Last_Touch_Attribution_Model.ipynb

{
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   "cell_type": "code",
   "execution_count": 1,
   "id": "7789a247-824b-4eef-977b-51a8548c0b34",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fbcadbbf-7d3a-46bf-a6f9-9516a0181f46",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cookie</th>\n",
       "      <th>time</th>\n",
       "      <th>interaction</th>\n",
       "      <th>conversion</th>\n",
       "      <th>conversion_value</th>\n",
       "      <th>channel</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>00000FkCnDfDDf0iC97iC703B</td>\n",
       "      <td>2018-07-03T13:02:11Z</td>\n",
       "      <td>impression</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Instagram</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00000FkCnDfDDf0iC97iC703B</td>\n",
       "      <td>2018-07-17T19:15:07Z</td>\n",
       "      <td>impression</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Online Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00000FkCnDfDDf0iC97iC703B</td>\n",
       "      <td>2018-07-24T15:51:46Z</td>\n",
       "      <td>impression</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Online Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00000FkCnDfDDf0iC97iC703B</td>\n",
       "      <td>2018-07-29T07:44:51Z</td>\n",
       "      <td>impression</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Online Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0000nACkD9nFkBBDECD3ki00E</td>\n",
       "      <td>2018-07-03T09:44:57Z</td>\n",
       "      <td>impression</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Paid Search</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      cookie                  time interaction  conversion  \\\n",
       "0  00000FkCnDfDDf0iC97iC703B  2018-07-03T13:02:11Z  impression           0   \n",
       "1  00000FkCnDfDDf0iC97iC703B  2018-07-17T19:15:07Z  impression           0   \n",
       "2  00000FkCnDfDDf0iC97iC703B  2018-07-24T15:51:46Z  impression           0   \n",
       "3  00000FkCnDfDDf0iC97iC703B  2018-07-29T07:44:51Z  impression           0   \n",
       "4  0000nACkD9nFkBBDECD3ki00E  2018-07-03T09:44:57Z  impression           0   \n",
       "\n",
       "   conversion_value         channel  \n",
       "0               0.0       Instagram  \n",
       "1               0.0  Online Display  \n",
       "2               0.0  Online Display  \n",
       "3               0.0  Online Display  \n",
       "4               0.0     Paid Search  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"attribution_data.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "232c7157-1d09-45e6-acf7-31df793ab2f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cookie</th>\n",
       "      <th>time</th>\n",
       "      <th>interaction</th>\n",
       "      <th>conversion</th>\n",
       "      <th>conversion_value</th>\n",
       "      <th>channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0007oEBhnoF97AoEE3BCkFnhB</td>\n",
       "      <td>2018-07-06T13:45:29Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>Paid Search</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>00090n9EBBEkA000C7Cik999D</td>\n",
       "      <td>2018-07-05T06:53:53Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Facebook</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>000h3n9nC0hFhE3CCnkkAof7n</td>\n",
       "      <td>2018-07-19T14:31:57Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Facebook</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>000hCBnCB7oi7ADAEnEBCnBEE</td>\n",
       "      <td>2018-07-25T11:15:16Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>6.5</td>\n",
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       "      <th>124</th>\n",
       "      <td>000kiDB3D0fCfDAohCDB3ohko</td>\n",
       "      <td>2018-07-26T16:16:21Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>Facebook</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>586663</th>\n",
       "      <td>oooEAi9EoC7F3A33037h0khk3</td>\n",
