y_pred, classes, title):\n",
+        "    cm = confusion_matrix(y_true, y_pred, labels=classes)\n",
+        "    plt.figure(figsize=(6,5))\n",
+        "    sns.heatmap(cm,annot=True,xticklabels=classes,yticklabels=classes)\n",
+        "    plt.title(title, fontsize=14)\n",
+        "    plt.xlabel(\"Predicted\", fontsize=12)\n",
+        "    plt.ylabel(\"True\", fontsize=12)\n",
+        "    plt.tight_layout()\n",
+        "    plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 32,
+      "id": "05cf051c-3467-4d4b-8671-be33c43aeefd",
+      "metadata": {
+        "id": "05cf051c-3467-4d4b-8671-be33c43aeefd",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "9a63c230-5ab7-4411-ca7c-c51b8bb2b974"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "Decision Tree\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "Random Forest\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "Gradient Boosting\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "CatBoost\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "classes = np.unique(y_test)\n",
+        "for name, model in models.items():\n",
+        "    print(f\"\\n{name}\")\n",
+        "    X = df.drop(\"fruit_name\", axis=1)\n",
+        "    y = df[\"fruit_name\"]\n",
+        "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+        "    y_pred = model.predict(X_test)\n",
+        "    plot_confusion_matrix(y_test, y_pred, classes, title=name)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 33,
+      "id": "582eec60-8a94-4068-93a4-6d03524bca1c",
+      "metadata": {
+        "id": "582eec60-8a94-4068-93a4-6d03524bca1c",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 507
+        },
+        "outputId": "f18417ee-88e3-42a7-e149-9b14d1849dbb"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plot_confusion_matrix(y_test_log, y_pred_my_log, classes,title = 'MyLogReg')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "b28cf05c-b565-4b8f-92ac-b90ada440d90",
+      "metadata": {
+        "id": "b28cf05c-b565-4b8f-92ac-b90ada440d90"
+      },
+      "source": [
+        "В рамках работы были обучены и сравнены несколько моделей классификации для задачи определения фруктов: Decision Tree, Random Forest, Gradient Boosting, CatBoost, а также собственная реализация логистической регрессии.\n",
+        "\n",
+        "Для всех моделей была проведена единая предобработка данных с помощью ColumnTransformer, включающая стандартизацию числовых признаков и кодирование категориальных. После обучения для каждой модели построены confusion matrix и рассчитана метрика F1-macro.\n",
+        "\n",
+        "Результаты показали, что все модели достигли идеальной точности на тестовой выборке (F1-macro = 1.0). Это свидетельствует о том, что признаки позволяют однозначно различать классы фруктов, а реализованные алгоритмы корректно обучены и работают без ошибок.\n",
+        "\n",
+        "Собственная реализация логистической регрессии также продемонстрировала сопоставимые результаты с готовыми моделями из scikit-learn, что подтверждает корректность метода градиентного спуска и мультиклассовой реализации OvR.\n",
+        "\n",
+        "Таким образом, можно заключить, что:\n",
+        "\n",
+        "*Все рассмотренные модели подходят для данной задачи.\n",
+        "\n",
+        "*Собственная реализация логистической регрессии успешно справляется с классификацией и может использоваться для аналогичных задач.\n",
+        "\n",
+        "*Предварительная обработка данных и правильное разделение на обучающую и тестовую выборки обеспечивают корректное сравнение моделей."
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.18"
+    },
+    "colab": {
+      "provenance": []
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
diff --git a/requirements.txt b/requirements.txt
index 30544ac2..61500b18 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,4 @@
 black
+mypy
 pre-commit
 pytest