Upload folder using huggingface_hub

.gitattributes

@@ -61,3 +61,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 Seongnam/osm_simplified.osm.pbf filter=lfs diff=lfs merge=lfs -text
 Seongnam/road_graph.gpkg filter=lfs diff=lfs merge=lfs -text
 Seongnam/road_graph_nodes.gpkg filter=lfs diff=lfs merge=lfs -text
+NYC/osm_simplified.osm.pbf filter=lfs diff=lfs merge=lfs -text
+NYC/road_graph.gpkg filter=lfs diff=lfs merge=lfs -text
+NYC/road_graph_nodes.gpkg filter=lfs diff=lfs merge=lfs -text
+NYC/taxi_zones/taxi_zones.shp filter=lfs diff=lfs merge=lfs -text

NYC/boundary.geojson

@@ -0,0 +1,8 @@
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+]
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NYC/edge_index.pkl

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NYC/nyc_manhattan_2017-10-19.parquet

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NYC/nyc_taxi_preprocessing.ipynb

@@ -0,0 +1,729 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# NYC Yellow Taxi Data Preprocessing\n",
+    "\n",
+    "- **Date**: 2017-10-19 (Thursday)\n",
+    "- **Time**: 06:00 ~ 10:00 (Morning Rush)\n",
+    "- **Goal**: LocationID → lat/lon coordinate mapping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import geopandas as gpd\n",
+    "\n",
+    "DATA_DIR = '.'\n",
+    "TARGET_DATE = '2017-10-19'\n",
+    "TIME_START = 6   # 06:00\n",
+    "TIME_END = 10    # 10:00"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Taxi Zones Shapefile → Centroid Coordinates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total zones: 263\n"
+     ]
+    },
+    {
+     "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>LocationID</th>\n",
+       "      <th>zone</th>\n",
+       "      <th>borough</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Newark Airport</td>\n",
+       "      <td>EWR</td>\n",
+       "      <td>40.691830</td>\n",
+       "      <td>-74.174002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Jamaica Bay</td>\n",
+       "      <td>Queens</td>\n",
+       "      <td>40.616746</td>\n",
+       "      <td>-73.831300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Allerton/Pelham Gardens</td>\n",
+       "      <td>Bronx</td>\n",
+       "      <td>40.864474</td>\n",
+       "      <td>-73.847422</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Alphabet City</td>\n",
+       "      <td>Manhattan</td>\n",
+       "      <td>40.723752</td>\n",
+       "      <td>-73.976968</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>Arden Heights</td>\n",
+       "      <td>Staten Island</td>\n",
+       "      <td>40.552659</td>\n",
+       "      <td>-74.188485</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>Arrochar/Fort Wadsworth</td>\n",
+       "      <td>Staten Island</td>\n",
+       "      <td>40.600324</td>\n",
+       "      <td>-74.071770</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>Astoria</td>\n",
+       "      <td>Queens</td>\n",
+       "      <td>40.761493</td>\n",
+       "      <td>-73.919694</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>Astoria Park</td>\n",
+       "      <td>Queens</td>\n",
+       "      <td>40.778559</td>\n",
+       "      <td>-73.923086</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>Auburndale</td>\n",
+       "      <td>Queens</td>\n",
+       "      <td>40.751034</td>\n",
+       "      <td>-73.787949</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>Baisley Park</td>\n",
+       "      <td>Queens</td>\n",
+       "      <td>40.678953</td>\n",
+       "      <td>-73.790987</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   LocationID                     zone        borough        lat        lon\n",
+       "0           1           Newark Airport            EWR  40.691830 -74.174002\n",
+       "1           2              Jamaica Bay         Queens  40.616746 -73.831300\n",
+       "2           3  Allerton/Pelham Gardens          Bronx  40.864474 -73.847422\n",
+       "3           4            Alphabet City      Manhattan  40.723752 -73.976968\n",
+       "4           5            Arden Heights  Staten Island  40.552659 -74.188485\n",
+       "5           6  Arrochar/Fort Wadsworth  Staten Island  40.600324 -74.071770\n",
+       "6           7                  Astoria         Queens  40.761493 -73.919694\n",
+       "7           8             Astoria Park         Queens  40.778559 -73.923086\n",
+       "8           9               Auburndale         Queens  40.751034 -73.787949\n",
+       "9          10             Baisley Park         Queens  40.678953 -73.790987"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Shapefile load & WGS84 conversion\n",
