Added consideration of race position and gap to ahead cars
This commit is contained in:
Aditya Pulipaka
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 4,
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"id": "be0c6fbf",
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"metadata": {},
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"outputs": [],
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@@ -31,7 +31,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 5,
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"id": "f757cb34",
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"metadata": {},
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"outputs": [
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@@ -39,7 +39,6 @@
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"req WARNING \tDEFAULT CACHE ENABLED! (318.35 MB) /Users/adipu/Library/Caches/fastf1\n",
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"core INFO \tLoading data for Italian Grand Prix - Race [v3.6.1]\n",
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"req INFO \tUsing cached data for session_info\n",
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"req INFO \tUsing cached data for driver_info\n",
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@@ -95,7 +94,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 6,
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"id": "aa5e5d8f",
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"metadata": {},
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"outputs": [
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@@ -136,6 +135,9 @@
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" <th></th>\n",
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" <th>lap_number</th>\n",
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" <th>total_laps</th>\n",
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" <th>position</th>\n",
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" <th>gap_to_leader</th>\n",
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" <th>gap_to_ahead</th>\n",
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" <th>lap_time</th>\n",
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" <th>average_speed</th>\n",
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" <th>max_speed</th>\n",
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@@ -150,6 +152,9 @@
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>6.223</td>\n",
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" <td>0.620</td>\n",
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" <td>0 days 00:01:33.340000</td>\n",
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" <td>210.17</td>\n",
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" <td>326.0</td>\n",
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@@ -162,6 +167,9 @@
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" <th>1</th>\n",
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" <td>2</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>8.229</td>\n",
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" <td>0.712</td>\n",
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" <td>0 days 00:01:28.012000</td>\n",
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" <td>236.87</td>\n",
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" <td>330.0</td>\n",
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@@ -174,6 +182,9 @@
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" <th>2</th>\n",
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" <td>3</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>9.799</td>\n",
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" <td>0.898</td>\n",
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" <td>0 days 00:01:27.546000</td>\n",
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" <td>236.40</td>\n",
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" <td>331.0</td>\n",
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@@ -186,6 +197,9 @@
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" <th>3</th>\n",
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" <td>4</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>10.953</td>\n",
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" <td>0.919</td>\n",
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" <td>0 days 00:01:27.221000</td>\n",
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" <td>240.13</td>\n",
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" <td>341.0</td>\n",
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@@ -198,6 +212,9 @@
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" <th>4</th>\n",
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" <td>5</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>11.563</td>\n",
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" <td>0.917</td>\n",
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" <td>0 days 00:01:27.033000</td>\n",
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" <td>236.09</td>\n",
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" <td>345.0</td>\n",
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@@ -210,6 +227,9 @@
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" <th>5</th>\n",
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" <td>6</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>12.123</td>\n",
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" <td>0.923</td>\n",
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" <td>0 days 00:01:27.175000</td>\n",
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" <td>236.74</td>\n",
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" <td>343.0</td>\n",
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@@ -222,6 +242,9 @@
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" <th>6</th>\n",
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" <td>7</td>\n",
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" <td>51</td>\n",
