{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "918f512c",
   "metadata": {},
   "source": [
    "# Shapash - Time Series Tabular Forecasting\n",
    "\n",
    "This notebook illustrates tabular forecasting: lag creation, calendar features, then local and global interpretation with Shapash."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2322c91c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_absolute_error, r2_score\n",
    "\n",
    "from shapash import SmartExplainer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a64f2af",
   "metadata": {},
   "source": [
    "## 1. Build a synthetic daily demand signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e63ee176",
   "metadata": {},
   "outputs": [
    {
     "data": {
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         "name": "index",
         "rawType": "int64",
         "type": "integer"
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        {
         "name": "date",
         "rawType": "datetime64[ns]",
         "type": "datetime"
        },
        {
         "name": "target",
         "rawType": "float64",
         "type": "float"
        }
       ],
       "ref": "6f76ec50-f9f7-4dcb-96aa-dcca02d9b160",
       "rows": [
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         "0",
         "2021-01-01 00:00:00",
         "121.21886831901773"
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        [
         "1",
         "2021-01-02 00:00:00",
         "124.03045419914201"
        ],
        [
         "2",
         "2021-01-03 00:00:00",
         "133.495133490113"
        ],
        [
         "3",
         "2021-01-04 00:00:00",
         "129.21691563012655"
        ],
        [
         "4",
         "2021-01-05 00:00:00",
         "109.3443050954835"
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       "shape": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>121.218868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-02</td>\n",
       "      <td>124.030454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-03</td>\n",
       "      <td>133.495133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>129.216916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>109.344305</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date      target\n",
       "0 2021-01-01  121.218868\n",
       "1 2021-01-02  124.030454\n",
       "2 2021-01-03  133.495133\n",
       "3 2021-01-04  129.216916\n",
       "4 2021-01-05  109.344305"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = np.random.default_rng(42)\n",
    "date_index = pd.date_range(start=\"2021-01-01\", periods=900, freq=\"D\")\n",
    "\n",
    "trend = np.linspace(0, 25, len(date_index))\n",
    "weekly = 10 * np.sin(2 * np.pi * np.arange(len(date_index)) / 7)\n",
    "yearly = 20 * np.sin(2 * np.pi * np.arange(len(date_index)) / 365)\n",
    "noise = rng.normal(0, 4, len(date_index))\n",
    "\n",
    "target = 120 + trend + weekly + yearly + noise\n",
    "ts_df = pd.DataFrame({\"date\": date_index, \"target\": target})\n",
    "ts_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4f332b8",
   "metadata": {},
   "source": [
    "## 2. Engineer tabular features (lags + calendar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fdf58370",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
       "columns": [
        {
         "name": "index",
         "rawType": "int64",
         "type": "integer"
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        {
         "name": "lag_1",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "lag_7",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "rolling_mean_7",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "rolling_std_7",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "day_of_week",
         "rawType": "int32",
         "type": "integer"
        },
        {
         "name": "month",
         "rawType": "int32",
         "type": "integer"
        },
        {
         "name": "is_weekend",
         "rawType": "int64",
         "type": "integer"
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       "ref": "036a7eb9-0b42-4326-b8bd-98907cb7e995",
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         "1",
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         "124.03045419914201",
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         "1",
         "1"
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         "133.495133490113",
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         "1"
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         "0",
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         "4",
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         "1",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_7</th>\n",
       "      <th>rolling_mean_7</th>\n",
       "      <th>rolling_std_7</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>month</th>\n",
       "      <th>is_weekend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>114.921933</td>\n",
       "      <td>121.218868</td>\n",
       "      <td>119.875422</td>\n",
       "      <td>9.963461</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>121.333851</td>\n",
       "      <td>124.030454</td>\n",
       "      <td>119.891848</td>\n",
       "      <td>9.966140</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>130.719155</td>\n",
       "      <td>133.495133</td>\n",
       "      <td>120.847377</td>\n",
       "      <td>10.721123</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>129.673558</td>\n",
       "      <td>129.216916</td>\n",
       "      <td>120.301437</td>\n",
       "      <td>10.045764</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>131.560379</td>\n",
       "      <td>109.344305</td>\n",
       "      <td>120.636218</td>\n",
       "      <td>10.424313</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        lag_1       lag_7  rolling_mean_7  rolling_std_7  day_of_week  month  \\\n",
       "0  114.921933  121.218868      119.875422       9.963461            4      1   \n",
       "1  121.333851  124.030454      119.891848       9.966140            5      1   \n",
       "2  130.719155  133.495133      120.847377      10.721123            6      1   \n",
       "3  129.673558  129.216916      120.301437      10.045764            0      1   \n",
       "4  131.560379  109.344305      120.636218      10.424313            1      1   \n",
       "\n",
       "   is_weekend  \n",