+    "zones = gpd.read_file(f'{DATA_DIR}/taxi_zones/taxi_zones.shp')\n",
+    "zones = zones.to_crs(epsg=4326)  # NAD83 feet -> WGS84 lat/lon\n",
+    "\n",
+    "# Centroid calculation (projected CRS for accuracy, then back to WGS84)\n",
+    "zones_proj = zones.to_crs(epsg=2263)  # NYC State Plane (feet)\n",
+    "centroids = zones_proj.geometry.centroid.to_crs(epsg=4326)\n",
+    "zones['lon'] = centroids.x\n",
+    "zones['lat'] = centroids.y\n",
+    "\n",
+    "zone_coords = zones[['LocationID', 'zone', 'borough', 'lat', 'lon']]\n",
+    "print(f'Total zones: {len(zone_coords)}')\n",
+    "zone_coords.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Yellow Taxi Data Load & Filter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total records (Oct 2017): 9,768,672\n",
+      "Columns: ['VendorID', 'tpep_pickup_datetime', 'tpep_dropoff_datetime', 'passenger_count', 'trip_distance', 'RatecodeID', 'store_and_fwd_flag', 'PULocationID', 'DOLocationID', 'payment_type', 'fare_amount', 'extra', 'mta_tax', 'tip_amount', 'tolls_amount', 'improvement_surcharge', 'total_amount', 'congestion_surcharge', 'airport_fee']\n"
+     ]
+    },
+    {
+     "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>VendorID</th>\n",
+       "      <th>tpep_pickup_datetime</th>\n",
+       "      <th>tpep_dropoff_datetime</th>\n",
+       "      <th>passenger_count</th>\n",
+       "      <th>trip_distance</th>\n",
+       "      <th>RatecodeID</th>\n",
+       "      <th>store_and_fwd_flag</th>\n",
+       "      <th>PULocationID</th>\n",
+       "      <th>DOLocationID</th>\n",
+       "      <th>payment_type</th>\n",
+       "      <th>fare_amount</th>\n",
+       "      <th>extra</th>\n",
+       "      <th>mta_tax</th>\n",
+       "      <th>tip_amount</th>\n",
+       "      <th>tolls_amount</th>\n",
+       "      <th>improvement_surcharge</th>\n",
+       "      <th>total_amount</th>\n",
+       "      <th>congestion_surcharge</th>\n",
+       "      <th>airport_fee</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-10-01 00:01:50</td>\n",
+       "      <td>2017-10-01 00:14:13</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>N</td>\n",
+       "      <td>142</td>\n",
+       "      <td>233</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>11.30</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-10-01 00:02:43</td>\n",
+       "      <td>2017-10-01 00:08:35</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>N</td>\n",
+       "      <td>142</td>\n",
+       "      <td>166</td>\n",
+       "      <td>1</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>1.85</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>11.15</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-10-01 00:12:08</td>\n",
+       "      <td>2017-10-01 00:25:49</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>N</td>\n",
+       "      <td>151</td>\n",
+       "      <td>262</td>\n",
+       "      <td>1</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>1.72</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>16.02</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
+       "0         1  2017-10-01 00:01:50   2017-10-01 00:14:13                1   \n",
+       "1         1  2017-10-01 00:02:43   2017-10-01 00:08:35                2   \n",
+       "2         1  2017-10-01 00:12:08   2017-10-01 00:25:49                3   \n",
+       "\n",
+       "   trip_distance  RatecodeID store_and_fwd_flag  PULocationID  DOLocationID  \\\n",
+       "0            2.0           1                  N           142           233   \n",
+       "1            2.3           1                  N           142           166   \n",
+       "2            2.8           1                  N           151           262   \n",
+       "\n",
+       "   payment_type  fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
+       "0             2         10.0    0.5      0.5        0.00           0.0   \n",
+       "1             1          8.0    0.5      0.5        1.85           0.0   \n",
+       "2             1         13.0    0.5      0.5        1.72           0.0   \n",
+       "\n",
+       "   improvement_surcharge  total_amount congestion_surcharge airport_fee  \n",
+       "0                    0.3         11.30                 None        None  \n",
+       "1                    0.3         11.15                 None        None  \n",
+       "2                    0.3         16.02                 None        None  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Parquet load\n",
+    "raw = pd.read_parquet(f'{DATA_DIR}/yellow_tripdata_2017-10.parquet')\n",
+    "print(f'Total records (Oct 2017): {len(raw):,}')\n",
