{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "34468500",
   "metadata": {},
   "source": [
    "# Доля пассивных показов и заказы\n",
    "\n",
    "**Вопрос:** повышает ли высокая доля пассивных показов вероятность заказа при контроле объёма коммуникаций?\n",
    "\n",
    "**Гипотеза:** большая доля пассивных показов связана с большей вероятностью заказа (проверяем ML)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "46fb7ac5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T19:11:43.639846Z",
     "iopub.status.busy": "2025-12-12T19:11:43.638998Z",
     "iopub.status.idle": "2025-12-12T19:11:50.215868Z",
     "shell.execute_reply": "2025-12-12T19:11:50.213723Z"
    }
   },
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "from pathlib import Path\n",
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import roc_auc_score\n",
    "\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 5)\n",
    "\n",
    "project_root = Path.cwd().resolve()\n",
    "while not (project_root / \"preanalysis\").exists() and project_root.parent != project_root:\n",
    "    project_root = project_root.parent\n",
    "    project_root = project_root.parent\n",
    "sys.path.append(str(project_root / \"preanalysis\"))\n",
    "import eda_utils as eda\n",
    "\n",
    "db_path = project_root / \"dataset\" / \"ds.sqlite\"\n",
    "conn = sqlite3.connect(db_path)\n",
    "df = pd.read_sql_query(\"select * from communications\", conn, parse_dates=[\"business_dt\"])\n",
    "conn.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "73842cf6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T19:11:50.222842Z",
     "iopub.status.busy": "2025-12-12T19:11:50.222356Z",
     "iopub.status.idle": "2025-12-12T19:11:52.672337Z",
     "shell.execute_reply": "2025-12-12T19:11:52.670490Z"
    }
   },
   "outputs": [
    {
     "data": {
      "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>active_imp_total</th>\n",
       "      <th>passive_imp_total</th>\n",
       "      <th>active_click_total</th>\n",
       "      <th>passive_click_total</th>\n",
       "      <th>orders_amt_total</th>\n",
       "      <th>imp_total</th>\n",
       "      <th>click_total</th>\n",
       "      <th>age</th>\n",
       "      <th>gender_cd</th>\n",
       "      <th>device_platform_cd</th>\n",
       "      <th>passive_share</th>\n",
       "      <th>ctr_all</th>\n",
       "      <th>has_order</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Android</td>\n",
       "      <td>0.514706</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>27.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>116.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Android</td>\n",
       "      <td>0.767241</td>\n",
       "      <td>0.198276</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>57.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>293.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>F</td>\n",
       "      <td>Android</td>\n",
       "      <td>0.805461</td>\n",
       "      <td>0.126280</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>F</td>\n",
       "      <td>Android</td>\n",
       "      <td>0.649123</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>23.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>43.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Android</td>\n",
       "      <td>0.465116</td>\n",
       "      <td>0.372093</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    active_imp_total  passive_imp_total  active_click_total  \\\n",
       "id                                                            \n",
       "1               33.0               35.0                14.0   \n",
       "2               27.0               89.0                19.0   \n",
       "3               57.0              236.0                37.0   \n",
       "4               20.0               37.0                14.0   \n",
       "5               23.0               20.0                13.0   \n",
       "\n",
       "    passive_click_total  orders_amt_total  imp_total  click_total   age  \\\n",
       "id                                                                        \n",
       "1                   3.0                 0       68.0         17.0  58.0   \n",
       "2                   4.0                 3      116.0         23.0  54.0   \n",
       "3                   0.0                 2      293.0         37.0  70.0   \n",
       "4                   1.0                 0       57.0         15.0  43.0   \n",
       "5                   3.0                 1       43.0         16.0  46.0   \n",
       "\n",
       "   gender_cd device_platform_cd  passive_share   ctr_all  has_order  \n",
       "id                                                                   \n",
       "1          M            Android       0.514706  0.250000          0  \n",
       "2          M            Android       0.767241  0.198276          1  \n",
       "3          F            Android       0.805461  0.126280          1  \n",
       "4          F            Android       0.649123  0.263158          0  \n",
       "5          M            Android       0.465116  0.372093          1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for cols, name in [\n",
    "    (eda.ACTIVE_IMP_COLS, \"active_imp_total\"),\n",
    "    (eda.PASSIVE_IMP_COLS, \"passive_imp_total\"),\n",
    "    (eda.ACTIVE_CLICK_COLS, \"active_click_total\"),\n",
    "    (eda.PASSIVE_CLICK_COLS, \"passive_click_total\"),\n",
    "    (eda.ORDER_COLS, \"orders_amt_total\"),\n",