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" <td>11</td>\n",
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" <td>12.694</td>\n",
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" <td>0.387</td>\n",
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" <td>0 days 00:01:26.929000</td>\n",
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" <td>239.72</td>\n",
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" <td>340.0</td>\n",
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@@ -234,6 +257,9 @@
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" <th>7</th>\n",
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" <td>8</td>\n",
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" <td>51</td>\n",
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" <td>10</td>\n",
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" <td>13.413</td>\n",
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" <td>2.760</td>\n",
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" <td>0 days 00:01:26.943000</td>\n",
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" <td>238.45</td>\n",
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" <td>351.0</td>\n",
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@@ -246,6 +272,9 @@
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" <th>8</th>\n",
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" <td>9</td>\n",
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" <td>51</td>\n",
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" <td>10</td>\n",
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" <td>14.320</td>\n",
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" <td>3.387</td>\n",
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" <td>0 days 00:01:27.383000</td>\n",
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" <td>236.81</td>\n",
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" <td>330.0</td>\n",
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@@ -258,6 +287,9 @@
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" <th>9</th>\n",
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" <td>10</td>\n",
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" <td>51</td>\n",
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" <td>10</td>\n",
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" <td>15.177</td>\n",
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" <td>3.760</td>\n",
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" <td>0 days 00:01:27.368000</td>\n",
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" <td>232.42</td>\n",
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" <td>331.0</td>\n",
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@@ -271,32 +303,44 @@
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"</div>"
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],
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"text/plain": [
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" lap_number total_laps lap_time average_speed max_speed \\\n",
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"0 1 51 0 days 00:01:33.340000 210.17 326.0 \n",
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"1 2 51 0 days 00:01:28.012000 236.87 330.0 \n",
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"2 3 51 0 days 00:01:27.546000 236.40 331.0 \n",
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"3 4 51 0 days 00:01:27.221000 240.13 341.0 \n",
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"4 5 51 0 days 00:01:27.033000 236.09 345.0 \n",
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"5 6 51 0 days 00:01:27.175000 236.74 343.0 \n",
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"6 7 51 0 days 00:01:26.929000 239.72 340.0 \n",
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"7 8 51 0 days 00:01:26.943000 238.45 351.0 \n",
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"8 9 51 0 days 00:01:27.383000 236.81 330.0 \n",
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"9 10 51 0 days 00:01:27.368000 232.42 331.0 \n",
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" lap_number total_laps position gap_to_leader gap_to_ahead \\\n",
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"0 1 51 11 6.223 0.620 \n",
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"1 2 51 11 8.229 0.712 \n",
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"2 3 51 11 9.799 0.898 \n",
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"3 4 51 11 10.953 0.919 \n",
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"4 5 51 11 11.563 0.917 \n",
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"5 6 51 11 12.123 0.923 \n",
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"6 7 51 11 12.694 0.387 \n",
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"7 8 51 10 13.413 2.760 \n",
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"8 9 51 10 14.320 3.387 \n",
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"9 10 51 10 15.177 3.760 \n",
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"\n",
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" tire_compound tire_life_laps track_temperature rainfall \n",
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"0 MEDIUM 1 42.5 False \n",
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"1 MEDIUM 2 42.5 False \n",
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"2 MEDIUM 3 43.2 False \n",
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"3 MEDIUM 4 43.2 False \n",
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"4 MEDIUM 5 43.1 False \n",
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"5 MEDIUM 6 43.3 False \n",
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"6 MEDIUM 7 43.6 False \n",
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"7 MEDIUM 8 43.6 False \n",
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"8 MEDIUM 9 43.6 False \n",
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"9 MEDIUM 10 43.9 False "
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" lap_time average_speed max_speed tire_compound \\\n",
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"0 0 days 00:01:33.340000 210.17 326.0 MEDIUM \n",
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"1 0 days 00:01:28.012000 236.87 330.0 MEDIUM \n",
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"2 0 days 00:01:27.546000 236.40 331.0 MEDIUM \n",
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"3 0 days 00:01:27.221000 240.13 341.0 MEDIUM \n",
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"4 0 days 00:01:27.033000 236.09 345.0 MEDIUM \n",
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"5 0 days 00:01:27.175000 236.74 343.0 MEDIUM \n",
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"6 0 days 00:01:26.929000 239.72 340.0 MEDIUM \n",
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"7 0 days 00:01:26.943000 238.45 351.0 MEDIUM \n",
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"8 0 days 00:01:27.383000 236.81 330.0 MEDIUM \n",
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"9 0 days 00:01:27.368000 232.42 331.0 MEDIUM \n",
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"\n",
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" tire_life_laps track_temperature rainfall \n",
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"0 1 42.5 False \n",
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"1 2 42.5 False \n",
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"2 3 43.2 False \n",
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"3 4 43.2 False \n",
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"4 5 43.1 False \n",
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"5 6 43.3 False \n",
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"6 7 43.6 False \n",
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"7 8 43.6 False \n",
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"8 9 43.6 False \n",
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"9 10 43.9 False "
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]
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},
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"execution_count": 3,
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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@@ -306,7 +350,10 @@
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"weather = session.weather_data\n",
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"weather['SessionTime'] = pd.to_timedelta(weather['Time'])\n",
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"\n",
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"# 4. Create lap-level data by aggregating telemetry\n",
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"# 4. Get all laps for position calculation\n",
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"all_laps = session.laps\n",
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"\n",
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"# 5. Create lap-level data by aggregating telemetry\n",
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"lap_data_list = []\n",
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"\n",
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"for lap_idx in driver_laps.index:\n",
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@@ -332,6 +379,43 @@
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" tire_compound = lap['Compound']\n",
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" tire_life = lap['TyreLife']\n",
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" \n",
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" # Get position data for this lap\n",
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" position = lap['Position']\n",
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" \n",
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" # Calculate gaps: get all drivers' data for this lap\n",
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" this_lap_all_drivers = all_laps[all_laps['LapNumber'] == lap_number].copy()\n",
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" \n",
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" # Sort by position to calculate gaps\n",
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" this_lap_all_drivers = this_lap_all_drivers.sort_values('Position')\n",
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" \n",
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" # Calculate cumulative race time for gap calculations\n",
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" gap_to_leader = 0.0\n",
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" gap_to_ahead = 0.0\n",
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" \n",
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" if pd.notna(position) and position > 1:\n",
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" # Get our driver's data\n",
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" our_data = this_lap_all_drivers[this_lap_all_drivers['Driver'] == 'ALO']\n",
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" \n",
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" if not our_data.empty:\n",
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" # Time at the end of this lap (cumulative)\n",
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" # Note: FastF1 provides 'Time' which is cumulative race time\n",
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" our_time = our_data['Time'].values[0]\n",
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" \n",
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" # Get leader's time (P1)\n",
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" leader_data = this_lap_all_drivers[this_lap_all_drivers['Position'] == 1]\n",
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" if not leader_data.empty:\n",
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" leader_time = leader_data['Time'].values[0]\n",