+    "print(f'Columns: {list(raw.columns)}')\n",
+    "raw.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filtered (2017-10-19 6:00~10:00): 60,046 trips\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Date & time filter: 2017-10-19 06:00 ~ 10:00\n",
+    "raw['tpep_pickup_datetime'] = pd.to_datetime(raw['tpep_pickup_datetime'])\n",
+    "raw['tpep_dropoff_datetime'] = pd.to_datetime(raw['tpep_dropoff_datetime'])\n",
+    "\n",
+    "mask = (\n",
+    "    (raw['tpep_pickup_datetime'].dt.date == pd.Timestamp(TARGET_DATE).date()) &\n",
+    "    (raw['tpep_pickup_datetime'].dt.hour >= TIME_START) &\n",
+    "    (raw['tpep_pickup_datetime'].dt.hour < TIME_END)\n",
+    ")\n",
+    "\n",
+    "df = raw[mask].copy().reset_index(drop=True)\n",
+    "print(f'Filtered ({TARGET_DATE} {TIME_START}:00~{TIME_END}:00): {len(df):,} trips')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. LocationID → Lat/Lon Mapping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mapped trips: 60,046\n",
+      "Missing pickup coords: 890\n",
+      "Missing dropoff coords: 899\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "\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>tpep_pickup_datetime</th>\n",
+       "      <th>PULocationID</th>\n",
+       "      <th>o_lat</th>\n",
+       "      <th>o_lon</th>\n",
+       "      <th>DOLocationID</th>\n",
+       "      <th>d_lat</th>\n",
+       "      <th>d_lon</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2017-10-19 06:00:25</td>\n",
+       "      <td>161</td>\n",
+       "      <td>40.758028</td>\n",
+       "      <td>-73.977698</td>\n",
+       "      <td>50</td>\n",
+       "      <td>40.766238</td>\n",
+       "      <td>-73.995135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2017-10-19 06:00:12</td>\n",
+       "      <td>162</td>\n",
+       "      <td>40.756688</td>\n",
+       "      <td>-73.972356</td>\n",
+       "      <td>230</td>\n",
+       "      <td>40.759818</td>\n",
+       "      <td>-73.984197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2017-10-19 06:01:32</td>\n",
+       "      <td>161</td>\n",
+       "      <td>40.758028</td>\n",
+       "      <td>-73.977698</td>\n",
+       "      <td>161</td>\n",
+       "      <td>40.758028</td>\n",
+       "      <td>-73.977698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2017-10-19 06:00:17</td>\n",
+       "      <td>132</td>\n",
+       "      <td>40.646985</td>\n",
+       "      <td>-73.786530</td>\n",
+       "      <td>66</td>\n",
+       "      <td>40.702259</td>\n",
+       "      <td>-73.985702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2017-10-19 06:00:14</td>\n",
+       "      <td>262</td>\n",
+       "      <td>40.775932</td>\n",
+       "      <td>-73.946510</td>\n",
+       "      <td>138</td>\n",
+       "      <td>40.774376</td>\n",
+       "      <td>-73.873628</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2017-10-19 06:03:42</td>\n",
+       "      <td>186</td>\n",
+       "      <td>40.748497</td>\n",
+       "      <td>-73.992438</td>\n",
+       "      <td>162</td>\n",
+       "      <td>40.756688</td>\n",
+       "      <td>-73.972356</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2017-10-19 06:00:47</td>\n",
+       "      <td>148</td>\n",
+       "      <td>40.718938</td>\n",
+       "      <td>-73.990896</td>\n",
+       "      <td>114</td>\n",
+       "      <td>40.728340</td>\n",
+       "      <td>-73.997380</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2017-10-19 06:02:13</td>\n",
+       "      <td>158</td>\n",
+       "      <td>40.735035</td>\n",
+       "      <td>-74.008984</td>\n",
+       "      <td>79</td>\n",
+       "      <td>40.727620</td>\n",
+       "      <td>-73.985937</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2017-10-19 06:31:28</td>\n",
+       "      <td>246</td>\n",
+       "      <td>40.753309</td>\n",
+       "      <td>-74.004016</td>\n",
+       "      <td>163</td>\n",
+       "      <td>40.764421</td>\n",
+       "      <td>-73.977569</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2017-10-19 06:46:07</td>\n",
+       "      <td>48</td>\n",
+       "      <td>40.762253</td>\n",
+       "      <td>-73.989845</td>\n",
+       "      <td>230</td>\n",
+       "      <td>40.759818</td>\n",
+       "      <td>-73.984197</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  tpep_pickup_datetime  PULocationID      o_lat      o_lon  DOLocationID  \\\n",
+       "0  2017-10-19 06:00:25           161  40.758028 -73.977698            50   \n",
+       "1  2017-10-19 06:00:12           162  40.756688 -73.972356           230   \n",