    "]:\n",
    "    df[name] = df[cols].sum(axis=1)\n",
    "\n",
    "df[\"imp_total\"] = df[\"active_imp_total\"] + df[\"passive_imp_total\"]\n",
    "df[\"click_total\"] = df[\"active_click_total\"] + df[\"passive_click_total\"]\n",
    "\n",
    "client = df.groupby(\"id\").agg(\n",
    "    {\n",
    "        \"active_imp_total\": \"sum\",\n",
    "        \"passive_imp_total\": \"sum\",\n",
    "        \"active_click_total\": \"sum\",\n",
    "        \"passive_click_total\": \"sum\",\n",
    "        \"orders_amt_total\": \"sum\",\n",
    "        \"imp_total\": \"sum\",\n",
    "        \"click_total\": \"sum\",\n",
    "        \"age\": \"median\",\n",
    "        \"gender_cd\": lambda s: s.mode().iat[0],\n",
    "        \"device_platform_cd\": lambda s: s.mode().iat[0],\n",
    "    }\n",
    ")\n",
    "\n",
    "client[\"passive_share\"] = eda.safe_divide(client[\"passive_imp_total\"], client[\"imp_total\"])\n",
    "client[\"ctr_all\"] = eda.safe_divide(client[\"click_total\"], client[\"imp_total\"])\n",
    "client[\"has_order\"] = (client[\"orders_amt_total\"] > 0).astype(int)\n",
    "client.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98ac09e6",
   "metadata": {},
   "source": [
    "## Визуализация: заказы vs доля пассивных показов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "35bfe71d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T19:11:52.678022Z",
     "iopub.status.busy": "2025-12-12T19:11:52.677564Z",
     "iopub.status.idle": "2025-12-12T19:11:52.998699Z",
     "shell.execute_reply": "2025-12-12T19:11:52.997056Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1046120/906462969.py:2: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  order_rate = client.groupby(bins)[\"has_order\"].mean().reset_index()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = pd.qcut(client[\"passive_share\"], 8, duplicates=\"drop\")\n",
    "order_rate = client.groupby(bins)[\"has_order\"].mean().reset_index()\n",
    "order_rate[\"passive_share\"] = order_rate[\"passive_share\"].astype(str)\n",
    "plt.figure(figsize=(12, 4))\n",
    "sns.lineplot(data=order_rate, x=\"passive_share\", y=\"has_order\", marker=\"o\")\n",
    "plt.xticks(rotation=40)\n",
    "plt.title(\"Доля клиентов с заказом vs доля пассивных показов\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6def67b9",
   "metadata": {},
   "source": [
    "## ML-модель: влияние доли пассивных показов на заказ\n",
    "Target: `has_order`. Фичи: объёмы актив/пассив, клики, возраст, пол, платформа, пассивная доля."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ae61b923",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T19:11:53.004801Z",
     "iopub.status.busy": "2025-12-12T19:11:53.004396Z",
     "iopub.status.idle": "2025-12-12T19:11:53.143675Z",
     "shell.execute_reply": "2025-12-12T19:11:53.141866Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.6804173758429694,\n",
       " num__passive_click_total           0.638861\n",
       " num__passive_share                 0.303223\n",
       " num__active_imp_total              0.216964\n",
       " cat__device_platform_cd_Android    0.186635\n",
       " num__active_click_total           -0.150704\n",
       " cat__gender_cd_M                   0.130234\n",
       " cat__device_platform_cd_iPadOS    -0.105558\n",
       " num__passive_imp_total            -0.087140\n",
       " num__age                          -0.072639\n",
       " cat__device_platform_cd_iOS        0.038500\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = client[[\n",
    "    \"active_imp_total\",\n",
    "    \"passive_imp_total\",\n",
    "    \"active_click_total\",\n",
    "    \"passive_click_total\",\n",
    "    \"passive_share\",\n",
    "    \"age\",\n",
    "    \"gender_cd\",\n",
    "    \"device_platform_cd\",\n",
    "]]\n",
    "X = X.copy()\n",
    "X[\"gender_cd\"] = eda.normalize_gender(X[\"gender_cd\"])\n",
    "X[\"device_platform_cd\"] = eda.normalize_device(X[\"device_platform_cd\"])\n",
    "y = client[\"has_order\"]\n",
    "\n",
    "numeric_cols = [\"active_imp_total\", \"passive_imp_total\", \"active_click_total\", \"passive_click_total\", \"passive_share\", \"age\"]\n",
    "cat_cols = [\"gender_cd\", \"device_platform_cd\"]\n",
    "\n",
    "preprocess = ColumnTransformer(\n",
    "    [\n",
    "        (\"num\", Pipeline([(\"scaler\", StandardScaler())]), numeric_cols),\n",
    "        (\"cat\", OneHotEncoder(handle_unknown=\"ignore\"), cat_cols),\n",
    "    ]\n",
    ")\n",
    "\n",
    "model = Pipeline([(\"pre\", preprocess), (\"clf\", LogisticRegression(max_iter=1000))])\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, stratify=y)\n",
    "model.fit(X_train, y_train)\n",
    "proba = model.predict_proba(X_test)[:, 1]\n",
    "auc = roc_auc_score(y_test, proba)\n",
    "coef = model.named_steps[\"clf\"].coef_[0]\n",
    "features = model.named_steps[\"pre\"].get_feature_names_out()\n",
    "coef_series = pd.Series(coef, index=features).sort_values(key=abs, ascending=False)\n",
    "auc, coef_series.head(10)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7df5ccb7",
   "metadata": {},
   "source": [
    "## Вывод по гипотезе\n",
    "- Линейный рост доли клиентов с заказом при увеличении `passive_share`.\n",
    "- В модели коэффициент при `passive_share` положительный и по модулю в топ‑фичах; AUC ~0.68. Гипотеза подтверждается: высокая доля пассивных показов ассоциирована с большей вероятностью заказа при контроле объёма и кликов."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}