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" # Convert numpy.timedelta64 to seconds\n",
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" gap_to_leader = (our_time - leader_time) / np.timedelta64(1, 's')\n",
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" \n",
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" # Get car ahead's time (Position - 1)\n",
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" ahead_position = position - 1\n",
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" ahead_data = this_lap_all_drivers[this_lap_all_drivers['Position'] == ahead_position]\n",
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" if not ahead_data.empty:\n",
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" ahead_time = ahead_data['Time'].values[0]\n",
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" # Convert numpy.timedelta64 to seconds\n",
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" gap_to_ahead = (our_time - ahead_time) / np.timedelta64(1, 's')\n",
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" \n",
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" # Get weather data for this lap (use lap start time)\n",
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" lap_start_time = pd.to_timedelta(lap['LapStartTime'])\n",
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" \n",
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@@ -344,6 +428,9 @@
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" lap_record = {\n",
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" 'lap_number': int(lap_number),\n",
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" 'total_laps': int(total_laps),\n",
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" 'position': int(position) if pd.notna(position) else None,\n",
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" 'gap_to_leader': round(gap_to_leader, 3) if gap_to_leader > 0 else 0.0,\n",
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" 'gap_to_ahead': round(gap_to_ahead, 3) if gap_to_ahead > 0 else 0.0,\n",
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" 'lap_time': lap_time,\n",
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" 'average_speed': round(avg_speed, 2),\n",
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" 'max_speed': round(max_speed, 2),\n",
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@@ -359,7 +446,7 @@
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" if lap_number % 10 == 0:\n",
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" print(f\"Processed lap {int(lap_number)}...\")\n",
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"\n",
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"# 5. Create final dataframe\n",
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"# 6. Create final dataframe\n",
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"laps_df = pd.DataFrame(lap_data_list)\n",
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"\n",
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"print(f\"\\n✓ Created lap-level dataframe with {len(laps_df)} laps\")\n",
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@@ -369,7 +456,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 7,
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"id": "b1086b8d",
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"metadata": {},
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"outputs": [
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@@ -383,6 +470,9 @@
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"Column types:\n",
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"lap_number int64\n",
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"total_laps int64\n",
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"position int64\n",
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"gap_to_leader float64\n",
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"gap_to_ahead float64\n",
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"lap_time timedelta64[ns]\n",
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"average_speed float64\n",
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"max_speed float64\n",
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@@ -418,6 +508,9 @@
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" <th></th>\n",
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" <th>lap_number</th>\n",
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" <th>total_laps</th>\n",
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" <th>position</th>\n",
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" <th>gap_to_leader</th>\n",
|
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" <th>gap_to_ahead</th>\n",
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" <th>lap_time</th>\n",
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" <th>average_speed</th>\n",
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" <th>max_speed</th>\n",
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@@ -430,6 +523,9 @@
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" <th>count</th>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51</td>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
@@ -440,6 +536,9 @@
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" <th>mean</th>\n",
|
||||
" <td>26.000000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>9.803922</td>\n",
|
||||
" <td>29.418314</td>\n",
|
||||
" <td>2.889235</td>\n",
|
||||
" <td>0 days 00:01:27.596803921</td>\n",
|
||||
" <td>235.797059</td>\n",
|
||||
" <td>333.686275</td>\n",
|
||||
@@ -450,6 +549,9 @@
|
||||
" <th>std</th>\n",
|
||||
" <td>14.866069</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>1.058671</td>\n",
|
||||
" <td>13.842909</td>\n",
|
||||
" <td>1.707825</td>\n",
|
||||
" <td>0 days 00:00:03.069690434</td>\n",
|
||||
" <td>7.855085</td>\n",
|
||||
" <td>4.921342</td>\n",
|
||||
@@ -460,6 +562,9 @@
|
||||
" <th>min</th>\n",
|
||||