+       "2  2017-10-19 06:01:32           161  40.758028 -73.977698           161   \n",
+       "3  2017-10-19 06:00:17           132  40.646985 -73.786530            66   \n",
+       "4  2017-10-19 06:00:14           262  40.775932 -73.946510           138   \n",
+       "5  2017-10-19 06:03:42           186  40.748497 -73.992438           162   \n",
+       "6  2017-10-19 06:00:47           148  40.718938 -73.990896           114   \n",
+       "7  2017-10-19 06:02:13           158  40.735035 -74.008984            79   \n",
+       "8  2017-10-19 06:31:28           246  40.753309 -74.004016           163   \n",
+       "9  2017-10-19 06:46:07            48  40.762253 -73.989845           230   \n",
+       "\n",
+       "       d_lat      d_lon  \n",
+       "0  40.766238 -73.995135  \n",
+       "1  40.759818 -73.984197  \n",
+       "2  40.758028 -73.977698  \n",
+       "3  40.702259 -73.985702  \n",
+       "4  40.774376 -73.873628  \n",
+       "5  40.756688 -73.972356  \n",
+       "6  40.728340 -73.997380  \n",
+       "7  40.727620 -73.985937  \n",
+       "8  40.764421 -73.977569  \n",
+       "9  40.759818 -73.984197  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Pickup coordinates\n",
+    "df = df.merge(\n",
+    "    zone_coords[['LocationID', 'lat', 'lon']].rename(\n",
+    "        columns={'lat': 'o_lat', 'lon': 'o_lon'}\n",
+    "    ),\n",
+    "    left_on='PULocationID', right_on='LocationID', how='left'\n",
+    ").drop(columns='LocationID')\n",
+    "\n",
+    "# Dropoff coordinates\n",
+    "df = df.merge(\n",
+    "    zone_coords[['LocationID', 'lat', 'lon']].rename(\n",
+    "        columns={'lat': 'd_lat', 'lon': 'd_lon'}\n",
+    "    ),\n",
+    "    left_on='DOLocationID', right_on='LocationID', how='left'\n",
+    ").drop(columns='LocationID')\n",
+    "\n",
+    "print(f'Mapped trips: {len(df):,}')\n",
+    "print(f'Missing pickup coords: {df[\"o_lat\"].isna().sum()}')\n",
+    "print(f'Missing dropoff coords: {df[\"d_lat\"].isna().sum()}')\n",
+    "df[['tpep_pickup_datetime', 'PULocationID', 'o_lat', 'o_lon', 'DOLocationID', 'd_lat', 'd_lon']].head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Final trips (after dropping NaN): 58,988\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Drop rows with missing coordinates\n",
+    "df = df.dropna(subset=['o_lat', 'o_lon', 'd_lat', 'd_lon']).reset_index(drop=True)\n",
+    "print(f'Final trips (after dropping NaN): {len(df):,}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. Summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== NYC Yellow Taxi Preprocessing Summary ===\n",
+      "Date: 2017-10-19 (Thursday)\n",
+      "Time: 6:00 ~ 10:00\n",
+      "Total trips: 58,988\n",
+      "Pickup time range: 2017-10-19 06:00:02 ~ 2017-10-19 09:59:59\n",
+      "Lat range: 40.5770 ~ 40.8760\n",
+      "Lon range: -74.1740 ~ -73.7546\n",
+      "\n",
+      "Pickup by Borough:\n",
+      "borough\n",
+      "Manhattan    55328\n",
+      "Queens        2921\n",
+      "Brooklyn       709\n",
+      "Bronx           28\n",
+      "EWR              2\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('=== NYC Yellow Taxi Preprocessing Summary ===')\n",
+    "print(f'Date: {TARGET_DATE} (Thursday)')\n",
+    "print(f'Time: {TIME_START}:00 ~ {TIME_END}:00')\n",
+    "print(f'Total trips: {len(df):,}')\n",
+    "print(f'Pickup time range: {df[\"tpep_pickup_datetime\"].min()} ~ {df[\"tpep_pickup_datetime\"].max()}')\n",
+    "print(f'Lat range: {df[\"o_lat\"].min():.4f} ~ {df[\"o_lat\"].max():.4f}')\n",
+    "print(f'Lon range: {df[\"o_lon\"].min():.4f} ~ {df[\"o_lon\"].max():.4f}')\n",
+    "print()\n",
+    "\n",
+    "# Borough distribution\n",
+    "pu_borough = df.merge(\n",
+    "    zone_coords[['LocationID', 'borough']],\n",
+    "    left_on='PULocationID', right_on='LocationID', how='left'\n",
+    ")\n",
+    "print('Pickup by Borough:')\n",
+    "print(pu_borough['borough'].value_counts().to_string())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saved: nyc_taxi_2017-10-19_morning.csv (58,988 rows)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Save as CSV\n",
+    "output = df[[\n",
+    "    'tpep_pickup_datetime', 'tpep_dropoff_datetime',\n",
+    "    'PULocationID', 'DOLocationID',\n",
+    "    'o_lat', 'o_lon', 'd_lat', 'd_lon',\n",
+    "    'passenger_count', 'trip_distance', 'total_amount'\n",
+    "]].copy()\n",
+    "\n",
+    "output.to_csv(f'{DATA_DIR}/nyc_taxi_{TARGET_DATE}_morning.csv', index=False)\n",
+    "print(f'Saved: nyc_taxi_{TARGET_DATE}_morning.csv ({len(output):,} rows)')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

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