       "      <td>2018-07-25T14:42:17Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Online Video</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586690</th>\n",
       "      <td>oooh7FDi0hBnEDBii70hfEf93</td>\n",
       "      <td>2018-07-27T19:25:29Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Online Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586701</th>\n",
       "      <td>oooik3A7A7FA9oof3hDfin7CB</td>\n",
       "      <td>2018-07-12T08:53:23Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>Online Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586707</th>\n",
       "      <td>oookCEDh03D7oo3f0FkB799E7</td>\n",
       "      <td>2018-07-29T21:25:54Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Online Video</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586723</th>\n",
       "      <td>ooonih0kon3FDAB90EfADEFnn</td>\n",
       "      <td>2018-07-13T09:35:35Z</td>\n",
       "      <td>conversion</td>\n",
       "      <td>1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>Instagram</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>17639 rows × 6 columns</p>\n",
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      ],
      "text/plain": [
       "                           cookie                  time interaction  \\\n",
       "22      0007oEBhnoF97AoEE3BCkFnhB  2018-07-06T13:45:29Z  conversion   \n",
       "23      00090n9EBBEkA000C7Cik999D  2018-07-05T06:53:53Z  conversion   \n",
       "83      000h3n9nC0hFhE3CCnkkAof7n  2018-07-19T14:31:57Z  conversion   \n",
       "109     000hCBnCB7oi7ADAEnEBCnBEE  2018-07-25T11:15:16Z  conversion   \n",
       "124     000kiDB3D0fCfDAohCDB3ohko  2018-07-26T16:16:21Z  conversion   \n",
       "...                           ...                   ...         ...   \n",
       "586663  oooEAi9EoC7F3A33037h0khk3  2018-07-25T14:42:17Z  conversion   \n",
       "586690  oooh7FDi0hBnEDBii70hfEf93  2018-07-27T19:25:29Z  conversion   \n",
       "586701  oooik3A7A7FA9oof3hDfin7CB  2018-07-12T08:53:23Z  conversion   \n",
       "586707  oookCEDh03D7oo3f0FkB799E7  2018-07-29T21:25:54Z  conversion   \n",
       "586723  ooonih0kon3FDAB90EfADEFnn  2018-07-13T09:35:35Z  conversion   \n",
       "\n",
       "        conversion  conversion_value         channel  \n",
       "22               1               6.5     Paid Search  \n",
       "23               1               8.0        Facebook  \n",
       "83               1               6.0        Facebook  \n",
       "109              1               6.5    Online Video  \n",
       "124              1               7.5        Facebook  \n",
       "...            ...               ...             ...  \n",
       "586663           1               7.0    Online Video  \n",
       "586690           1               6.0  Online Display  \n",
       "586701           1               7.5  Online Display  \n",
       "586707           1               6.0    Online Video  \n",
       "586723           1               7.5       Instagram  \n",
       "\n",
       "[17639 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered_conversion = df[df['conversion']== 1]\n",
    "df_filtered_conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "feb12782-3666-453c-934d-64f30ce8820f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weight (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>channel</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Facebook</th>\n",
       "      <td>30.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paid Search</th>\n",
       "      <td>25.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Online Video</th>\n",
       "      <td>19.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Instagram</th>\n",
       "      <td>12.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Online Display</th>\n",
       "      <td>12.13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Weight (%)\n",
       "channel                   \n",
       "Facebook             30.05\n",
       "Paid Search          25.78\n",
       "Online Video         19.32\n",
       "Instagram            12.72\n",