       "0           0  \n",
       "1           1  \n",
       "2           1  \n",
       "3           0  \n",
       "4           0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = ts_df.copy()\n",
    "df[\"lag_1\"] = df[\"target\"].shift(1)\n",
    "df[\"lag_7\"] = df[\"target\"].shift(7)\n",
    "df[\"rolling_mean_7\"] = df[\"target\"].shift(1).rolling(7).mean()\n",
    "df[\"rolling_std_7\"] = df[\"target\"].shift(1).rolling(7).std()\n",
    "df[\"day_of_week\"] = df[\"date\"].dt.dayofweek\n",
    "df[\"month\"] = df[\"date\"].dt.month\n",
    "df[\"is_weekend\"] = (df[\"day_of_week\"] >= 5).astype(int)\n",
    "\n",
    "model_df = df.dropna().reset_index(drop=True)\n",
    "feature_cols = [\n",
    "    \"lag_1\",\n",
    "    \"lag_7\",\n",
    "    \"rolling_mean_7\",\n",
    "    \"rolling_std_7\",\n",
    "    \"day_of_week\",\n",
    "    \"month\",\n",
    "    \"is_weekend\",\n",
    "]\n",
    "\n",
    "X = model_df[feature_cols]\n",
    "y = model_df[[\"target\"]]\n",
    "\n",
    "split_idx = int(len(model_df) * 0.8)\n",
    "X_train, X_test = X.iloc[:split_idx], X.iloc[split_idx:]\n",
    "y_train, y_test = y.iloc[:split_idx], y.iloc[split_idx:]\n",
    "date_train = model_df[\"date\"].iloc[:split_idx]\n",
    "date_test = model_df[\"date\"].iloc[split_idx:]\n",
    "\n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8cf26bd",
   "metadata": {},
   "source": [
    "## 3. Train and evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3e5873ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
       "columns": [
        {
         "name": "index",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "MAE",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "R2",
         "rawType": "float64",
         "type": "float"
        }
       ],
       "ref": "75182817-b76d-4aed-a97a-58baad9f0c1e",
       "rows": [
        [
         "train",
         "1.5115687821085546",
         "0.9851178238393178"
        ],
        [
         "test",
         "5.771073777965898",
         "0.5350600701496167"
        ]
       ],
       "shape": {
        "columns": 2,
        "rows": 2
       }
      },
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MAE</th>\n",
       "      <th>R2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>1.511569</td>\n",
       "      <td>0.985118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>test</th>\n",
       "      <td>5.771074</td>\n",
       "      <td>0.535060</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            MAE        R2\n",
       "train  1.511569  0.985118\n",
       "test   5.771074  0.535060"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = RandomForestRegressor(n_estimators=400, random_state=42, n_jobs=-1)\n",
    "model.fit(X_train, y_train.iloc[:, 0])\n",
    "\n",
    "pred_train = model.predict(X_train)\n",
    "pred_test = model.predict(X_test)\n",
    "\n",
    "metrics = pd.DataFrame(\n",
    "    {\n",
    "        \"MAE\": [\n",
    "            mean_absolute_error(y_train.iloc[:, 0], pred_train),\n",
    "            mean_absolute_error(y_test.iloc[:, 0], pred_test),\n",
    "        ],\n",
    "        \"R2\": [\n",
    "            r2_score(y_train.iloc[:, 0], pred_train),\n",
    "            r2_score(y_test.iloc[:, 0], pred_test),\n",
    "        ],\n",
    "    },\n",
    "    index=[\"train\", \"test\"],\n",
    ")\n",
    "metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "99acff10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1218a0110>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_df = pd.DataFrame(\n",
    "    {\n",
    "        \"date\": date_test.values,\n",
    "        \"actual\": y_test.iloc[:, 0].values,\n",
    "        \"predicted\": pred_test,\n",
    "    }\n",
    ")\n",
    "\n",
    "plot_df = compare_df.set_index(\"date\").tail(60)\n",
    "\n",
    "ax = plot_df[\"actual\"].plot(\n",
    "    figsize=(12, 4),\n",
    "    color=\"#FECB2F\",   # jaune style Shapash\n",
    "    linewidth=2.4,\n",
    "    label=\"Actual\",\n",
    ")\n",
    "plot_df[\"predicted\"].plot(\n",
    "    ax=ax,\n",
    "    color=\"#7A7A7A\",   # gris\n",
    "    linewidth=2.2,\n",
    "    linestyle=\"--\",\n",
    "    label=\"Predicted\",\n",
    ")\n",
    "\n",
    "ax.set_title(\"Actual vs Predicted demand\")\n",
    "ax.grid(alpha=0.25)\n",
    "ax.legend(frameon=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71ae5d35",
   "metadata": {},
   "source": [
    "## 4. Explain forecasting drivers with Shapash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ac0a7561",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Shap explainer type - <shap.explainers._tree.TreeExplainer object at 0x121857410>\n"
     ]
    },
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_dict = {\n",
    "    \"lag_1\": \"Demand D-1\",\n",
    "    \"lag_7\": \"Demand D-7\",\n",
    "    \"rolling_mean_7\": \"7-day rolling mean\",\n",
    "    \"rolling_std_7\": \"7-day rolling volatility\",\n",
    "    \"day_of_week\": \"Day of week\",\n",
    "    \"month\": \"Month\",\n",
    "    \"is_weekend\": \"Weekend\",\n",
    "}\n",
    "\n",
    "xpl = SmartExplainer(\n",
    "    model=model,\n",
    "    features_dict=feature_dict,\n",
    "    title_story=\"Demand forecasting with tabular features\",\n",
    ")\n",
    "\n",
    "y_pred_test_df = pd.DataFrame(pred_test, columns=[\"target\"], index=X_test.index)\n",
    "\n",
    "xpl.compile(\n",
    "    x=X_test,\n",
    "    y_pred=y_pred_test_df,\n",
    "    y_target=y_test,\n",
    "    additional_data=model_df.loc[X_test.index, [\"date\"]],\n",
    ")\n",
    "\n",
    "xpl.plot.features_importance()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e714cc26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "worst_error_idx = (y_test.iloc[:, 0] - pred_test).abs().idxmax()\n",
    "xpl.plot.local_plot(index=worst_error_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c2c7673",
   "metadata": {},
   "source": [
    "## 5. Leakage checklist for temporal models\n",
    "\n",
    "- Use a strict time-based split (never random shuffling).\n",
    "- Compute rolling statistics using only past values.\n",
    "- Verify that calendar features are available at inference time.\n",
    "- Monitor drift in lag feature distributions in production."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "survptf_312",
   "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": "3.12.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}