" <td>1.000000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>6.000000</td>\n",
|
||||
" <td>6.223000</td>\n",
|
||||
" <td>0.387000</td>\n",
|
||||
" <td>0 days 00:01:26.105000</td>\n",
|
||||
" <td>191.140000</td>\n",
|
||||
" <td>322.000000</td>\n",
|
||||
@@ -470,6 +575,9 @@
|
||||
" <th>25%</th>\n",
|
||||
" <td>13.500000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>9.000000</td>\n",
|
||||
" <td>16.928500</td>\n",
|
||||
" <td>1.123000</td>\n",
|
||||
" <td>0 days 00:01:26.715000</td>\n",
|
||||
" <td>236.105000</td>\n",
|
||||
" <td>331.000000</td>\n",
|
||||
@@ -480,6 +588,9 @@
|
||||
" <th>50%</th>\n",
|
||||
" <td>26.000000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>10.000000</td>\n",
|
||||
" <td>29.113000</td>\n",
|
||||
" <td>2.799000</td>\n",
|
||||
" <td>0 days 00:01:26.943000</td>\n",
|
||||
" <td>237.130000</td>\n",
|
||||
" <td>332.000000</td>\n",
|
||||
@@ -490,6 +601,9 @@
|
||||
" <th>75%</th>\n",
|
||||
" <td>38.500000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>10.000000</td>\n",
|
||||
" <td>43.405500</td>\n",
|
||||
" <td>4.136500</td>\n",
|
||||
" <td>0 days 00:01:27.328500</td>\n",
|
||||
" <td>238.655000</td>\n",
|
||||
" <td>334.000000</td>\n",
|
||||
@@ -500,6 +614,9 @@
|
||||
" <th>max</th>\n",
|
||||
" <td>51.000000</td>\n",
|
||||
" <td>51.0</td>\n",
|
||||
" <td>12.000000</td>\n",
|
||||
" <td>48.171000</td>\n",
|
||||
" <td>8.135000</td>\n",
|
||||
" <td>0 days 00:01:47.272000</td>\n",
|
||||
" <td>241.700000</td>\n",
|
||||
" <td>351.000000</td>\n",
|
||||
@@ -511,28 +628,38 @@
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" lap_number total_laps lap_time average_speed \\\n",
|
||||
"count 51.000000 51.0 51 51.000000 \n",
|
||||
"mean 26.000000 51.0 0 days 00:01:27.596803921 235.797059 \n",
|
||||
"std 14.866069 0.0 0 days 00:00:03.069690434 7.855085 \n",
|
||||
"min 1.000000 51.0 0 days 00:01:26.105000 191.140000 \n",
|
||||
"25% 13.500000 51.0 0 days 00:01:26.715000 236.105000 \n",
|
||||
"50% 26.000000 51.0 0 days 00:01:26.943000 237.130000 \n",
|
||||
"75% 38.500000 51.0 0 days 00:01:27.328500 238.655000 \n",
|
||||
"max 51.000000 51.0 0 days 00:01:47.272000 241.700000 \n",
|
||||
" lap_number total_laps position gap_to_leader gap_to_ahead \\\n",
|
||||
"count 51.000000 51.0 51.000000 51.000000 51.000000 \n",
|
||||
"mean 26.000000 51.0 9.803922 29.418314 2.889235 \n",
|
||||
"std 14.866069 0.0 1.058671 13.842909 1.707825 \n",
|
||||
"min 1.000000 51.0 6.000000 6.223000 0.387000 \n",
|
||||
"25% 13.500000 51.0 9.000000 16.928500 1.123000 \n",
|
||||
"50% 26.000000 51.0 10.000000 29.113000 2.799000 \n",
|
||||
"75% 38.500000 51.0 10.000000 43.405500 4.136500 \n",
|
||||
"max 51.000000 51.0 12.000000 48.171000 8.135000 \n",
|
||||
"\n",
|
||||
" max_speed tire_life_laps track_temperature \n",
|
||||
"count 51.000000 51.000000 51.000000 \n",
|
||||
"mean 333.686275 15.411765 42.898039 \n",
|
||||
"std 4.921342 8.616673 0.876924 \n",
|
||||
"min 322.000000 1.000000 40.800000 \n",
|
||||
"25% 331.000000 8.500000 42.500000 \n",
|
||||
"50% 332.000000 15.000000 43.100000 \n",
|
||||
"75% 334.000000 21.000000 43.600000 \n",
|
||||
"max 351.000000 33.000000 44.300000 "
|
||||
" lap_time average_speed max_speed tire_life_laps \\\n",
|
||||
"count 51 51.000000 51.000000 51.000000 \n",
|
||||
"mean 0 days 00:01:27.596803921 235.797059 333.686275 15.411765 \n",
|
||||
"std 0 days 00:00:03.069690434 7.855085 4.921342 8.616673 \n",
|
||||
"min 0 days 00:01:26.105000 191.140000 322.000000 1.000000 \n",
|
||||
"25% 0 days 00:01:26.715000 236.105000 331.000000 8.500000 \n",
|
||||
"50% 0 days 00:01:26.943000 237.130000 332.000000 15.000000 \n",
|
||||
"75% 0 days 00:01:27.328500 238.655000 334.000000 21.000000 \n",
|
||||
"max 0 days 00:01:47.272000 241.700000 351.000000 33.000000 \n",
|
||||
"\n",
|
||||
" track_temperature \n",
|
||||
"count 51.000000 \n",
|
||||
"mean 42.898039 \n",
|
||||
"std 0.876924 \n",
|
||||
"min 40.800000 \n",
|
||||
"25% 42.500000 \n",
|
||||
"50% 43.100000 \n",
|
||||
"75% 43.600000 \n",
|
||||
"max 44.300000 "
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -549,7 +676,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"execution_count": 8,
|
||||
"id": "b2a3b878",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@@ -569,7 +696,55 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"execution_count": 9,
|
||||
"id": "efcff166",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"Position and Gap Analysis:\n",
|
||||
"Starting position: P11\n",
|
||||
"Final position: P9\n",
|
||||
"Average gap to leader: 29.42s\n",
|
||||
"Average gap to car ahead: 2.89s\n",
|
||||
"\n",
|
||||
"Position changes over race:\n",
|
||||
" lap_number position gap_to_leader gap_to_ahead\n",
|
||||
"0 1 11 6.223 0.620\n",
|
||||
"1 2 11 8.229 0.712\n",
|
||||
"2 3 11 9.799 0.898\n",
|
||||
"3 4 11 10.953 0.919\n",
|
||||
"4 5 11 11.563 0.917\n",
|
||||
"5 6 11 12.123 0.923\n",
|
||||
"6 7 11 12.694 0.387\n",
|
||||
"7 8 10 13.413 2.760\n",
|
||||
"8 9 10 14.320 3.387\n",
|
||||
"9 10 10 15.177 3.760\n",
|
||||
"10 11 10 15.829 3.984\n",
|
||||
"11 12 10 16.760 4.129\n",
|
||||
"12 13 10 17.031 3.995\n",
|
||||
"13 14 10 17.666 4.076\n",
|
||||
"14 15 10 17.366 0.469\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Display position and gap information\n",
|
||||
"print(\"\\nPosition and Gap Analysis:\")\n",
|
||||
"print(f\"Starting position: P{laps_df['position'].iloc[0]}\")\n",
|
||||
"print(f\"Final position: P{laps_df['position'].iloc[-1]}\")\n",
|
||||
"print(f\"Average gap to leader: {laps_df['gap_to_leader'].mean():.2f}s\")\n",
|
||||
"print(f\"Average gap to car ahead: {laps_df['gap_to_ahead'].mean():.2f}s\")\n",
|
||||
"print(f\"\\nPosition changes over race:\")\n",
|
||||
"print(laps_df[['lap_number', 'position', 'gap_to_leader', 'gap_to_ahead']].head(15))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "0202372e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
||||
Reference in New Issue
Block a user