       "Online Display       12.13"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_touch = pd.DataFrame(round(df_filtered_conversion[\"channel\"].value_counts(normalize=True) * 100, 2))\n",
    "last_touch.columns = [\"Weight (%)\"]\n",
    "last_touch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dfda3c5a-274f-4a9f-bc76-744f88dc8d90",
   "metadata": {},
   "outputs": [
    {
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gSp2fKjUkeXl5qXr16rbpK1assJ2Ge6tRElNrSUpK0pYtWxzehtRQ7Orqmunv9qmnnnJ4WPKOHTtm2NbRfeRWUo+rv//+u92gNwDuDiEJwG1Zs2aN2rdvr6CgIAUHB6tMmTKKjIy0Pb744gtJSjcEdenSRZK0f/9+lSpVSt26ddOMGTN07NixHN2G27Vr1y7bz6nf7Gckdf7ly5fv6oNPepKSkmy13O39Y8qVK5fp/NTePGvgcZSfn5/t59v5Jt8Rd1t3UlKSJkyYoFq1ailv3rwKCwtThQoV7Pbh06dPS0p/H3a0FmtvaGbvYenSpTP9dj+j7UlOTraFkc8//zzd0c+sj++++07S//U6ZLXU63Yk+96gm69Hurn9li1bdOXKFUnStWvXbB/ya9asaddbuHnzZtvPoaGhmW6rtXf1drY39W8rIiIiw/upSTd+JxEREQ6tMyv2kVvp0KGD3N3dlZiYqDp16qhFixb67LPPtGvXLkazA+4CIQmAw4YPH666detq9uzZ6Q5da5X6wceqW7duev3115UnTx7Fx8drypQp6tixo8LCwlSqVCkNHDgwy4NFVrBu661OHwsJCUl3uayqI/VDT2anjTnCx8cn0/mpH9zvpDcstSdGku30paxyN3X//fffioqKUr9+/bRhwwZdu3Yt03Wltw87Wos1+GT2Hjq6PSkpKXbT//77b12/fj3TZdOT2bDkd6NevXq20O5ISHrooYfk4+OjpKQk23DzmzZt0tWrVyWlHfo7NbjertvZ3tShwx0ZlMHRgRuyYh+5lXLlymnGjBnKnz+/rl+/rp9++km9e/dWZGSkgoOD9fTTT9/RabPA/Y7R7QA4ZPny5bbRviIiIjRo0CDVrVtXxYoVk6+vr+16iDfffFNvvfVWhuv5z3/+o2effVbffvutli9frvXr1+vy5cs6cOCAxo0bp48//ljjx49Xr169cmS7btfd9N7cLyIjI+Xq6qqUlBRt3brV2eXY9O/f33b6VcuWLdWtWzdVrFhRwcHB8vLysv1uixUrpqNHj+bqb+GtH6p79Oih/v37O7RcetdyZYXAwEA98MAD2rVrl+0DeUJCgu2UxZtDkru7u2rUqKHY2FitXLlSDRs2zPT+SNbt3bp1q9zd3R2qq2jRone0Pf80bdq0UePGjTVr1iwtWbJEq1at0pkzZ/S///1P06ZN07Rp09SlSxdNnjyZ65IABxGSADgk9TS6/Pnza/369Rl+k+pI70l4eLhef/11vf7660pKStKmTZs0e/Zsff7557p69ar69OmjmjVr2q6LcTbraTGnTp3KdEAE6+k9Nw9AkVGvwM0yOkUtMDDQFj5OnDhxy7qdxd/fX5UrV9bWrVsVFxdnO73SmRISEjRr1ixJN64lmjZtWoZtM7sZaW5h3beMMZkO4JFTHn74Ye3atUtnzpzR3r17dejQIaWkpNgN7GBVt25dxcbG2sJR6vVJ7u7utmuoUll7JwsWLJgt4Sd1KPIzZ87csq0jbXJaQECAnn32WT377LOSpD179ujHH3/Uxx9/rOPHj+urr75SlSpVHA7UwP2OrxMAOGT37t2SpIYNG2Z6qon12gFHuLu7q3bt2vrwww81ffp0STc+9KVeQ5HKmT041g+gGzZsyLRt6jUVPj4+aa5bSL1W51YfwlNHA7uZu7u7rZZVq1bl6p6OZ555RtKN3+X48eOdXI20b98+JSUlSZLat2+fYbu9e/fq4sWLOVXWHfPw8LDdN2nNmjVOruaGm69LSg0/tWrVsrvfUarU3qX169crMTFRa9eulXTjVLybB/ywhqzs2t7U9/PgwYOZ/o3+/fffOXJa8N0e88qXL6/XXntN69evt72fs2fPzorSgPsCIQmAQ1Kvf8jsQvxt27bdMkRk5pFHHrH9fPNF89Yb0yYmJt7xa9yJBg0a2D7kTZ48OcN2R44c0S+//JJmmVSpN7zdunVrhgFn9+7d2rFjR4av0aJFC0nSoUOHcvXNIbt162a7PmvChAlasWKFw8t+8803WV6P9fqdzPbhzz77LMtfO7ukjm64d+9eLVmyxMnV2J8it3LlSlvP0M2n2qWKioqyDbc+depU2+h1N59qJ924vUDq9T3jx4/Pli8IUo8/KSkpti9s0jNt2rQc+YIiq455YWFhKlOmjKRbD0YC4P8QkgA4JHX43tWrV2v//v1p5p85c0ZPP/10puuYNm1aphebL1261PZzaqBIZR2o4MCBAw7VnFUKFy6sVq1aSZIWLVqkr776Kk2ba9euqVu3brbeitT75FjVr19f0o37Ls2YMSPN/AsXLmQ6xHjqelO/FX7uuefsRt67mTNHDfTx8dG0adNspwf+61//0ty5czNd5siRI+rQoYOef/75LK+nVKlStm/mv/rqq3Q/5C5YsCDb7m+VHfr376+8efNKutFzl9rbm5GFCxdmGsDvVuHChVWyZElJUkxMjK1X2drDZOXv76/IyEhJ0rvvvmubnl5Iypcvn+1vau3atXrppZcyPW311KlT+vLLL2+r/latWtkGZhk+fHi6x5l9+/bZrs3Mbo4e83744QedP38+w/lHjx7V3r17JaU9rgLIGNckAfep7du3a+rUqbds16hRIxUrVkydO3fWggULdOnSJdWvX1+vvfaa7T4fa9eu1bhx43Ty5ElFRUVleC+Wp59+WoMGDVLr1q1Vu3ZtlSxZUl5eXjp16pR++eUXTZw4UdKNm1PefJ+SKlWqyMvLS1evXtXQoUPl7u6u8PBw23U+RYoUkbe39128I5n74IMPtHz5cp07d07dunXT6tWr1b59e+XPn1979+7Ve++9ZxuSuV27dmratGmadTz11FMaPny4EhIS1L17d+3fv1/R0dFycXHRli1bNG7cOB07dkxVqlTRtm3b0q0jJCREEydOVOfOnXX69GnVqFFDPXv2VNOmTRUSEqKLFy9q165dmj9/vuLi4nI8UFo98sgj+vLLL/Xcc8/p0qVLatu2rWrVqqW2bduqcuXKCgwMVHx8vA4ePKjFixdr/vz5SkxMVEBAQJbXEhQUpGbNmmnhwoVavHixHnvsMfXu3Vvh4eE6ffq05s6dq6lTpyoiIkLnz5/Pldec3KxQoUL66quv1LZtW504cULVqlVT165d1bRpUxUtWtR2H6iNGzfqu+++08GDB7VgwYIM74+VFerVq6cDBw7or7/+knTjHk21atXKsH3dunW1fft22+lrrq6uGfY8jRw5UitWrNCGDRv00UcfKTY2Vj179lTlypXl6+urc+fOaffu3Vq2bJkWLVqkyMhI9ejRw+Havby89OGHH6pjx4763//+p5o1a+rVV1+1hbyVK1fqnXfeUUpKikqXLq19+/Zl62nAtWvXtv380ksvaciQIbbhz6Ub92XLkyePPvzwQ3Xq1En/+te/1KhRI5UvX14BAQE6d+6cNm/erI8//tg2UmNuHRAHyJUMgPtGTEyMkXRbj3nz5tmWf+aZZzJs5+bmZj788EMzbNgw27SbOfJ6AQEBZtGiRenW/8orr2S4XExMTJa9N8OGDUu3zdatW03hwoUzrb9169bmypUrGb7O7NmzjZubW7rLent7mzlz5pguXboYSSY8PDzD9UydOtV4e3tnWkt6y4eHhxtJpkuXLpm+H47U4KjY2Fjz4IMPOvT7L1asmJk+fXqaddzqd5Oqfv36RpKpX79+mnlHjhwxxYoVy/S1d+/enel7NGXKFFv7Q4cOZVjHoUOHbO2mTJlyW3VaZfb3lGr+/PkmMDDwlu+tq6ur+fXXX9Ms7+h764jJkyfbvWb16tUzbT9z5ky79pUqVcq0fUJCgmndurVD+1LDhg3TLO/I+zlq1Cjj4uKS7jp9fHzMwoULTb169Ywk06RJkzTLW48ltzou3eq9b9euXYbbl7r/pe5Lt/rdv/XWW5nWAsAep9sBcNjkyZP1zTffqF69evLz85Onp6fCw8P19NNPa+3atbccNWnXrl1655131KJFC1WoUEFBQUFyc3NTvnz5VKtWLQ0bNkxxcXFq0qRJusuPGTNGX3zxherVq6fAwMB0LwbPTlWqVFFcXJxGjx6tmjVrKl++fPLw8FDhwoXVunVrzZ8/X3PnzrW7luBmTzzxhNauXatWrVqpYMGC8vDwUFhYmLp06aJNmzapbdu2DtXSpUsXHThwQEOGDFHVqlWVL18+ubm5KX/+/KpVq5Zef/11LV68OKs2/a7Ur19fv/32m3788Uf17NlTDzzwgAoUKKA8efIoX758evDBB9WtWzf9+OOPOnDggDp06JAtdYSFhWnr1q16+eWXVaZMGXl6eiogIECVKlXSsGHDtH37dlWoUCFbXjs7tWjRQocOHdJ7772nRo0aqVChQnJ3d5e3t7dKlCih5s2ba9y4cTp8+LAaNmyYrbXcfKpcRr1CqW4+FS+9U+2s/Pz8NHfuXK1atUo9evRQ2bJl5efnpzx58igwMFDVq1dX37599fPPP9uuD7xdQ4YM0YoVK9SyZUsFBwfbjnPdunXT5s2b1axZMyUkJEhStvR6Wk2bNk3vvvuuatSooYCAgHSH754xY4YmTZqkjh07qnLlygoJCVGePHmUN29ePfDAA+rdu7e2bdumN954I1trBe41Lsbk4uGRAAAAcpGkpCQFBAToypUreuONNzK9LxyAfy56kgAAABz0ww8/2K7xyex6KwD/bPQkAQAA/H+Z3fz48OHDqlevno4dO6ZChQrp2LFjypOHMbCAexF/2QAAAP9fuXLl1KxZMzVv3lwPPPCAfH19dfr0acXExOizzz6zDbf93nvvEZCAexg9SQAAAP/frYb1dnV11ahRozR48OAcqgiAM/AVCAAAwP+3YMECLVq0SGvXrtWpU6d09uxZeXp6qkiRImrQoIH69u2rBx980NllAshm9CQBAAAAgMU935OUkpKi48ePy8/PL1vvjA0AAAAgdzPG6MKFCypcuHC69x5Ldc+HpOPHjyssLMzZZQAAAADIJY4ePaqiRYtmOP+eD0l+fn6SbrwR/v7+Tq4GAAAAgLMkJCQoLCzMlhEycs+HpNRT7Pz9/QlJAAAAAG49kmUO1QEAAAAA/wiEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwMKpIWnixImqWLGi/P395e/vr6ioKC1atMg2/+rVq+rbt6+CgoKUN29etWnTRqdOnXJixQAAAADudU4NSUWLFtWYMWO0ZcsWbd68WY0aNdLjjz+u3bt3S5JeeuklLViwQHPmzNGKFSt0/PhxtW7d2pklAwAAALjHuRhjjLOLsAoMDNTYsWPVtm1bFSxYUNOnT1fbtm0lSXv37lX58uW1bt061apVK93lExMTlZiYaHuekJCgsLAwxcfHy9/fP0e2AQAAAEDuk5CQoICAgFtmgzw5WFOmkpOTNWfOHF26dElRUVHasmWLkpKS1LhxY1ubcuXKqVixYpmGpNGjR2vEiBFZVlfVl7/OsnUh99sytrOzSwAAAICTOX3ghp07dypv3rzy9PRUr169NG/ePFWoUEEnT56Uh4eH8uXLZ9e+UKFCOnnyZIbrGzx4sOLj422Po0ePZvMWAAAAALiXOL0nqWzZstq+fbvi4+P13XffqUuXLlqxYsUdr8/T01Oenp5ZWCEAAACA+4nTQ5KHh4dKlSolSapatao2bdqkjz76SO3bt9e1a9d0/vx5u96kU6dOKSQkxEnVAgAAALjXOf10u5ulpKQoMTFRVatWlbu7u5YvX26bFxcXpyNHjigqKsqJFQIAAAC4lzm1J2nw4MFq2rSpihUrpgsXLmj69OmKjY3VkiVLFBAQoO7du2vAgAEKDAyUv7+/nn/+eUVFRWU4aAMAAAAA3C2nhqTTp0+rc+fOOnHihAICAlSxYkUtWbJEjz76qCTpgw8+kKurq9q0aaPExERFR0fr008/dWbJAAAAAO5xue4+SVnN0bHQM8IQ4PcXhgAHAAC4dzmaDXLdNUkAAAAA4EyEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAACLPM4uAMANVV/+2tklIAdtGdvZ2SUAAIAM0JMEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWDg1JI0ePVrVq1eXn5+fgoOD1bJlS8XFxdm1adCggVxcXOwevXr1clLFAAAAAO51Tg1JK1asUN++fbV+/Xr98ssvSkpK0mOPPaZLly7ZtevZs6dOnDhhe7z77rtOqhgAAADAvS6PM1988eLFds+nTp2q4OBgbdmyRQ8//LBtuo+Pj0JCQnK6PAAAAAD3oVx1TVJ8fLwkKTAw0G76t99+qwIFCujBBx/U4MGDdfny5QzXkZiYqISEBLsHAAAAADjKqT1JVikpKXrxxRdVp04dPfjgg7bpHTt2VHh4uAoXLqwdO3bo1VdfVVxcnL7//vt01zN69GiNGDEip8oGAAAAcI/JNSGpb9++2rVrl1avXm03/dlnn7X9HBkZqdDQUD3yyCM6cOCASpYsmWY9gwcP1oABA2zPExISFBYWln2FAwAAALin5IqQ1K9fP/30009auXKlihYtmmnbmjVrSpL279+fbkjy9PSUp6dnttQJAAAA4N7n1JBkjNHzzz+vefPmKTY2ViVKlLjlMtu3b5ckhYaGZnN1AAAAAO5HTg1Jffv21fTp0/Xjjz/Kz89PJ0+elCQFBATI29tbBw4c0PTp09WsWTMFBQVpx44deumll/Twww+rYsWKziwdAAAAwD3KqSFp4sSJkm7cMNZqypQp6tq1qzw8PLRs2TJ9+OGHunTpksLCwtSmTRu98cYbTqgWAAAAwP3A6afbZSYsLEwrVqzIoWoAAAAAIJfdJwkAAAAAnI2QBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYOHUkDR69GhVr15dfn5+Cg4OVsuWLRUXF2fX5urVq+rbt6+CgoKUN29etWnTRqdOnXJSxQAAAADudU4NSStWrFDfvn21fv16/fLLL0pKStJjjz2mS5cu2dq89NJLWrBggebMmaMVK1bo+PHjat26tROrBgAAAHAvy+PMF1+8eLHd86lTpyo4OFhbtmzRww8/rPj4eP33v//V9OnT1ahRI0nSlClTVL58ea1fv161atVyRtkAAAAA7mG56pqk+Ph4SVJgYKAkacuWLUpKSlLjxo1tbcqVK6dixYpp3bp16a4jMTFRCQkJdg8AAAAAcFSuCUkpKSl68cUXVadOHT344IOSpJMnT8rDw0P58uWza1uoUCGdPHky3fWMHj1aAQEBtkdYWFh2lw4AAADgHpJrQlLfvn21a9cuzZw5867WM3jwYMXHx9seR48ezaIKAQAAANwPnHpNUqp+/frpp59+0sqVK1W0aFHb9JCQEF27dk3nz5+36006deqUQkJC0l2Xp6enPD09s7tkAAAAAPcop/YkGWPUr18/zZs3T7/++qtKlChhN79q1apyd3fX8uXLbdPi4uJ05MgRRUVF5XS5AAAAAO4DTu1J6tu3r6ZPn64ff/xRfn5+tuuMAgIC5O3trYCAAHXv3l0DBgxQYGCg/P399fzzzysqKoqR7QAAAABkC6eGpIkTJ0qSGjRoYDd9ypQp6tq1qyTpgw8+kKurq9q0aaPExERFR0fr008/zeFKAQAAANwvnBqSjDG3bOPl5aUJEyZowoQJOVARAAAAgPtdrhndDgAAAAByA0ISAAAAAFgQkgAAAADAIlfcJwkAkHOqvvy1s0tADtoytrOzSwCAfxx6kgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAIs8t9M4JSVFK1as0KpVq/Tnn3/q8uXLKliwoKpUqaLGjRsrLCwsu+oEAAAAgBzhUE/SlStXNGrUKIWFhalZs2ZatGiRzp8/Lzc3N+3fv1/Dhg1TiRIl1KxZM61fvz67awYAAACAbONQT1KZMmUUFRWlL774Qo8++qjc3d3TtPnzzz81ffp0PfnkkxoyZIh69uyZ5cUCAAAAQHZzKCQtXbpU5cuXz7RNeHi4Bg8erEGDBunIkSNZUhwAAAAA5DSHTre7VUCycnd3V8mSJe+4IAAAAABwptsauMHq+vXr+vzzzxUbG6vk5GTVqVNHffv2lZeXV1bWBwAAAAA56o5D0gsvvKA//vhDrVu3VlJSkr7++mtt3rxZM2bMyMr6AAAAACBHORyS5s2bp1atWtmeL126VHFxcXJzc5MkRUdHq1atWllfIQAAAADkIIdvJjt58mS1bNlSx48flyQ99NBD6tWrlxYvXqwFCxbolVdeUfXq1bOtUAAAAADICQ6HpAULFqhDhw5q0KCBPv74Y02aNEn+/v4aMmSIhg4dqrCwME2fPj07awUAAACAbHdb1yS1b99e0dHReuWVVxQdHa3PPvtM77//fnbVBgAAAAA5zuGepFT58uXTpEmTNHbsWHXu3Fkvv/yyrl69mh21AQAAAECOczgkHTlyRO3atVNkZKQ6deqk0qVLa8uWLfLx8VGlSpW0aNGi7KwTAAAAAHKEwyGpc+fOcnV11dixYxUcHKznnntOHh4eGjFihH744QeNHj1a7dq1y85aAQAAACDbOXxN0ubNm/Xbb7+pZMmSio6OVokSJWzzypcvr5UrV2rSpEnZUiQAAAAA5BSHQ1LVqlX15ptvqkuXLlq2bJkiIyPTtHn22WeztDgAAAAAyGkOn2739ddfKzExUS+99JL++usvff7559lZFwAAAAA4hcM9SeHh4fruu++ysxYAAAAAcDqHepIuXbp0Wyu93fYAAAAAkFs4FJJKlSqlMWPG6MSJExm2Mcbol19+UdOmTTV+/PgsKxAAAAAAcpJDp9vFxsbq9ddf1/Dhw1WpUiVVq1ZNhQsXlpeXl86dO6fff/9d69atU548eTR48GA999xz2V03AAAAAGQLh0JS2bJlNXfuXB05ckRz5szRqlWrtHbtWl25ckUFChRQlSpV9MUXX6hp06Zyc3PL7poBAAAAINs4PHCDJBUrVkwDBw7UwIEDs6seAAAAAHAqh4cABwAAAID7ASEJAAAAACwISQAAAABgQUgCAAAAAIvbDklHjhyRMSbNdGOMjhw5kiVFAQAAAICz3HZIKlGihM6cOZNm+t9//60SJUpkSVEAAAAA4Cy3HZKMMXJxcUkz/eLFi/Ly8sqSogAAAADAWRy+T9KAAQMkSS4uLho6dKh8fHxs85KTk7VhwwZVrlw5ywsEAAAAgJzkcEjatm2bpBs9STt37pSHh4dtnoeHhypVqqRBgwZlfYUAAAAAkIMcDkkxMTGSpGeeeUYfffSR/P39s60oAAAAAHAWh0NSqilTpmRHHQAAAACQK9x2SLp06ZLGjBmj5cuX6/Tp00pJSbGbf/DgwSwrDgAAAABy2m2HpB49emjFihV6+umnFRoamu5IdwAAAADwT3XbIWnRokVauHCh6tSpkx31AAAAAIBT3fZ9kvLnz6/AwMDsqAUAAAAAnO62Q9Jbb72lN998U5cvX86OegAAAADAqRw63a5KlSp21x7t379fhQoVUvHixeXu7m7XduvWrVlbIQAAAADkIIdCUsuWLbO5DAAAAADIHRwKScOGDcvuOgAAAAAgV7jta5IAAAAA4F52x6Pb3fwICgpSkSJFVL9+fU2ZMsWhda1cuVItWrRQ4cKF5eLioh9++MFufteuXeXi4mL3aNKkye2WDAAAAAAOu+37JL355pv6z3/+o6ZNm6pGjRqSpI0bN2rx4sXq27evDh06pN69e+v69evq2bNnpuu6dOmSKlWqpG7duql169bptmnSpIld6PL09LzdkgEAAADAYbcdklavXq1Ro0apV69edtM///xzLV26VHPnzlXFihU1fvz4W4akpk2bqmnTppm28fT0VEhIyO2WCQAAAAB35LZPt1uyZIkaN26cZvojjzyiJUuWSJKaNWumgwcP3n11kmJjYxUcHKyyZcuqd+/eOnv2bKbtExMTlZCQYPcAAAAAAEfddkgKDAzUggUL0kxfsGCBAgMDJd04jc7Pz++ui2vSpIm+/vprLV++XO+8845WrFihpk2bKjk5OcNlRo8erYCAANsjLCzsrusAAAAAcP+47dPthg4dqt69eysmJsZ2TdKmTZv0888/67PPPpMk/fLLL6pfv/5dF/fkk0/afo6MjFTFihVVsmRJxcbG6pFHHkl3mcGDB2vAgAG25wkJCQQlAAAAAA677ZDUs2dPVahQQZ988om+//57SVLZsmW1YsUK1a5dW5I0cODArK3y/4uIiFCBAgW0f//+DEOSp6cngzsAAAAAuGO3HZIkqU6dOqpTp05W13JLx44d09mzZxUaGprjrw0AAADg/uBQSEpISJC/v7/t58yktnPExYsXtX//ftvzQ4cOafv27bZ7L40YMUJt2rRRSEiIDhw4oFdeeUWlSpVSdHS0w68BAAAAALfDoZCUP39+nThxQsHBwcqXL59cXFzStDHGyMXFJdNBFW62efNmNWzY0PY89VqiLl26aOLEidqxY4e++uornT9/XoULF9Zjjz2mt956i9PpAAAAAGQbh0LSr7/+ahu5LiYmJstevEGDBjLGZDg/dUhxAAAAAMgpDoUk60h1WTFqHQAAAADkVrd9nyRJWrVqlZ566inVrl1bf/31lyTpm2++0erVq7O0OAAAAADIabcdkubOnavo6Gh5e3tr69atSkxMlCTFx8fr7bffzvICAQAAACAn3XZIGjVqlD777DN98cUXcnd3t02vU6eOtm7dmqXFAQAAAEBOu+2QFBcXp4cffjjN9ICAAJ0/fz4ragIAAAAAp7ntkBQSEmJ3b6NUq1evVkRERJYUBQAAAADOctshqWfPnurfv782bNggFxcXHT9+XN9++60GDRqk3r17Z0eNAAAAAJBjHBoC3Oq1115TSkqKHnnkEV2+fFkPP/ywPD09NWjQID3//PPZUSMAAAAA5BiHQ9KhQ4dUokQJubi4aMiQIXr55Ze1f/9+Xbx4URUqVFDevHmzs04AAAAAyBEOh6SSJUsqPDxcDRs2VKNGjdSwYUNVqFAhO2sDAAAAgBzncEj69ddfFRsbq9jYWM2YMUPXrl1TRESELTA1bNhQhQoVys5aAQAAACDbORySGjRooAYNGkiSrl69qrVr19pC01dffaWkpCSVK1dOu3fvzq5aAQAAACDb3fbADZLk5eWlRo0aqW7dumrYsKEWLVqkzz//XHv37s3q+gAAAAAgR91WSLp27ZrWr1+vmJgYxcbGasOGDQoLC9PDDz+sTz75RPXr18+uOgEAAAAgRzgckho1aqQNGzaoRIkSql+/vp577jlNnz5doaGh2VkfAAAAAOQoh0PSqlWrFBoaqkaNGqlBgwaqX7++goKCsrM2AAAAAMhxro42PH/+vCZNmiQfHx+98847Kly4sCIjI9WvXz999913OnPmTHbWCQAAAAA5wuGeJF9fXzVp0kRNmjSRJF24cEGrV69WTEyM3n33XXXq1EmlS5fWrl27sq1YAAAAAMhuDvck3czX11eBgYEKDAxU/vz5lSdPHu3ZsycrawMAAACAHOdwT1JKSoo2b96s2NhYxcTEaM2aNbp06ZKKFCmihg0basKECWrYsGF21goAAAAA2c7hkJQvXz5dunRJISEhatiwoT744AM1aNBAJUuWzM76AAAAACBHORySxo4dq4YNG6pMmTLZWQ8AAAAAOJXDIem5557LzjoAAAAAIFe444EbAAAAAOBeREgCAAAAAAtCEgAAAABYOHxNEgAAwO2o+vLXzi4BOWjL2M7OLgHIMvQkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACw4GayAAAA+EfjxsX3l5y4cTE9SQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAunhqSVK1eqRYsWKly4sFxcXPTDDz/YzTfG6M0331RoaKi8vb3VuHFj7du3zznFAgAAALgvODUkXbp0SZUqVdKECRPSnf/uu+9q/Pjx+uyzz7Rhwwb5+voqOjpaV69ezeFKAQAAANwv8jjzxZs2baqmTZumO88Yow8//FBvvPGGHn/8cUnS119/rUKFCumHH37Qk08+mZOlAgAAALhP5Nprkg4dOqSTJ0+qcePGtmkBAQGqWbOm1q1bl+FyiYmJSkhIsHsAAAAAgKNybUg6efKkJKlQoUJ20wsVKmSbl57Ro0crICDA9ggLC8vWOgEAAADcW3JtSLpTgwcPVnx8vO1x9OhRZ5cEAAAA4B8k14akkJAQSdKpU6fspp86dco2Lz2enp7y9/e3ewAAAACAo3JtSCpRooRCQkK0fPly27SEhARt2LBBUVFRTqwMAAAAwL3MqaPbXbx4Ufv377c9P3TokLZv367AwEAVK1ZML774okaNGqXSpUurRIkSGjp0qAoXLqyWLVs6r2gAAAAA9zSnhqTNmzerYcOGtucDBgyQJHXp0kVTp07VK6+8okuXLunZZ5/V+fPnVbduXS1evFheXl7OKhkAAADAPc6pIalBgwYyxmQ438XFRSNHjtTIkSNzsCoAAAAA97Nce00SAAAAADgDIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFrk6JA0fPlwuLi52j3Llyjm7LAAAAAD3sDzOLuBWHnjgAS1btsz2PE+eXF8yAAAAgH+wXJ848uTJo5CQEGeXAQAAAOA+katPt5Okffv2qXDhwoqIiFCnTp105MiRTNsnJiYqISHB7gEAAAAAjsrVIalmzZqaOnWqFi9erIkTJ+rQoUOqV6+eLly4kOEyo0ePVkBAgO0RFhaWgxUDAAAA+KfL1SGpadOmeuKJJ1SxYkVFR0fr559/1vnz5zV79uwMlxk8eLDi4+Ntj6NHj+ZgxQAAAAD+6XL9NUlW+fLlU5kyZbR///4M23h6esrT0zMHqwIAAABwL8nVPUk3u3jxog4cOKDQ0FBnlwIAAADgHpWrQ9KgQYO0YsUKHT58WGvXrlWrVq3k5uamDh06OLs0AAAAAPeoXH263bFjx9ShQwedPXtWBQsWVN26dbV+/XoVLFjQ2aUBAAAAuEfl6pA0c+ZMZ5cAAAAA4D6Tq0+3AwAAAICcRkgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACwICQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAAAAAwIKQBAAAAAAWhCQAAAAAsCAkAQAAAIAFIQkAAAAALAhJAAAAAGBBSAIAAAAAC0ISAAAAAFgQkgAAAADAgpAEAAAAABaEJAAAAACw+EeEpAkTJqh48eLy8vJSzZo1tXHjRmeXBAAAAOAeletD0qxZszRgwAANGzZMW7duVaVKlRQdHa3Tp087uzQAAAAA96BcH5LGjRunnj176plnnlGFChX02WefycfHR5MnT3Z2aQAAAADuQXmcXUBmrl27pi1btmjw4MG2aa6urmrcuLHWrVuX7jKJiYlKTEy0PY+Pj5ckJSQk3FENyYlX7mg5/DPd6X6SFdjX7i/sa8gp7GvIKexryCl3s6+lLmuMybSdi7lVCyc6fvy4ihQporVr1yoqKso2/ZVXXtGKFSu0YcOGNMsMHz5cI0aMyMkyAQAAAPyDHD16VEWLFs1wfq7uSboTgwcP1oABA2zPU1JS9PfffysoKEguLi5OrOyfIyEhQWFhYTp69Kj8/f2dXQ7uYexryCnsa8gp7GvIKexrd8YYowsXLqhw4cKZtsvVIalAgQJyc3PTqVOn7KafOnVKISEh6S7j6ekpT09Pu2n58uXLrhLvaf7+/vzRIUewryGnsK8hp7CvIaewr92+gICAW7bJ1QM3eHh4qGrVqlq+fLltWkpKipYvX253+h0AAAAAZJVc3ZMkSQMGDFCXLl1UrVo11ahRQx9++KEuXbqkZ555xtmlAQAAALgH5fqQ1L59e505c0ZvvvmmTp48qcqVK2vx4sUqVKiQs0u7Z3l6emrYsGFpTlsEshr7GnIK+xpyCvsacgr7WvbK1aPbAQAAAEBOy9XXJAEAAABATiMkAQAAAIAFIQkAAAAALAhJSCM2NlYuLi46f/58tr7O1KlTuYfVP4Qjv6vhw4ercuXKOVJPVsupfR6ZO3z4sFxcXLR9+3ZJuev34sj+3bVrV7Vs2TJH6gGQu+Tm41cqFxcX/fDDD1myrpu3915ESMrFunbtKhcXlzSP/fv3O7s0/MNY9yUPDw+VKlVKI0eO1PXr1x1avn379vrjjz/uuo558+apVq1aCggIkJ+fnx544AG9+OKLd71eONfRo0fVrVs3FS5cWB4eHgoPD1f//v119uzZu1pv7dq1deLECYdu+nenWrRooSZNmqQ7b9WqVXJxcdGOHTs0aNAgu3v2IXfKyqBavHhxffjhh1myLuRe/+Tjl2T//7u7u7sKFSqkRx99VJMnT1ZKSopd2xMnTqhp06bZWs+9hJCUyzVp0kQnTpywe5QoUcLZZeEfKHVf2rdvnwYOHKjhw4dr7NixDi3r7e2t4ODgu3r95cuXq3379mrTpo02btyoLVu26D//+Y+SkpLuar23kpycnOY/CmSdgwcPqlq1atq3b59mzJih/fv367PPPrPd9Pvvv/++43V7eHgoJCRELi4uWVixve7du+uXX37RsWPH0sybMmWKqlWrpooVKypv3rwKCgrKtjpwf7t27ZqzS7gv/dOPX6lS/38/fPiwFi1apIYNG6p///5q3ry53ZehISEhDBd+GwhJuZynp6dCQkLsHh999JEiIyPl6+ursLAw9enTRxcvXrRbbs2aNWrQoIF8fHyUP39+RUdH69y5c5KklJQUjR49WiVKlJC3t7cqVaqk7777Ls1rr1mzRhUrVpSXl5dq1aqlXbt22c2fO3euHnjgAXl6eqp48eJ6//337eafO3dOnTt3Vv78+eXj46OmTZtq3759GW7rmTNnVK1aNbVq1UqJiYl3+pYhA6n7Unh4uHr37q3GjRtr/vz5kqRx48Zluk+ld7rdmDFjVKhQIfn5+al79+66evVqpq+/YMEC1alTRy+//LLKli2rMmXKqGXLlpowYYJdux9//FEPPfSQvLy8FBERoREjRtgd5B2tdf78+apQoYI8PT115MgRJSYm6tVXX1VYWJg8PT1VqlQp/fe//7V77S1btqhatWry8fFR7dq1FRcXd1vv8f2ob9++8vDw0NKlS1W/fn0VK1ZMTZs21bJly/TXX39pyJAhtrbFixfX22+/rW7dusnPz0/FihXTpEmTMlz3zaerpP5ulyxZovLlyytv3ry2DwdWX375pcqXLy8vLy+VK1dOn376aYav0bx5cxUsWFBTp061m37x4kXNmTNH3bt3l5T2dLvk5GQNGDBA+fLlU1BQkF555RXdfEcNR461K1asUI0aNeTp6anQ0FC99tprDvfwInMNGjTQCy+8oFdeeUWBgYEKCQnR8OHDbfONMRo+fLiKFSsmT09PFS5cWC+88IJt2T///FMvvfSS7Vt6STp79qw6dOigIkWKyMfHR5GRkZoxY4bd6164cEGdOnWSr6+vQkND9cEHH6hBgwZ2vebFixfXW2+9pc6dO8vf31/PPvusJOnVV19VmTJl5OPjo4iICA0dOtTui6TU/XDy5MkqVqyY8ubNqz59+ig5OVnvvvuuQkJCFBwcrP/85z/Z9K7eW/7px69Uqf+/FylSRA899JBef/11/fjjj1q0aJHdsc16ut21a9fUr18/hYaGysvLS+Hh4Ro9erRd24kTJ6pp06by9vZWREREup8VUyUnJ6t79+62413ZsmX10Ucf2eavXLlS7u7uOnnypN1yL774ourVq3fLbXQKg1yrS5cu5vHHH08z/YMPPjC//vqrOXTokFm+fLkpW7as6d27t23+tm3bjKenp+ndu7fZvn272bVrl/n444/NmTNnjDHGjBo1ypQrV84sXrzYHDhwwEyZMsV4enqa2NhYY4wxMTExRpIpX768Wbp0qdmxY4dp3ry5KV68uLl27ZoxxpjNmzcbV1dXM3LkSBMXF2emTJlivL29zZQpU2x1/Pvf/zbly5c3K1euNNu3bzfR0dGmVKlStnVMmTLFBAQEGGOMOXLkiClbtqzp0qWLuX79eja8m/e39Palf//73+ahhx4yxtx6n7L+rowxZtasWcbT09N8+eWXZu/evWbIkCHGz8/PVKpUKcMaRo8ebQoWLGh27tyZYZuVK1caf39/M3XqVHPgwAGzdOlSU7x4cTN8+HBbG0dqdXd3N7Vr1zZr1qwxe/fuNZcuXTLt2rUzYWFh5vvvvzcHDhwwy5YtMzNnzjTG/N8+X7NmTRMbG2t2795t6tWrZ2rXru3I23vfOnv2rHFxcTFvv/12uvN79uxp8ufPb1JSUowxxoSHh5vAwEAzYcIEs2/fPjN69Gjj6upq9u7da4wx5tChQ0aS2bZtmzHm/34v586dM8b83++2cePGZtOmTWbLli2mfPnypmPHjrbXnDZtmgkNDTVz5841Bw8eNHPnzjWBgYFm6tSpGW7Hyy+/bEqWLGmr0xhjJk+ebLy9vc358+eNMcYMGzbMbv9+5513TP78+c3cuXPN77//brp37278/Pzs/s5udaw9duyY8fHxMX369DF79uwx8+bNMwUKFDDDhg1z6P1HWtZjXf369Y2/v78ZPny4+eOPP8xXX31lXFxczNKlS40xxsyZM8f4+/ubn3/+2fz5559mw4YNZtKkScaYG/t20aJFzciRI82JEyfMiRMnjDE3fmdjx44127ZtMwcOHDDjx483bm5uZsOGDbYaevToYcLDw82yZcvMzp07TatWrYyfn5/p37+/rU14eLjx9/c37733ntm/f7/Zv3+/McaYt956y6xZs8YcOnTIzJ8/3xQqVMi88847tuWGDRtm8ubNa9q2bWt2795t5s+fbzw8PEx0dLR5/vnnzd69e83kyZONJLN+/frsfKv/8e6V41dGnxWNMaZSpUqmadOmtueSzLx584wxxowdO9aEhYWZlStXmsOHD5tVq1aZ6dOn27UNCgoyX3zxhYmLizNvvPGGcXNzM7///nu623vt2jXz5ptvmk2bNpmDBw+aadOmGR8fHzNr1izbOsuUKWPeffdd2/Nr166ZAgUKmMmTJ2e4fc5ESMrFunTpYtzc3Iyvr6/t0bZt2zTt5syZY4KCgmzPO3ToYOrUqZPuOq9evWp8fHzM2rVr7aZ3797ddOjQwRjzf3/YqR8gjblxMPH29rbt7B07djSPPvqo3TpefvllU6FCBWOMMX/88YeRZNasWWOb/7///c94e3ub2bNnG2P+74P33r17TVhYmHnhhRfsPqQg61gPoikpKeaXX34xnp6eZtCgQem2v3mfujkkRUVFmT59+tgtU7NmzUxD0sWLF02zZs2MJBMeHm7at29v/vvf/5qrV6/a2jzyyCNp/sP65ptvTGhoaIbrTa9WSWb79u22aXFxcUaS+eWXX9JdR+o+v2zZMtu0hQsXGknmypUrGb72/W79+vV2/+nebNy4cUaSOXXqlDHmxoeMp556yjY/JSXFBAcHm4kTJxpjHPuQIcn2gdIYYyZMmGAKFSpke16yZEm7/+iNufHBMyoqKsPt2LNnj5FkYmJibNPq1atnV+vNISk0NNTuP/ukpCRTtGhR29+ZI8fa119/3ZQtW9buuDdhwgSTN29ek5ycnGG9yNjNIalu3bp286tXr25effVVY4wx77//vilTpozti7ubhYeHmw8++OCWr/mvf/3LDBw40BhjTEJCgnF3dzdz5syxzT9//rzx8fFJE5Jatmx5y3WPHTvWVK1a1fZ82LBhxsfHxyQkJNimRUdHm+LFi9vtM2XLljWjR4++5frvZ/fK8SuzkNS+fXtTvnx523Pr9j7//POmUaNGGX7ukmR69eplN61mzZq2LyVv3t709O3b17Rp08b2/J133rGrZ+7cuSZv3rzm4sWLGa7DmfLkQGcV7kLDhg01ceJE23NfX18tW7ZMo0eP1t69e5WQkKDr16/r6tWrunz5snx8fLR9+3Y98cQT6a5v//79unz5sh599FG76deuXVOVKlXspkVFRdl+DgwMVNmyZbVnzx5J0p49e/T444/bta9Tp44+/PBDJScna8+ePcqTJ49q1qxpmx8UFGS3Dkm6cuWK6tWrp44dO3KBbDb76aeflDdvXiUlJSklJUUdO3a0nXpyq33qZnv27FGvXr3spkVFRSkmJibD1/f19dXChQt14MABxcTEaP369Ro4cKA++ugjrVu3Tj4+Pvrtt9+0Zs0au1NFkpOT7WpxpFYPDw9VrFjRto7t27fLzc1N9evXz/Q9si4TGhoqSTp9+rSKFSuW6XL3O3PTaWaZsb7HLi4uCgkJ0enTpx1e3sfHRyVLlrQ9Dw0NtS1/6dIlHThwQN27d1fPnj1tba5fv57pxdPlypVT7dq1NXnyZDVo0ED79+/XqlWrNHLkyHTbx8fH68SJE3bHtzx58qhatWq298KRY+2ePXsUFRVld81CnTp1dPHiRR07doz9LgtY9zfJfn954okn9OGHHyoiIkJNmjRRs2bN1KJFC+XJk/FHo+TkZL399tuaPXu2/vrrL127dk2JiYm2Y8/BgweVlJSkGjVq2JYJCAhQ2bJl06yrWrVqaabNmjVL48eP14EDB3Tx4kVdv35d/v7+dm2KFy8uPz8/2/NChQrJzc1Nrq6udtNu5+/qfvZPP35lxhiT4TVRXbt21aOPPqqyZcuqSZMmat68uR577DG7NtbPganPMxvNbsKECZo8ebKOHDmiK1eu6Nq1a3anKXft2lVvvPGG1q9fr1q1amnq1Klq166dfH1972j7shvXJOVyvr6+KlWqlO2RmJio5s2bq2LFipo7d662bNliu6Yj9cJPb2/vDNeXeu3GwoULtX37dtvj999/z/Rc0+zi6empxo0b66efftJff/2V469/P2nYsKG2b9+uffv26cqVK/rqq6/k6+urw4cP33KfykolS5ZUjx499OWXX2rr1q36/fffNWvWLEk39s8RI0bY7Zs7d+7Uvn375OXl5XCt3t7edv8xZPY3YeXu7m77OXV5Bn3IWKlSpeTi4mL3xYfVnj17lD9/fhUsWNA2zfoeSzfe59t5j9NbPvVDTurx7YsvvrDbh3bt2qX169dnut7u3btr7ty5unDhgqZMmaKSJUveMlRnJrcda+9Xme1vYWFhiouL06effipvb2/16dNHDz/8cKaDyYwdO1YfffSRXn31VcXExGj79u2Kjo6+o2PlzR8M161bp06dOqlZs2b66aeftG3bNg0ZMiTNutPbprv9u7of3UvHr4zs2bMnw8G+HnroIR06dEhvvfWWrly5onbt2qlt27Z39DqSNHPmTA0aNEjdu3fX0qVLtX37dj3zzDN2+29wcLBatGihKVOm6NSpU1q0aJG6det2x6+Z3QhJ/zBbtmxRSkqK3n//fdWqVUtlypTR8ePH7dpUrFgxw6FqrReyW8NXqVKlFBYWZtfW+kd57tw5/fHHHypfvrwkqXz58lqzZo1d+zVr1qhMmTJyc3NT+fLldf36dW3YsME2/+zZs4qLi1OFChVs01xdXfXNN9+oatWqatiwYZptQdZJDdzFihWz+6bUkX3qZuXLl7f73Uq6o4N48eLF5ePjo0uXLkm6cdCOi4tLs2+WKlVKrq6ud1SrJEVGRiolJUUrVqy47RqRsaCgID366KP69NNPdeXKFbt5J0+e1Lfffqv27dvnyOhO0o1vzwsXLqyDBw+m2X9uNSpou3bt5OrqqunTp+vrr79Wt27dMqw7ICBAoaGhdn8D169f15YtW2zPHTnWli9fXuvWrbP7JnvNmjXy8/NT0aJF7+atgIO8vb3VokULjR8/XrGxsVq3bp127twp6UaPdHJysl37NWvW6PHHH9dTTz2lSpUqKSIiwu72CBEREXJ3d9emTZts0+Lj4x26hcLatWsVHh6uIUOGqFq1aipdurT+/PPPLNpS3OxeOn6l59dff9XOnTvVpk2bDNv4+/urffv2+uKLLzRr1izNnTvXbkS/m/9fX79+ve1z4M3WrFmj2rVrq0+fPqpSpYpKlSqlAwcOpGnXo0cPzZo1S5MmTVLJkiVVp06d2962nMLpdv8wpUqVUlJSkj7++GO1aNFCa9as0WeffWbXZvDgwYqMjFSfPn3Uq1cveXh4KCYmRk888YQKFCigQYMG6aWXXlJKSorq1q2r+Ph4rVmzRv7+/urSpYttPSNHjlRQUJAKFSqkIUOGqECBArb7TwwcOFDVq1fXW2+9pfbt22vdunX65JNPbKOwlC5dWo8//rh69uypzz//XH5+fnrttddUpEiRNKfpubm56dtvv1WHDh3UqFEjxcbGKiQkJHvfSNg4sk/drH///uratauqVaumOnXq6Ntvv9Xu3bsVERGR4TLDhw/X5cuX1axZM4WHh+v8+fMaP368kpKSbKckvfnmm2revLmKFSumtm3bytXVVb/99pt27dqlUaNG3VGt0o0w1qVLF3Xr1k3jx49XpUqV9Oeff+r06dNq167d7b1hsPPJJ5+odu3aio6O1qhRo1SiRAnt3r1bL7/8sooUKZLjo2yNGDFCL7zwggICAtSkSRMlJiZq8+bNOnfunAYMGJDhcnnz5lX79u01ePBgJSQkqGvXrpm+Tv/+/TVmzBiVLl1a5cqV07hx4+xuGunn53fLY22fPn304Ycf6vnnn1e/fv0UFxenYcOGacCAAXanTiF7TJ06VcnJyapZs6Z8fHw0bdo0eXt7Kzw8XNKN48bKlSv15JNPytPTUwUKFFDp0qX13Xffae3atcqfP7/GjRunU6dO2b788/PzU5cuXfTyyy8rMDBQwcHBGjZsmFxdXW/5Ybt06dI6cuSIZs6cqerVq2vhwoWaN29etr8P97N75fiVmJiokydPKjk5WadOndLixYs1evRoNW/eXJ07d053mXHjxik0NFRVqlSRq6ur5syZo5CQELuRbOfMmaNq1aqpbt26+vbbb7Vx48Y0o8KmKl26tL7++mstWbJEJUqU0DfffKNNmzalCXjR0dHy9/fXqFGjMjylObfgKPwPU6lSJY0bN07vvPOOHnzwQX377bd2QzZKUpkyZbR06VL99ttvqlGjhqKiovTjjz/aeg/eeustDR06VKNHj1b58uXVpEkTLVy4MM2OPGbMGPXv319Vq1bVyZMntWDBAnl4eEi68Y3/7NmzNXPmTD344IN68803NXLkSLsPFlOmTFHVqlXVvHlzRUVFyRijn3/+OU13s3TjfP4ZM2bogQceUKNGjTiXOgc5sk/drH379ho6dKheeeUVVa1aVX/++ad69+6d6TL169fXwYMH1blzZ5UrV05NmzbVyZMntXTpUtv5+tHR0frpp5+0dOlSVa9eXbVq1dIHH3xg+9ByJ7Wmmjhxotq2bas+ffqoXLly6tmzp60HC3eudOnS2rx5syIiItSuXTuVLFlSzz77rBo2bKh169YpMDAwR+tJPZVzypQpioyMVP369TV16lSHvont3r27zp07p+joaBUuXDjTtgMHDtTTTz+tLl26KCoqSn5+fmrVqpVdm1sda4sUKaKff/5ZGzduVKVKldSrVy91795db7zxxp2/AXBYvnz59MUXX6hOnTqqWLGili1bpgULFtjuhzVy5EgdPnxYJUuWtJ1y9cYbb+ihhx5SdHS0GjRooJCQkDQ3rx03bpyioqLUvHlzNW7cWHXq1LEN6ZyZf//733rppZfUr18/Va5cWWvXrtXQoUOzZdtxw71y/Fq8eLFCQ0NVvHhxNWnSRDExMRo/frx+/PFHubm5pbuMn5+f3n33XVWrVk3Vq1fX4cOH9fPPP9t9QTNixAjNnDlTFStW1Ndff60ZM2bYnQ1k9dxzz6l169Zq3769atasqbNnz6pPnz5p2rm6uqpr165KTk7OMMDlFi7mdq5YAwAAgMMuXbqkIkWK6P3337fddwvI7VxcXDRv3rw0XwJkhe7du+vMmTO2ezXmVpxuBwAAkEW2bdumvXv3qkaNGoqPj7edUnTzqebA/SY+Pl47d+7U9OnTc31AkghJAAAAWeq9995TXFycPDw8VLVqVa1atUoFChRwdlmAUz3++OPauHGjevXqleb2CLkRp9sBAAAAgAUDNwAAAACABSEJAAAAACwISQAAAABgQUgCAAAAAAtCEgAAAABYEJIAALmei4uLfvjhB2eX4ZCuXbtmyw0YAQA5h5AEAHC6kydP6vnnn1dERIQ8PT0VFhamFi1aaPny5c4uDQBwH+JmsgAApzp8+LDq1KmjfPnyaezYsYqMjFRSUpKWLFmivn37au/evc4uEQBwn6EnCQDgVH369JGLi4s2btyoNm3aqEyZMnrggQc0YMAArV+/3tbuf//7n1q1aiUfHx+VLl1a8+fPt81LTk5W9+7dVaJECXl7e6ts2bL66KOP7F4n9TS49957T6GhoQoKClLfvn2VlJRka1O8eHG9/fbb6tatm/z8/FSsWDFNmjTJbj1Hjx5Vu3btlC9fPgUGBurxxx/X4cOHs+fNAQA4BSEJAOA0f//9txYvXqy+ffvK19c3zfx8+fLZfh4xYoTatWunHTt2qFmzZurUqZP+/vtvSVJKSoqKFi2qOXPm6Pfff9ebb76p119/XbNnz7ZbX0xMjA4cOKCYmBh99dVXmjp1qqZOnWrX5v3331e1atW0bds29enTR71791ZcXJwkKSkpSdHR0fLz89OqVau0Zs0a5c2bV02aNNG1a9ey9s0BADgNIQkA4DT79++XMUblypW7ZduuXbuqQ4cOKlWqlN5++21dvHhRGzdulCS5u7trxIgRqlatmkqUKKFOnTrpmWeeSROS8ufPr08++UTlypVT8+bN9a9//SvNdU/NmjVTnz59VKpUKb366qsqUKCAYmJiJEmzZs1SSkqKvvzyS0VGRqp8+fKaMmWKjhw5otjY2Kx5UwAATsc1SQAApzHGONy2YsWKtp99fX3l7++v06dP26ZNmDBBkydP1pEjR3TlyhVdu3ZNlStXtlvHAw88IDc3N9vz0NBQ7dy5M8PXcXFxUUhIiO11fvvtN+3fv19+fn52y1y9elUHDhxweFsAALkbIQkA4DSlS5eWi4uLQ4MzuLu72z13cXFRSkqKJGnmzJkaNGiQ3n//fUVFRcnPz09jx47Vhg0bHF6HI20uXryoqlWr6ttvv01TX8GCBW+5DQCAfwZCEgDAaQIDAxUdHa0JEybohRdeSHNd0vnz5+2uS8rImjVrVLt2bfXp08c2LTt6dh566CHNmjVLwcHB8vf3z/L1AwByB65JAgA41YQJE5ScnKwaNWpo7ty52rdvn/bs2aPx48crKirKoXWULl1amzdv1pIlS/THH39o6NCh2rRpU5bX2qlTJxUoUECPP/64Vq1apUOHDik2NlYvvPCCjh07luWvBwBwDkISAMCpIiIitHXrVjVs2FADBw7Ugw8+qEcffVTLly/XxIkTHVrHc889p9atW6t9+/aqWbOmzp49a9erlFV8fHy0cuVKFStWTK1bt1b58uXVvXt3Xb16lZ4lALiHuJjbuWoWAAAAAO5x9CQBAAAAgAUhCQAAAAAsCEkAAAAAYEFIAgAAAAALQhIAAAAAWBCSAAAAAMCCkAQAAAAAFoQkAAAAALAgJAEAAACABSEJAAAAACwISQAAAABg8f8AbOBVcrB8WTgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(10, 6))\n",
    "sns.barplot(data=last_touch, x=last_touch.index, y='Weight (%)')\n",
    "plt.xlabel('Channel')\n",
    "plt.title('Last Touch Channel Weights', fontsize=20)\n",
    "plt.savefig('plot/last_touch.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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